Project Celsius

Strategic Fleet Expansion & Autonomous Deployment Model

Confidential • Authorized Personnel Only

Celsius Expedited Network

Executive Summary

Strategic Analysis & Network Overview

The Celsius Expedited Network is in an early build phase, designed not as a traditional trucking operation, but as an engineered, time-definite operating system. This approach represents a fundamental shift in strategy, effectively applying the principles of Precision Scheduled Railroading (PSR) to the highway—a model we define as "Precision Truckload."

Just as PSR revolutionized rail by shifting focus from "moving trains when full" to "moving trains on a schedule," the Celsius "Precision Truckload" model prioritizes network velocity and disciplined cadence over opportunistic freight acceptance. The thesis is clear: time-definite reliability is manufactured through deliberate design choices—committed Expedited Lanes (ELs), rigid schedules, and repeatable operating procedures—rather than by chasing yield on individual loads.

Though early in the development process, this "Precision Truckload" approach has already demonstrated the same durable economic lift seen in successful PSR implementations:

Asset Velocity: By adhering to a scheduled network rather than waiting for optimized density, the Expedited Network delivered an Operating Ratio (OR) of 86.2, compared to 108.6 for the standard Over-the-Road (OTR) network.
Utilization as the Driver: Much like PSR reduces railcar dwell, Celsius has drastically reduced tractor dwell. Operational velocity for Expedited is approximately ~45mph versus ~23mph for OTR.
Cost Structure Efficiency: The performance gap is not driven by premium pricing, but by the removal of "network friction." Deadhead is lower (13% vs. 16.5%), and freight-to-capacity matching is tighter.

Data Selection & Comparative Performance: KSMTA isolated the comparative results (OTR vs. Expedited) to the period between October 25, 2025, and January 10, 2026. This specific interval was selected to capture the Expedited network's performance after a critical volume expansion, ensuring the data reflects the network's current operating scale rather than early-stage volatility.

Key Finding: The analysis reveals a critical divergence: while the OTR network commands a higher Yield (revenue per loaded mile), it fails to convert that advantage into actual Margin. OTR profitability is eroded by operational friction—specifically dwell, variability, and market pricing pressure. In contrast, the Expedited Network converts revenue to profit more efficiently by adhering to Precision Truckload principles: enforcing schedule discipline and protecting asset utilization.

This comparison indicates the "financial prize" available to Celsius. By treating the truck not as a variable asset that chases freight, but as a scheduled asset that freight must conform to, Celsius is building a network engineered for repeatability, cadence, and velocity. This structure is the requisite foundation for layering in autonomous capability, which acts as the ultimate force multiplier for a precision-based network.

SWOT Analysis: Celsius Expedited Network

Strengths (Internal)

Superior Financial Performance: The network is demonstrating an Operating Ratio (OR) of 86.2 versus the OTR network's 108.6. This is achieved through efficiency rather than premium pricing.
The "Intentionality Standard": A disciplined operating model that prioritizes engineered commitments, defined schedules, and repeatable processes over daily optimization or opportunistic freight acceptance.
Operational Velocity: Significantly higher velocity (~45mph) compared to OTR (~23mph), driven by lower deadhead (13%) and better freight-to-capacity matching.
Experienced Leadership: Led by an executive with a proven playbook for designing scaled expedited networks, ensuring governance and preventing scope creep.
Risk-Mitigated Growth Strategy: The "Incubation Process" uses OTR assets to validate lanes and freight behavior before committing dedicated expedited capacity, reducing upfront capital risk.
Engineered Seasonality: Rather than reacting to produce shifts, the network embeds seasonal lane maps and launch-point adjustments (e.g., shifting origin from Mexico to California) into the design.

Weaknesses (Internal)

Infrastructure Gaps: The current physical network requires significant expansion to support the engineered model. Specific needs include capacity expansion in Dallas, a larger site in Kansas City, and a new yard agreement in Laredo.
High-Consequence Environment: Operating within the refrigerated truckload (TL) sector introduces higher variance and higher penalties for failure compared to dry van networks.
Early Build Phase Maturity: The network is still in the early stages, relying on a limited number of active lanes (6 active corridors mentioned), limiting broad geographic reach.
Financial Modeling Blind Spots: The current "Expedited Calculator" and financial planning approach risks overstating immediate profitability by under-weighting the total cost of ownership (TCO) required to support an engineered, autonomous-ready network. Key blind spots include:
- Infrastructure "Burden": The model recognizes infrastructure as existing "sunk costs" rather than variable costs necessary for growth. Without detailed analysis, proforma net margins are inflated.
- Autonomous CAPEX Shock: Modeling autonomous trucks as "labor savings" without accounting for significantly higher upfront acquisition costs creates a Cash Flow Trough in early stages.
- Accelerated Asset Depreciation: Assuming standard 4-5 year useful life while projecting autonomous utilization levels compresses a 4-year truck into a 2-year truck, creating a "profit mirage."

Opportunities (External)

Autonomous Trucking Integration: Autonomy is identified as a "force multiplier," offering potential to break human hours-of-service constraints, remove friction costs, increase effective utilization, and reduce cost-to-serve through continuous operation.
Geographic Expansion: Evaluation is underway for new nodes in South Atlanta, Oregon, Salt Lake City, Las Vegas, and Denver, which would densify the network and reduce execution risk.
Future Pricing Power: While currently relying on efficiency for margin, establishing a reputation for time-definite reliability will allow Celsius to command premium pricing when the broader truckload market cycle turns favorable.
Take-or-Pay Structures: Moving customers toward "intentional volume commitments" and take-or-pay constructs can stabilize revenue and insulate the network from market volatility.
Counter-Cyclical Competitive Positioning: While the industry has paused investment due to prolonged freight recession, Celsius is accelerating—defining a new category where reliability is a product of design, not just driver effort.

Threats (External)

Operational "Drift": The risk that sales, operations, or pricing teams revert to "opportunistic freight acceptance," which would erode the cadence and utilization that make the model profitable.
Market Environment: The current truckload market does not support premium pricing, forcing the network to rely entirely on internal cost efficiency to generate margin.
Shipper Non-Compliance: The model relies heavily on customer behavior (appointment discipline, facility performance). If shippers fail to meet these engineered standards, the schedule integrity—and thus the profitability—collapses.
Infrastructure Constraints: If the necessary terminals and drop lots are not acquired or funded in time, they will become the primary bottleneck to scaling, regardless of freight demand.
Autonomous Equipment Providers: AV technology developers (Aurora, Waymo, Kodiak) may pursue vertical integration strategies—partnering directly with shippers or acquiring carrier assets—to capture freight margin rather than selling technology to carriers. This disintermediation risk could marginalize traditional carriers who fail to secure early AV partnerships or develop proprietary autonomous capabilities.

Expedited Network Overview

The Expedited Network operates within the Company's OTR temperature-controlled platform but functions as a distinct product. While it shares assets, it does not share the same operating philosophy. OTR seeks optimization; Expedited seeks repetition.

The structure mirrors Less-Than-Truckload (LTL) linehaul logic: scheduled departures, defined routes, and strict timing. However, this is executed in the high-variance environment of refrigerated truckload freight. The strategy relies on a simple formula: Density creates efficiency, efficiency creates velocity, and velocity creates profitability.

The "Precision Standards" (Intentionality)

To prevent operational drift, the network enforces four engineered standards:

Disciplined Customer Selection: Not all freight fits the network. Onboarding requires strict appointment discipline, specific yard processes, and agreed-upon escalation protocols.
Volume Commitments: Stability is achieved through "low-water-mark" volume protections and, where feasible, take-or-pay contracts.
Schedule Integrity: Lanes are designed with repeatable launch points and predictable cycle times. The mandate is to run the schedule, not just the load.
True Cost Attribution: The cost model must allocate specific expedited support costs (security, trailer positioning, yard labor) to the lane, ensuring leadership sees the real unit economics.

Leadership & Governance

The initiative is led by executive leadership with a proven track record in designing scaled OTR and expedited networks. This experience provides the necessary governance to prevent the organization from sliding back into "opportunistic" freight acceptance, which protects the network's cadence and utilization.

Engineered Seasonality

Seasonality is a design input, not a surprise. As an example, produce origins shift across the calendar (e.g., from Mexico to California), and these shifts are embedded into the lane architecture. The approach uses predefined lane swaps and planned launch-point adjustments to preserve schedule integrity. The result: avoid paying for seasonality through empty miles or network breakage.

The Incubation Process (Risk Mitigation)

Less speculation on capacity. The network grows through a staged "prove-it" process:

Selection: Identify high-potential lanes with consistent volume and committed customers.
Incubation: Run the lane using OTR assets first. This validates facility readiness, dwell times, and freight consistency without stranding expensive expedited assets. Earn while you learn.
Conversion: Only once the lane demonstrates repeatable cycle times and stable utilization, can it be marked for inclusion to the dedicated Expedited.

Current Footprint & Infrastructure

An engineered network requires a physical operating system. Terminals, yards, and drop lots are not "ancillary" support; they are the production floor. As the network scales, physical space—not freight demand—will be the primary constraint.

Active Lanes & Capacity

The current network is built around committed corridors with explicit truck positions:

Los Angeles ↔ Dallas: 24 trucks
Laredo ↔ Dallas: 16 trucks
Indiana ↔ North Carolina: 8 trucks
Indiana ↔ Pennsylvania: 8 trucks
Texas ↔ Kansas: 4 trucks
Indiana ↔ Kansas: 4 trucks

Node Readiness & Expansion

Operational Nodes: Los Angeles (San Bernardino drop lot), Indianapolis (Terminal), Memphis, Oklahoma.
Immediate Needs: Dallas (Capacity expansion), Kansas City (Site expansion), Laredo (Yard agreement pending), Carlisle, PA (New leased lot).
Future Nodes (Evaluation): South Atlanta, Oregon, Salt Lake City, Las Vegas, Denver.

Financial Implication: The "Infrastructure Burden"

Infrastructure costs must be treated as variable costs of growth, not fixed corporate overhead. Facility leases, yard security, and maintenance coverage scale linearly with lane density. Excluding these from lane-level P&L modeling overstates margins and hides the true effort required to deliver time-definite service.

Operating & Commercial Requirements

Operations: Execute the Schedule

The goal is to move from "managing chaos" to "managing exceptions."

Standardized Recovery: Dispatchers use pre-set playbooks for disruptions rather than negotiating solutions daily.
Strict Thresholds: Defined triggers determine when to pivot capacity or reject freight to save the broader schedule.
Seasonal Transitions: Playbooks dictate exactly when lanes pivot and how capacity repositions, preventing decision paralysis during produce shifts.

Commercial: Contract for Behavior

In the near term, monetize reliability, not price.

Behavior over Rates: Prioritize contracts that enforce consistency—appointment adherence, cancellation penalties, and volume floors.
Mode Agnostic / Profile Specific: Utilize dry van freight to fill network gaps ("Universal Capacity"), provided the freight profile matches velocity requirements (e.g., drop-and-hook, no dwell).
Future Pricing: Premium pricing will follow proven reliability. Once the network scale and reputation are established, and the market cycle turns, pivot to yield expansion.

Autonomous Trucking: The Force Multiplier

In the Celsius Expedited Network, autonomous trucking is not treated as a novelty or an experiment; it is the ultimate realization of the Precision Truckload thesis. The expedited network is engineered to reduce variability for human drivers; that same engineering makes it the ideal operating environment for Autonomous Vehicle (AV) technology.

While traditional carriers view autonomy primarily as a labor solution (replacing the driver), Celsius views it as an Asset Utilization Solution. The goal is to decouple revenue generation from human physiological constraints.

1. Operational Mechanics: The "Continuous Chain"

Standard OTR trucks are legally capped by Hours of Service (HOS)—an 11-hour driving window followed by a mandatory 10-hour reset. This effectively idles the revenue-generating asset for 50%+ of its available life.

Autonomy in the Celsius model introduces the "Continuous Chain" concept:

The Hub-to-Hub Machine: AV units operate strictly on the long-haul middle mile (e.g., Dallas terminal to LA drop lot). They do not perform pickup or delivery (P&D).
The 22-Hour Day: By eliminating mandatory sleep breaks, an autonomous tractor can operate 20–22 hours per day, stopping only for fueling and safety checks.
Velocity Math: A human driver averages ~500 miles/day. An AV unit averages ~900–1,000 miles/day. This effectively doubles the revenue production of a single capital asset (the tractor) without doubling the fleet size.

2. Financial Impact: Shifting the Cost Structure

Autonomy fundamentally alters the unit economics of the lane.

Fixed vs. Variable Swap: Trade the high variable cost of human labor (wages, benefits, recruiting, retention) for a higher upfront fixed cost (technology hardware, software licensing, sensor suites).
Cost-to-Serve Reduction: While the upfront CapEx is higher, the cost-per-mile decreases significantly over the life of the asset due to the elimination of driver pay (typically 30-40% of linehaul cost) and the doubling of mileage efficiency.
Insurance & Claims: Over time, the removal of human error—distraction, fatigue, impairment—is projected to lower insurance premiums and claims reserves, a critical factor in high-value refrigerated freight.

3. Network Stability & Service Perfection

In a time-definite network, variance is the enemy. Humans introduce variance (sick days, family emergencies, fatigue management). Robots offer predictable consistency.

Cycle Time Precision: An AV unit traveling from Laredo to Detroit has a predictable transit time with a variance of minutes, not hours. This allows dispatchers to tighten appointment windows and reduce "buffer time" in the schedule.
Reduction of Recovery Costs: A significant portion of expedited margin is lost to "service recovery"—paying for repowers, last-minute relays, or team drivers to save a late load. AV reliability drastically reduces the frequency of these expensive operational "band-aids."

4. The "Hybrid Deployment" Strategy

Celsius will not flip a switch to full autonomy. They are executing a staged Hybrid Deployment Model:

Phase 1: The "Launchpad" (Current State): Human drivers validate the lane—the facility processes, the gate times, and the customer volume.
Phase 2: The "Pilot" (Supervised Autonomy): AV units run the middle mile with a safety driver present to intervene if necessary. This gathers data and maps the route nuances.
Phase 3: The "Driver-Out" (Hub-to-Hub): Fully autonomous operation on the interstate leg. Human "drayage" drivers handle the complex first and final mile (shipper to terminal / terminal to receiver).

5. Strategic Synergy: Why Celsius Wins with AV

A small number of truckload carriers are contemplating "layering" autonomy onto "messy" networks: random routes, unpredictable customers, and variable freight. Autonomy fails in chaos. Because Celsius has already done the hard work of "engineering" the freight—building clean lanes, enforcing "Precision Truckload" discipline, and standardizing drop lots—they have started to build the "tracks" for the autonomous "train." They are not retrofitting autonomy; they are plugging it into a system designed to receive it.

Strategic Conclusion

The Celsius Expedited Network is transitioning from design to execution. By applying "Precision Truckload" principles, they have already proven that a scheduled, engineered model outperforms the traditional OTR model in margin (86.2 OR vs 108.6 OR) and velocity.

Success moving forward requires rigid adherence to two rules:

Do Not Drift: Avoid the temptation to accept opportunistic freight that degrades network velocity, regardless of the level of external traditional truckload market rates. A line must be drawn in the sand.
Fund the Nodes: Accept that infrastructure is a core operating cost and fund it ahead of the curve to prevent bottlenecks.

Ultimately, Celsius is building a machine that converts Miles into Margin more efficiently than any competitor. The near-term goal is to scale this machine while protecting the discipline that makes it profitable.

Overview

The Company is a large-scale, asset-based, temperature-controlled transportation and logistics platform operating across the contiguous United States. With a multi-decade operating history, the business has established itself as a top-tier provider of refrigerated freight services to blue-chip customers in food, protein, grocery, beverage, pharmaceutical, retail, and specialty logistics markets.

The Company generates approximately $1.0 billion in annual revenue, operates a fleet of roughly 3,000 power units and 5,000 trailers, employs approximately 4,000 team members, and maintains a coast-to-coast terminal footprint that enables national service coverage.

Business Model

The Company operates through three complementary divisions, providing diversified revenue streams and strong customer retention.

Over-the-Road (OTR) Refrigerated Transportation

Long-haul, temperature-controlled freight
Serves protein, produce, grocery, beverage, pharmaceutical, and high-value cargo
Emphasis on safety, compliance, and reliability
Largest division by revenue and fleet count

Dedicated Transportation Solutions

Customized, multi-year contracted fleets for large customers
Highest margin and fastest-growing division
Predictable revenue, strong pricing power, and low churn
Focus area for fleet expansion over the next 3–5 years

Logistics & Brokerage Solutions

Asset-light brokerage and freight management
Enhances customer stickiness and network efficiency
Provides flexibility during market volatility

Dedicated services represent approximately 30% of revenue, providing downside protection during freight cycles.

Customers and Revenue Profile

Approximately 286 active customers
Highly diversified customer base with no single customer exceeding ~17% of revenue
Long-tenured relationships with large national shippers, many exceeding 10–25 years
Strong mix across grocery, protein, food service, beverage, healthcare, retail, and specialty freight

Revenue by commodity is heavily weighted toward essential, non-discretionary goods, providing resilience through economic cycles.

Market Opportunity

Operates within the U.S. refrigerated trucking market, valued at approximately $27.5 billion in 2023
Domestic refrigerated freight is projected to grow at a ~7.8% CAGR through 2029
Market remains highly fragmented, with the largest competitor holding only ~5% market share
Industry dynamics favor scaled operators with safety, technology, and capital advantages

The sector is emerging from a multi-year downturn caused by excess capacity, inflation, and rate pressure, creating a favorable entry point for consolidation.

Competitive Advantages

Scale and Network Density across 48 states
High safety performance, including best-in-class CSA scores and declining accident rates
Long-standing customer relationships with embedded operations
Strong driver-centric culture, supporting retention and service reliability
Modern fleet and infrastructure, supporting operational efficiency
Advanced technology adoption, including cloud-based TMS, AI-enabled driver safety systems, advanced EDI and API customer integrations, and early participation in autonomous vehicle pilots

Growth Strategy

The Company's growth plan is built on three parallel levers:

1. Organic Growth

Expansion of the Dedicated fleet from ~800 trucks to over 2,000
Continued customer penetration and share expansion
Pricing recovery as industry capacity rationalizes

2. Strategic M&A and Industry Consolidation

Targeting 4–6 mid-sized or 1–2 large acquisitions
Focus on companies with succession issues, under-optimized operations, or capital constraints
Pre-screened pipeline of acquisition candidates across multiple regions

3. Operational and Technology-Driven Margin Expansion

Cost synergies from scale
Network optimization
Technology-enabled productivity improvements
Autonomous and semi-autonomous initiatives over the medium term

Combined organic growth and acquisitions are expected to support a path toward $5.0 billion in revenue within 7–10 years.

Financial Profile (Base Case)

Historical Adjusted EBITDA margins in the mid-teens, temporarily pressured by industry conditions
Base case forecast assumes organic growth only, with EBITDA expanding to ~$295 million by 2027
Operating ratio improves steadily into the high-80% range
Strong free cash flow generation once growth capex moderates

Recapitalization and Investor Returns

The proposed recapitalization contemplates approximately $500 million of new equity, enabling accelerated growth and acquisitions.

Illustrative outcomes show:

IRRs ranging from mid-teens to 30%+, depending on EBITDA growth and exit multiple
MOIC outcomes of 2.0x–5.0x+ under strategic growth scenarios
Multiple exit paths including strategic sale, private equity recapitalization, public market listing, or long-term hold with cash yield

Risk Profile and Mitigation

Key risks include freight cyclicality, labor availability, fuel volatility, and regulatory compliance. These are mitigated through:

Contracted revenue mix
Safety and compliance leadership
Fuel surcharge programs
Diversified customer and commodity exposure
Scaled operating platform

Investment Thesis

The Company represents a rare opportunity to invest in a scaled, essential-services transportation platform at a cyclical inflection point, with:

Clear line of sight to organic growth
A compelling consolidation opportunity
Strong operational discipline
Significant upside from margin recovery and scale

Temperature-Controlled Transportation

The Platform

A scaled, asset-based, temperature-controlled transportation and logistics platform with $1.0B annual revenue, 3,000+ power units, and a multi-decade operating history serving America's essential supply chains.

Platform At-a-Glance

~$1.0B

Annual Revenue

~3,000

Power Units

~5,000

Trailers

~4,000

Team Members

286

Active Customers

State Coverage

Three Complementary Divisions

Over-the-Road (OTR) Refrigerated

Largest Division

Long-haul, temperature-controlled freight serving protein, produce, grocery, beverage, pharmaceutical, and high-value cargo. Emphasis on safety, compliance, and reliability.

Dedicated Transportation

Highest Margin

Customized, multi-year contracted fleets for large customers. Predictable revenue, strong pricing power, and low churn. Focus area for expansion: 800 → 2,000+ trucks.

Logistics & Brokerage

Asset-Light

Asset-light brokerage and freight management. Enhances customer stickiness and network efficiency. Provides flexibility during market volatility.

Expedited Network

Future Star

Precision Truckload operations applying scheduled railroading principles to highway freight—engineered for time-definite reliability, network velocity, and autonomous readiness. Early results show 22-point OR advantage over traditional OTR with 2x operational velocity.

Downside Protection: Dedicated services represent ~30% of revenue, providing stability through freight cycles.

Market Opportunity

U.S. Reefer Market (2023) TAM

Market Size $27.5B

Highly fragmented, largest player ~5% share

Projected CAGR Through 2029

Growth Rate ~7.8%

Essential goods demand driving growth

Revenue Target 7-10 Years

Organic + M&A $5.0B

5x growth through consolidation

Competitive Advantages

Scale & Network Density (48 states)

Best-in-Class Safety (CSA scores)

10-25+ Year Customer Relationships

Driver-Centric Culture & Retention

Cloud TMS & AI Safety Systems

Autonomous Vehicle Pilot Participant

Enter Project Celsius

The Expedited Network: Where Foundation Meets Future

Project Celsius transforms this proven platform into something unprecedented: a Precision Truckload operation applying scheduled railroading principles to highway freight. The existing OTR infrastructure provides the scale, customer relationships, and operational expertise. Celsius adds the network design, cadence discipline, and autonomous readiness that unlock the next tier of margin and growth.

From OTR Baseline

108 OR, 23 mph velocity, reactive dispatch

To Expedited Model

86 OR, 45 mph velocity, scheduled precision

Three-Lever Growth Strategy

Organic Growth

Expand Dedicated fleet from ~800 to 2,000+ trucks. Customer penetration and share expansion. Pricing recovery as capacity rationalizes.

Strategic M&A

Target 4-6 mid-sized or 1-2 large acquisitions. Focus on succession issues, under-optimized operations, capital constraints. Pre-screened pipeline across regions.

Operational Excellence + Technology

Cost synergies from scale. Network optimization. Technology-enabled productivity. Autonomous and semi-autonomous initiatives over medium term.

Financial Profile & Returns

Historical EBITDA Margin Baseline

Margins Mid-Teens

Temporarily pressured by industry conditions

2027 EBITDA Forecast Base Case

Organic Only ~$295M

OR improving to high-80% range

Illustrative IRR Strategic

Range 15-30%+

2.0x - 5.0x+ MOIC under growth scenarios

Recapitalization: ~$500M new equity contemplated to accelerate growth and acquisitions. Multiple exit paths: strategic sale, PE recap, public listing, or long-term hold with cash yield.

Celsius Expedited Network

Precision Truckload

An engineered, time-definite operating system applying Precision Scheduled Railroading (PSR) principles to highway freight. Not a traditional trucking operation—a network designed for repeatability, cadence, and velocity.

FREIGHTMATH DASHBOARD

Key Highlights

Proven Performance: Expedited vs. OTR

Data period: October 25, 2025 – January 10, 2026 (post volume expansion)

Operating Ratio 22.4pt Advantage

Expedited 86.2

OTR 108.6

Efficiency-driven margin, not premium pricing

Operational Velocity 2x Faster

Expedited ~45

OTR ~23

mph — Drastically reduced tractor dwell time

Deadhead Percentage 3.5pt Lower

Expedited 13%

OTR 16.5%

Tighter freight-to-capacity matching

Key Finding: While OTR commands higher Yield (revenue per loaded mile), it fails to convert that advantage into Margin. OTR profitability is eroded by operational friction—dwell, variability, and market pricing pressure. The Expedited Network converts revenue to profit more efficiently through schedule discipline and asset utilization protection. This comparison indicates the "financial prize" available to Celsius.

Current Network Footprint

Active Lanes & Capacity

Los Angeles Dallas

24 trucks

Laredo Dallas

16 trucks

Indiana North Carolina

8 trucks

Indiana Pennsylvania

8 trucks

Texas Kansas

4 trucks

Indiana Kansas

4 trucks

Total Active Capacity 64 trucks

Node Status

Operational

Los Angeles (San Bernardino) Indianapolis (Terminal) Memphis Oklahoma

Immediate Needs

Dallas (Capacity expansion) Kansas City (Site expansion) Laredo (Yard agreement pending) Carlisle, PA (New leased lot)

Future Evaluation

South Atlanta Oregon Salt Lake City Las Vegas Denver

Rule #1: Do Not Drift

Avoid accepting opportunistic freight that degrades network velocity, regardless of external market rates. A line must be drawn in the sand.

Rule #2: Fund the Nodes

Accept that infrastructure is a core operating cost and fund it ahead of the curve to prevent bottlenecks.

Ultimately, Celsius is building a machine that converts Miles into Margin more efficiently than any competitor. The near-term goal is to scale this machine while protecting the discipline that makes it profitable.

SWOT Analysis

Click each section to expand full details

Strengths 6 factors

Superior OR (86.2) Intentionality Standard 2.3x Velocity +3 more

Superior Financial Performance

The network is demonstrating an Operating Ratio (OR) of 86.2 versus the OTR network's 108.6. This is achieved through efficiency rather than premium pricing.

The "Intentionality Standard"

A disciplined operating model that prioritizes engineered commitments, defined schedules, and repeatable processes over daily optimization or opportunistic freight acceptance.

Operational Velocity

Significantly higher velocity (~45mph) compared to OTR (~23mph), driven by lower deadhead (13% vs 16.5%) and better freight-to-capacity matching.

Experienced Leadership

Led by an executive with a proven playbook for designing scaled expedited networks, ensuring governance and preventing scope creep.

Risk-Mitigated Growth Strategy

The "Incubation Process" uses OTR assets to validate lanes and freight behavior before committing dedicated expedited capacity, reducing upfront capital risk.

Engineered Seasonality

Rather than reacting to produce shifts, the network embeds seasonal lane maps and launch-point adjustments (e.g., shifting origin from Mexico to California) into the design.

Weaknesses 4 factors

Infrastructure Gaps High-Consequence Sector Financial Blind Spots +1 more

Infrastructure Gaps

The current physical network requires significant expansion to support the engineered model. Specific needs include capacity expansion in Dallas, a larger site in Kansas City, and a new yard agreement in Laredo.

High-Consequence Environment

Operating within the refrigerated truckload (TL) sector introduces higher variance and higher penalties for failure compared to dry van networks.

Early Build Phase Maturity

The network is still in the early stages, relying on a limited number of active lanes (6 active corridors), limiting broad geographic reach.

Financial Modeling Blind Spots

The current "Expedited Calculator" and financial planning approach risks overstating immediate profitability:

Infrastructure "Burden": The model recognizes infrastructure (yards, security, terminals) as existing "sunk costs" rather than variable costs necessary for growth. Without detailed analysis, proforma net margins are inflated. If a new lane requires a leased drop lot in Carlisle, PA to function, that lease cost must be allocated to that lane's unit economics.

Autonomous CAPEX Shock: Modeling autonomous trucks simply as "labor savings" without accounting for significantly higher upfront acquisition cost (technology hardware + software licensing + integration). This creates a Cash Flow Trough in early stages—while OPEX drops, CAPEX spikes.

Accelerated Asset Depreciation: Assuming standard 4-5 year useful life while projecting "autonomous utilization" levels. The "Force Multiplier" effect means trucks running 200,000+ miles/year vs 100,000 miles/year—compressing a 4-year truck into a 2-year truck. Monthly depreciation expense must double to match accelerated consumption, otherwise creating a "profit mirage."

Opportunities 5 factors

AV Force Multiplier Geographic Expansion Pricing Power +2 more

Autonomous Trucking Integration

Autonomy is identified as a "force multiplier." It offers the potential to break human hours-of-service, remove other 'friction costs' (e.g. idling, out-of-route mileage, maintenance compliance), increase effective utilization, and reduce cost-to-serve through continuous operation.

Geographic Expansion

Evaluation is underway for new nodes in South Atlanta, Oregon, Salt Lake City, Las Vegas, and Denver, which would densify the network and reduce execution risk.

Future Pricing Power

While currently relying on efficiency for margin, establishing a reputation for time-definite reliability will allow Celsius to command premium pricing when the broader truckload market cycle turns favorable.

Take-or-Pay Structures

Moving customers toward "intentional volume commitments" and take-or-pay constructs can stabilize revenue and insulate the network from market volatility.

Counter-Cyclical Competitive Positioning

While the industry has paused investment due to prolonged freight recession, Celsius is accelerating. By coupling counter-cyclical asset acquisition with the "Precision Truckload" operating system, Celsius is doing more than just gaining market share—it is defining a new category. This engineered approach creates separation from traditional "opportunistic" carriers, effectively carving out a proprietary niche where reliability is a product of design, not just driver effort.

Threats 4 factors

Operational Drift Market Environment Shipper Compliance +2 more

Operational "Drift"

The risk that sales, operations, or pricing teams revert to "opportunistic freight acceptance," which would erode the cadence and utilization that make the model profitable.

Market Environment

The current truckload market does not support premium pricing, forcing the network to rely entirely on internal cost efficiency to generate margin.

Shipper Non-Compliance

The model relies heavily on customer behavior (appointment discipline, facility performance). If shippers fail to meet these engineered standards, the schedule integrity—and thus the profitability—collapses.

Infrastructure Constraints

If the necessary terminals and drop lots (the "physical operating system") are not acquired or funded in time, they will become the primary bottleneck to scaling, regardless of freight demand.

Autonomous Equipment Providers

AV technology developers may pursue vertical integration—partnering directly with shippers or acquiring carrier assets—to capture freight margin rather than selling technology to carriers. This disintermediation risk could marginalize traditional carriers who fail to secure early AV partnerships.

Expedited Network Overview

The Expedited Network operates within the Company's OTR temperature-controlled platform but functions as a distinct product. While it shares assets, it does not share the same operating philosophy. OTR seeks optimization; Expedited seeks repetition.

The Precision Standards (Intentionality)

To prevent operational drift, the network enforces four engineered standards

Disciplined Customer Selection

Not all freight fits the network. Onboarding requires strict appointment discipline, specific yard processes, and agreed-upon escalation protocols.

Volume Commitments

Stability is achieved through "low-water-mark" volume protections and, where feasible, take-or-pay contracts.

Schedule Integrity

Lanes are designed with repeatable launch points and predictable cycle times. The mandate is to run the schedule, not just the load.

True Cost Attribution

The cost model must allocate specific expedited support costs (security, trailer positioning, yard labor) to the lane, ensuring leadership sees real unit economics.

The Incubation Process (Risk Mitigation)

Less speculation on capacity. The network grows through a staged "prove-it" process.

1. Selection

Identify high-potential lanes with consistent volume and committed customers.

2. Incubation

Run the lane using OTR assets first. This validates facility readiness, dwell times, and freight consistency without stranding expensive expedited assets. Earn while you learn.

3. Conversion

Only once the lane demonstrates repeatable cycle times and stable utilization, can it be marked for inclusion to the dedicated Expedited.

Operating & Commercial Requirements

Operations: Execute the Schedule

The goal is to move from "managing chaos" to "managing exceptions."

Standardized Recovery: Dispatchers use pre-set playbooks for disruptions rather than negotiating solutions daily.
Strict Thresholds: Defined triggers determine when to pivot capacity or reject freight to save the broader schedule.
Seasonal Transitions: Playbooks dictate exactly when lanes pivot and how capacity repositions, preventing decision paralysis during produce shifts.

Commercial: Contract for Behavior

In the near term, monetize reliability, not price.

Behavior over Rates: Prioritize contracts that enforce consistency—appointment adherence, cancellation penalties, and volume floors.
Mode Agnostic / Profile Specific: Utilize dry van freight to fill network gaps ("Universal Capacity"), provided the freight profile matches velocity requirements (e.g., drop-and-hook, no dwell).
Future Pricing: Premium pricing will follow proven reliability. Once network scale and reputation are established, and the market cycle turns, pivot to yield expansion.

Autonomous Trucking: The Force Multiplier

In the Celsius Expedited Network, autonomous trucking is not treated as a novelty or an experiment—it is the ultimate realization of the Precision Truckload thesis. The expedited network is engineered to reduce variability for human drivers; that same engineering makes it the ideal operating environment for AV technology.

While traditional carriers view autonomy primarily as a labor solution (replacing the driver), Celsius views it as an Asset Utilization Solution. The goal is to decouple revenue generation from human physiological constraints.

1. Operational Mechanics: The "Continuous Chain"

The Hub-to-Hub Machine

AV units operate strictly on the long-haul middle mile (e.g., Dallas terminal to LA drop lot). They do not perform pickup or delivery (P&D).

The 22-Hour Day

By eliminating mandatory sleep breaks, an autonomous tractor can operate 20–22 hours per day, stopping only for fueling and safety checks.

Velocity Math

A human driver averages ~500 miles/day. An AV unit averages ~900–1,000 miles/day. This effectively doubles the revenue production of a single capital asset (the tractor) without doubling the fleet size.

2. Financial Impact: Shifting the Cost Structure

Autonomy fundamentally alters the unit economics of the lane.

Fixed vs. Variable Swap: Trade the high variable cost of human labor (wages, benefits, recruiting, retention) for a higher upfront fixed cost (technology hardware, software licensing, sensor suites).

Cost-to-Serve Reduction: While the upfront CapEx is higher, the cost-per-mile decreases significantly over the life of the asset due to the elimination of driver pay (typically 30-40% of linehaul cost) and the doubling of mileage efficiency.

Insurance & Claims: Over time, the removal of human error—distraction, fatigue, impairment—is projected to lower insurance premiums and claims reserves, a critical factor in high-value refrigerated freight.

3. Network Stability & Service Perfection

In a time-definite network, variance is the enemy. Humans introduce variance (sick days, family emergencies, fatigue management). Robots offer predictable consistency.

Cycle Time Precision

An AV unit traveling from Laredo to Detroit has a predictable transit time with a variance of minutes, not hours. This allows dispatchers to tighten appointment windows and reduce "buffer time" in the schedule.

Reduction of Recovery Costs

A significant portion of expedited margin is lost to "service recovery"—paying for repowers, last-minute relays, or team drivers to save a late load. AV reliability drastically reduces the frequency of these expensive operational "band-aids."

4. The "Hybrid Deployment" Strategy

Celsius will not flip a switch to full autonomy. They are executing a staged Hybrid Deployment Model:

Phase 1

The "Launchpad"

Current State

Human drivers validate the lane: the facility processes, the gate times, and the customer volume.

Phase 2

The "Pilot"

Supervised Autonomy

AV units run the middle mile with a safety driver present to intervene if necessary. This gathers data and maps the route nuances.

Phase 3

"Driver-Out"

Hub-to-Hub

Fully autonomous operation on the interstate leg. Human "drayage" drivers handle the complex first and final mile (shipper to terminal / terminal to receiver).

5. Strategic Synergy: Why Celsius Wins with AV
A small number of truckload carriers are contemplating "layering" autonomy onto "messy" networks: random routes, unpredictable customers, and variable freight. Autonomy fails in chaos. Because Celsius has already done the hard work of "engineering" the freight—building clean lanes, enforcing "Precision Truckload" discipline, and standardizing drop lots—they have started to build the "tracks" for the autonomous "train." They are not retrofitting autonomy; they are plugging it into a system designed to receive it.

Strategic Conclusion

The Celsius Expedited Network is transitioning from design to execution. By applying "Precision Truckload" principles, they have already proven that a scheduled, engineered model outperforms traditional OTR in both margin (86.2 OR vs 108.6 OR) and velocity.

Success moving forward requires rigid adherence to two rules:

Rule #1: Do Not Drift

Avoid the temptation to accept opportunistic freight that degrades network velocity, regardless of the level of external traditional truckload market rates. A line must be drawn in the sand.

Rule #2: Fund the Nodes

Accept that infrastructure is a core operating cost and fund it ahead of the curve to prevent bottlenecks.

Fleet Expansion

Current Fleet (End 2025)

trucks

Target Fleet (Sep 2026)

trucks

Annual Growth After 2026

Tractor Depreciation

Maximum Useful Life

miles

Human-Operated Tractor Costs

Initial Cost - Sleeper (Human-Operated)

Initial Cost - Day Cab (Human-Operated)

% Day Cab (Human-Operated)

Blended Cost: $180,000

Salvage Value % (Human-Operated)

Est. Salvage: $27,000

Autonomous Tractor Costs

Initial Cost (Autonomous)

Salvage Value % (Autonomous)

Est. Salvage: $45,000

Human-Operated

Useful Life: 3.9 yrs (46 mo)

Tractor Fixed/Mo: $3,326

Autonomous

Useful Life: 2.8 yrs (34 mo)

Tractor Fixed/Mo: $7,519

Utilization Rates

Human-Operated Utilization

mi/yr

Autonomous Utilization

mi/yr

Stress Test Lab

Market Rate Variance 0%

Fuel Price Shock 0%

Utilization Impact 0%

Automation Strategy

Annual Auto Adoption %

2026 15%

2027 30%

2028 40%

2029 50%

2030 60%

2031 62%

2032 64%

Economic Assumptions

FSC Recovery (% of Fuel) 86%

Linehaul RPM by Year

2026

2027

2028

2029

2030

2031

2032

Cost Escalation

Annual Inflation 3.0%

Variable (Per Mile)

Fixed (Per Truck / Month)

Variable (Per Mile)

Fixed (Per Truck / Month)

Scenarios

Scenario Name

Year 7 Revenue

$0M

Year 7 Net Margin

Target: 10%

Year 7 EBITDA

$0M

0% margin

Breakeven RPM (Y7)

$0.00

Total Cost / Mile

Fleet Size (Y7)

0 Auto

Revenue & Cost Forecast

Fleet Composition (Y7)

Detailed Pro Forma

Category	2026	2027	2028	2029	2030	2031	2032

Analyst Insight: Loading model...

Network Overview

Active Trucks

Autonomous

Human-Operated

Active Lanes

Network Miles

Launchpad

Phase

Active Lanes & Capacity

Show Prospective Network Future lanes & hubs

$0M

Revenue

Op. Ratio

$0M

Net Profit

EBITDA Margin

Auto Fleet

Timeline

Jan 2026

Fleet Count

Jan 26Jul 26Jan 27Jul 27Jan 28Jul 28Jan 29Jul 29Jan 30Jul 30Jan 31Jul 31Dec 32

Over-the-Road Division

OTR Network Analysis

Comprehensive analysis of customer concentration, lane-level profitability, protein freight advantage, and strategic positioning within the temperature-controlled freight network.

FREIGHTMATH DASHBOARD

Network Performance Analysis

Customer Concentration and Lane-Level Profitability Structure

The top four customers account for 46.4% of total Over the Road volume over the last four weeks, with a Core Operating Ratio of 97.3 versus a network average of 108.3. Performance among these customers has been consistently strong, with Operating Ratio remaining below 100 across the 18 months and falling below 93.0 in nine of the last twenty periods. This concentration reflects a material share of network economics being anchored by a small group of large, operationally stable shippers that have delivered durable profitability relative to the broader book of business.

At the lane level, this concentration is balanced across both high-density and specialized freight patterns. Approximately 32% of top four customer volume moves on 18 Power Lanes (highest density lanes), representing 15% of total network's freight and producing a 95.8 Operating Ratio. Density within a network allows a carrier to increase velocity by eliminating operational and real-world obstacles and improving efficiency. This improvement to the speed at which freight moves through the network drives network profitability.

Exhibit 1 Top Customer Network Lane Map

An additional 20% of their volume moves on Spider Lanes (lowest density lanes), which operate at a 94.0 Operating Ratio despite lower volume, largely driven by protein-related freight. Together, these patterns illustrate that customer concentration is supported not only by scale lanes, but also by defensible, specialized lane pairs that sustain pricing power. This mix enhances operational durability by combining density-driven efficiency with niche lane profitability, while also shaping the scalability profile of the network around a limited number of high-impact customers.

Exhibit 2 Top Customer Network Lane Type Table

Top 4 Customers: Walmart (multiple Bill Tos), Smithfield Foods, Tyson Foods Inc, Smucker Company.

Protein Freight Share and Profitability Across the OTR Network

From August 2024 through the current period, protein-related customers (ie; beef, pork, poultry, etc) have represented a consistent and meaningful portion of the over-the-road network, accounting for approximately 28% to 34% of total freight. At the lane level, this freight category exhibits a favorable concentration and diversification profile, combining repeatable customer participation with strong underlying economics. Core ORs for protein freight averaged around 93 over this period, never exceeding 96 as a group and reaching lows near 88. Compared to other commodity types in the network, protein lanes consistently performed 15% to 20% better on Core OR, pointing to a structurally advantaged segment rather than performance driven by a single year or isolated market conditions.

This performance has important strategic implications for network design and earnings stability. The FreightMath Operating Ratio (Network Fit) score for protein lanes outperforms the network average, largely driven by the lower operating ratios of the freight itself rather than by customer diversification effects alone. As market conditions improve and lift profitability across other commodity types, the relative network fit, and operating ratio of protein freight is positioned to improve further. This reinforces protein lanes as both a stabilizing component during softer markets and a compounding contributor as the broader freight environment strengthens, supporting sustained network-level profitability over time.

Exhibit 3 Protein vs Non-Protein Freight Volume

Exhibit 4 Operating Ratio by Freight Type

Lane-Level Customer Diversification

Over the past three months, 26% of the OTR network's volume has moved on 53 high-density lanes averaging at least one load per day. These lanes represent the most consistent and operationally important portion of the network, driving equipment utilization and day-to-day network stability.

Within this core set, customer concentration is high. Only 13 of the 53 lanes have a top customer accounting for less than 85% of total lane volume, while the remaining lanes are predominantly single-customer in nature, with 95% to 100% of freight tied to one shipper. This structure reflects strong lane incumbency but also means a relatively small number of customer decisions influences a disproportionate share of the carrier's most productive freight.

Exhibit 5 Top Lane Customer Concentration

Bubble size represents total loads. X-axis shows top customer share, Y-axis shows loads per day.

While high volume lanes are vulnerable to single customer freight, the OTR network is dense from an area perspective. In terms of volume, the top 20 markets for this network have multiple market shippers and inbound/outbound areas.

OTR Network Improvements

Kroger's Volume Increase and Lack of Network Fit

Operating under multiple Bill To Names, Kroger overall represents 5.8% of the OTR network, making it a meaningful but not dominant customer at the network level. Rates on this freight run 23% below the network average, which could position it structurally as backhaul volume. However, origin/destination performance indicates a different dynamic. The FreightMath Operating Ratio for Kroger freight is 8.1 points worse than the network average, and the Core OR of 151.1 limits any ability to recover margin either before or after these loads. While backhaul freight can play a productive role in connecting profitable areas, its effectiveness depends on manageable losses at the lane level and its ability to connect profitable areas together. In this case, the magnitude of loss embedded in the freight materially constrains network flexibility.

Since May 2025, Kroger's load volume has increased by 20%, coinciding with a significant deterioration in quality. Core OR rose from 120.4 to 151.1, while the share of loads operating at a better-than-average FreightMath OR has declined from 19.7% to 8.9%. This reflects growing concentration in underperforming lanes rather than diversified, network-supportive coverage. Although the destination markets exhibit an outbound Core OR near breakeven, the inbound losses are substantial enough to overwhelm downstream performance. At the lane level, this pattern indicates that current pricing and mix are not aligned with scalable network economics, and performance improvement would require broad-based rate adjustments across multiple lanes rather than isolated optimization.

Exhibit 6 Kroger Volume and Lanes Overview

Chicago Imbalance and Customer Diversification

Over the past four weeks, the Chicago market has been oversold by 219 loads, representing a 34 percent imbalance driven by inbound volume. Inbound freight into Chicago is structurally unprofitable, operating at a Core OR of 138.3, and typical recovery areas for deadhead capacity such as Milwaukee and Indianapolis show similarly weak economics. While outbound Chicago lanes are the heaviest in the network and perform strongly at a Core OR of 81.1, this outbound strength masks persistent inbound underperformance rather than resolving it.

Inbound customer exposure is broadly diversified, with no single shipper representing more than 11% of volume, indicating pricing pressure is distributed across a wide customer base rather than concentrated in a small number of accounts. This mix highlights a lane-level structure where diversification limits single-customer risk but also reduces pricing leverage, making margin recovery dependent on systematic rate action across shippers.

Exhibit 7 Chicago Area Overview

Florida Inbound Lane Concentration and Profit Dynamics

Inbound Florida represents 5% of the OTR's network. Because outbound Florida rates are persistently constrained by supply and demand imbalance, inbound lanes must generate above-average contribution to offset predictable downstream losses. Performance varies meaningfully by lane and customer, highlighting the importance of lane-level economics rather than aggregate market exposure when assessing durability and scalability.

The GA-ALB (Albany) to FL-SAR (Sarasota) lane for Wal-Mart represents the most immediate concentration issue. This lane consistently exceeds 10 loads per week, operates below a profitable operating ratio, and carries incremental trailer pool costs at the Thomasville, GA facility. The combination of high volume, single-customer dependence, and structural cost drag makes this lane disproportionately influential on overall Florida inbound performance. While the volume supports scale, the current economics limit its ability to subsidize weaker outbound Florida freight.

Additional inbound exposure comes from lower-volume lanes originating in the Northeast and Texas, averaging roughly six loads per week. These lanes face suppressed outbound rates that are further degraded by Florida connectivity, resulting in a 102.2 Core OR and a materially weaker 113.0 FreightMath OR that reflects poor network fit. In contrast, the CO-DEN to FL-ORL lane for Cargill operates at a strong 90.0 OR with appropriate pricing, but extended dwell times exceeding four hours at both origin and destination, combined with below-average velocity on a long haul, constrain throughput efficiency. Collectively, these patterns underscore how customer concentration, operational friction, and lane velocity, not just rate adequacy, determine whether Florida inbound freight strengthens or dilutes network economics.

Exhibit 8 Florida Inbound Freight Map

Phoenix's Red Bull Dependence

The Phoenix market is centered around the outbound freight for Red Bull/Geodis, with 78% coming from this one customer. This structure produces a weak economic profile upstream, with Phoenix-originating freight operating at a Core OR of 115.0 and inbound freight positioning trucks into Phoenix performing even worse at a 124.8 Core OR. Alternative truck supply options are limited, as sourcing equipment from Los Angeles requires more than 370 unpaid deadhead miles, reinforcing the dependence on suboptimal inbound freight to support the outbound network.

While the outbound destinations tied to this freight generate a strong 96.2 Core OR that exceeds network averages, that performance is insufficient to offset losses incurred in the prior legs. As a result, the full network-adjusted FreightMath OR for this traffic is 123.9. The data indicates that lane-level customer concentration in Phoenix constrains flexibility and magnifies the impact of weak inbound economics. Improving durability and scalability in this market would require either materially higher outbound pricing to compensate for the network drag (around $0.50 per mile), or a broader mix of profitable inbound freight to rebalance the lane economics.

Exhibit 9 Phoenix Area Overview

Conagra Foods Performance Profile

Conagra Foods' recent performance reflects limited lane-level diversification within an overall underperforming footprint, ranking second highest in FreightMath Operating Ratio among shippers with material volume. With a FreightMath OR of 118.4 and a Core OR of 120.3 over the last four weeks, the majority of Conagra's volume is concentrated on lanes operating worse than network averages. Only 3 of 18 active lanes generate better than average FreightMath OR results, representing just 11 percent of total loads, and none of these lanes are high-density Power Lanes within the OTR network. Elevated origin and destination ORs of 118.3 and 111.5 indicate that performance pressure is broad-based rather than confined to a small subset of lanes. As a result, outcomes are driven by a narrow set of consistently underperforming corridors, limiting operating leverage, reducing network optionality, and constraining the ability for incremental volume to improve overall economics.

Exhibit 10 Conagra Foods Lane Map

Broker Utilization and Lane-Level Diversification Patterns

The OTR network demonstrates disciplined use of broker freight, with broker loads and miles representing just over 7% of total activity, which is down from 19% earlier in 2025. These numbers are also well below peer benchmarks. While broker freight carries a structurally higher Core Operating Ratio than shipper freight, its FreightMath Operating Ratio is less than three points above the network average. This indicates that broker freight is being deployed selectively in ways that align with overall network economics rather than as a broad capacity substitute. At the network level, brokers appear to function as a connective mechanism that supports profitable freight flows instead of diluting margin performance.

At the lane level, this strategy is most visible in key outbound markets such as Houston and Atlanta. Both lanes exhibit higher broker concentration than the network average, yet broker freight in these markets outperforms shipper freight on a FreightMath OR basis. This suggests that broker usage in these lanes is not driven by shipper dependency or pricing pressure, but by targeted diversification that enhances optionality and resilience. By maintaining strong lane-level economics while blending customer types, the network improves its ability to scale volume, adapt to demand shifts, and preserve profitability across market cycles.

Note: Broker freight inbound to the Chicago market, mentioned in the 'OTR Network Improvements' section above, is a current problem.

Lane-Level Customer Concentration and Network Conversion Patterns

KSMTA's FreightFit asset and logistics overlay highlights a network that is already structurally aligned for selective conversion between brokered and asset-based freight. The optimized view surfaces opportunities where asset capacity and lane coverage already exist, allowing freight to be absorbed with minimal disruption, while also identifying markets where shifting freight back to logistics improves overall balance. These findings are directional rather than prescriptive, reflecting how the current network behaves under optimization rather than a one-time tactical adjustment.

Customer concentration is a defining feature of the conversion opportunity. Approximately 78 percent of the freight identified for transition to the asset network is concentrated across three large shippers: Walmart, Costco, and Kroger. A significant share of this volume is intra-California, forming a cohesive lane set with expedited characteristics. This level of concentration underscores that incremental asset utilization gains are being driven by a small number of customers with repeatable, dense freight patterns rather than a broad base of fragmented demand.

The most substantial non-intra-California opportunity is tied to Walmart Produce, which generated 213 loads across 14 outbound California lanes over the past four weeks. The asset network already operates on 13 of these 14 lanes, indicating existing operational familiarity and capacity alignment. Nearly all lanes received full model acceptance, and the freight profile is long-haul in nature, averaging 1,700 miles per load at a $3.16 linehaul plus fuel rate. From a network perspective, this reflects a scalable conversion opportunity rooted in lane overlap and consistency rather than incremental complexity.

The model also identifies targeted cases where asset freight is better suited for logistics execution. Inbound Denver stands out, with 35 percent of asset freight rejected, largely originating from Dallas, Salt Lake City, and Indianapolis. Given Denver's below-average profitability, this shift removes lower-rated freight from oversupplied markets while improving balance in the Denver region. Los Angeles shows a similar dynamic on the outbound side, where a small percentage of loads were displaced to logistics as the model prioritized higher-performing outbound freight. Together, these patterns illustrate how lane-level customer concentration and market balance influence both conversion potential and network durability.

The Future of Autonomous Trucking in the United States

A Comprehensive Analysis of Market Dynamics, Technological Deployment, and Regulatory Frameworks (2025–2035)

Executive Summary

The United States trucking industry, responsible for moving over 72% of the nation's freight by weight, stands at the precipice of a fundamental structural transformation in 2025. After a decade of speculative investment, closed-course testing, and pilot programs, the sector is aggressively transitioning into the early stages of commercialization.

Current market intelligence indicates that the global autonomous long-haul trucking market, valued at approximately $2.7 billion in 2024, is projected to reach an estimated $42.6 billion by 2034—a Compound Annual Growth Rate (CAGR) of 32%.

The convergence of SAE Level 4 (L4) autonomous driving systems—capable of operating without human intervention within specific Operational Design Domains (ODDs)—with a chronic driver shortage projected to exceed 160,000 unfilled positions by 2030, has created an irresistible economic imperative. The potential to reduce Total Cost of Ownership (TCO) by up to 40% through 24/7 asset utilization serves as the primary catalyst for this shift.

1. The Economic and Operational Imperative

1.1 The Driver Shortage and Labor Demographics

The most cited driver for automation is the persistent shortage of qualified commercial truck drivers. The American Trucking Associations (ATA) reports a widening gap between freight demand and available workforce.

Critical Labor Gap: In 2024, the shortage hovered around 80,000 drivers—expected to double to 160,000 by 2030. The median age of a truck driver is 46 (vs. 42 for general workforce), and younger generations show reluctance to enter a profession characterized by long periods away from home.

Autonomous trucking addresses this structural deficit by restructuring the job. The prevailing "Hub-to-Hub" model envisions autonomous trucks handling the long, monotonous interstate segments (the "middle mile"), while human drivers are redeployed to shorter, regional, and urban routes ("first and last mile"). This shift transforms truck driving into a job that allows for nightly returns home.

1.2 Total Cost of Ownership (TCO) and Asset Utilization

In the current human-centric model, a truck's utilization is legally capped by Hours of Service (HOS) regulations—generally limiting a driver to 11 hours of driving within a 14-hour window, followed by a mandatory 10-hour break. This means that for nearly half of every day, a capital asset worth $150,000–$200,000 sits idle.

Human-Operated

11-hour driving limit
~50% daily utilization
HOS compliance required
Driver wages: 30-40% of cost/mile

Autonomous

~24-hour operation capability
Stops only for fuel/maintenance
Optimized fuel efficiency
30-45% TCO reduction

2. Probability of Autonomy by Freight Segment

The adoption of autonomous trucking will not be a monolithic wave but rather a tiered rollout dictated by the complexity of the Operational Design Domain (ODD), economic incentives, and regulatory friction.

HIGH

Over-the-Road (OTR) & Long-Haul

Commercial Readiness: Immediate Deployment

OTR represents the "beachhead" market for AV developers. The interstate highway system offers a structured, semi-predictable environment significantly easier for AI to navigate than urban centers.

Operational Model: Hub-to-Hub Architecture

2035 Forecast: 30% of new truck sales for hub-to-hub routes

Key Corridors: I-45 (Dallas-Houston), I-10 (TX-NM-AZ)

HIGH

Dedicated Trucking

Commercial Readiness: Early Commercialization

Dedicated trucking involves moving freight on consistent, repetitive routes for a single customer. This predictability makes it ideal for early autonomy adoption.

Key Advantage: Route predictability allows "over-training" on specific corridors

Pioneer: Gatik (Walmart, Kroger middle-mile)

Fit: Drop-and-hook operations minimize complexity

LOW-MOD

Short-Haul & Drayage

Commercial Readiness: Pilot / Testing Phase

Short-haul and drayage operations present a significantly more complex ODD—dense urban traffic, frequent stops, complex intersections, and unpredictable interactions.

Barrier: Urban complexity exceeds current L4 reliability

Labor Sensitivity: Ports are strongholds for organized labor (ILWU, Teamsters)

Political Risk: California legislation (AB 316) sought to mandate human operators

MIXED

Specialized, Hazmat & Oversize

Commercial Readiness: Niche Applications

Probability is bifurcated: extremely low for public road Hazmat/Oversize due to regulatory risk, but high for private road industrial applications.

Public Road Hazmat: PHMSA rulemaking in progress; catastrophic risk profile creates massive liability barrier

Exception: Permian Basin private roads (Kodiak + Atlas Energy frac sand hauling)

Oversize: Requires human judgment and real-time coordination

3. Technology and Competitive Landscape

3.1 Major Autonomous Technology Developers

Aurora Innovation

Market Leader

Strategy: "Aurora Driver" hardware/software stack designed to be vehicle-agnostic. Driver-as-a-Service business model.

Partnerships: PACCAR (Peterbilt/Kenworth), Volvo Trucks

Milestone: 2025 expansion to Fort Worth-El Paso route (+600 miles)

Kodiak Robotics

Active Deployment

Strategy: Modular "SensorPod" technology simplifies maintenance. Dual-use applications (public roads + industrial).

Differentiator: Permian Basin frac sand hauling with Atlas Energy Solutions

Financials: Public via SPAC (2025), ~$2.5B valuation

Plus (formerly Plus.ai)

2027 Target

Strategy: Evolutionary approach—L2++ "PlusDrive" generating revenue while developing L4 "SuperDrive"

Partnership: TRATON Group (Scania, MAN, International)

Validation: Driver-out testing completed at TRC Ohio

Torc Robotics (Daimler)

2027 Target

Strategy: "Integrated OEM" model as Daimler subsidiary. Co-developing chassis with redundant systems from ground up.

Platform: Autonomous-Ready Freightliner Cascadia

Approach: "Product-grade" truck vs. retrofitted prototype

Waymo Via (Alphabet)

Paused

Status: Trucking program paused in 2023 to focus on Robotaxi (Waymo One)

Implication: Withdrawal allowed Aurora and Kodiak to consolidate market share

Note: Retains IP and capability to re-enter

Gatik

Revenue Generating

Niche: Middle-mile B2B logistics using Class 3-6 box trucks (not Class 8)

Clients: Walmart, Kroger, Tyson Foods

Model: Short fixed routes, constrained ODD (e.g., right turns only)

3.2 OEM Strategies: The Platform War

The role of the OEM has shifted from hardware supplier to platform integrator. Autonomy requires "redundancy-ready" architecture—backup systems for every critical function.

OEM	AV Partner	Strategy	Launch
Daimler (Freightliner)	Torc Robotics	Vertical Integration: "Gen 5" Autonomous Cascadia	2027
PACCAR (Peterbilt/KW)	Aurora	Partnership: Aurora Driver on Peterbilt 579, KW T680	2025
Volvo Trucks	Aurora	Partnership: "Volvo VNL Autonomous" with redundant systems	2025/26
International (Traton)	Plus	Partnership: SuperDrive integration, global scale for cost reduction	2027

4. The Regulatory Ecosystem

The regulatory landscape is characterized by a dichotomy between a supportive federal framework striving to modernize safety standards and a patchwork of state laws ranging from enthusiastic deregulation to outright bans.

4.1 Federal Regulations (NHTSA & FMCSA)

The "America Drives Act"

Aims to create a unified federal framework, preempting state-level bans on autonomous trucks provided they meet federal safety standards. Directs FMCSA to update regulations by 2027 to clearly define the legal status of autonomous systems, exempting AVs from human-specific rules (drug testing, physical exams, HOS).

FMCSA Rulemaking

Actively distinguishing between "driver-assist" and "driver-replaced" technologies. SGO 2021-01 (Standing General Order) requires crash reporting for ADS—data indicates autonomous trucks maintain remarkable safety records during testing.

Workforce Impact Studies

DOT studies suggest a nuanced shift: while long-haul driving jobs may decrease, they will be offset by increases in short-haul roles and new technical positions (remote monitoring, fleet maintenance, AV dispatching). Framed as workforce transition, not elimination.

4.2 State Regulations: The Patchwork

🟢

Texas

Gold Standard

SB 2205 explicitly allows AV deployment without human driver. Insurance, traffic law compliance, and recording devices required. Created the "Texas Triangle" launchpad.

🟡

California

Battleground

2025: DMV proposed regulations to lift heavy-duty AV testing ban with phased permitted process. Faces fierce opposition from Teamsters. AB 316 (human operator mandate) vetoed by Governor Newsom.

🟢

Arizona & New Mexico

Aligned

Regulations aligned with Texas, forming contiguous "autonomous corridor" along I-10. Enables seamless Houston-to-Phoenix operations.

🔴

Restrictive States

Labor Protectionist

States like Delaware have introduced legislation to preemptively ban driverless trucks, mirroring California's labor concerns. Creates emerging "regulatory wall."

4.3 Liability and Insurance

In a traditional accident, liability splits between driver (negligence) and carrier (vicarious liability). In an autonomous crash, liability shifts toward Product Liability—resting with the Manufacturer (Aurora, etc.) or OEM if integrated. Insurance models are evolving to underwrite based on AV stack technical maturity rather than human driving history.

5. Operationalizing the Robot: Inspections, Scales, and Prechecks

For an autonomous truck to operate commercially, it must interact with existing roadside enforcement infrastructure. A robot cannot speak to a state trooper, nor step out to check its own brakes. The industry has developed digital proxies for these physical interactions.

5.1 The CVSA Enhanced Inspection Program

This program is arguably the most critical operational enabler for the industry. The CVSA has approved a new standard specifically for Level 4/5 autonomous trucks, removing the need for roadside stops.

Point-of-Origin Inspection

Rigorous "Enhanced CMV Inspection" by CVSA-certified technician at dispatch terminal. "No-Defect" Standard—vehicle must be completely defect-free to launch.

24-Hour Validity Window

Once passed, the truck is valid for 24-hour operational window (or until trip end). "Digital validity" travels with the truck.

In-Motion Data Broadcasting

Truck wirelessly communicates inspection status to law enforcement. Valid "green light" = bypass weigh stations. Fault detected = flagged to pull over.

5.2 Level VIII Electronic Inspections

Unlike Levels I-V (physical checks), Level VIII is a wireless inspection conducted while the vehicle is moving, without direct enforcement officer interaction.

Transmitted Data Elements:

GPS Coordinates USDOT Number Operating Authority UCR Compliance ADS Status (engaged/functioning) HOS Compliance / Driverless Code

Creates a "digital license plate" and "digital logbook" read automatically at highway speeds.

5.3 Weigh Station Bypass Technologies

Technology providers like Drivewyze integrate directly into autonomous stacks. Using geofencing, the system detects weigh station approach and transmits carrier safety scores, registration, and IFTA data. Coupled with CVSA Enhanced Inspection results, compliant trucks receive bypass signals—crucial since navigating crowded weigh station ramps adds unnecessary risk and time.

6. Future Roadmap (2025–2035)

The rollout of autonomous trucking will be evolutionary, not revolutionary—beginning with specific lanes and expanding as the technological ODD widens and the regulatory patchwork unifies.

2025–2026

Commercial Launch

"Driver-out" operations on limited OTR lanes. Small fleets (dozens of trucks). Focus on safety validation and data gathering.

Regions: Texas Triangle (I-45, I-10, I-35), Arizona, New Mexico

2027–2028

Corridor Expansion

Expansion to longer routes (TX→CA, TX→GA). Introduction of scalable factory-built chassis from Daimler, Volvo, and International.

Regions: Sun Belt (I-10, I-20), Southeast (I-75)

2029–2030

Network Density

Integration into major logistics networks (FedEx, UPS). Significant volume on dedicated lanes. ~10% of new sales.

Regions: Nationwide (excluding complex winter weather)

2030–2035

Widespread Adoption

Expansion into weather-challenged regions (Snow Belt). High penetration in OTR. Mixed fleets become the norm.

Regions: Continental U.S.

Conclusion

The future of autonomous trucking in the United States is no longer a question of "if," but "how fast." The technology for highway autonomy has matured to the point of commercial viability, evidenced by 2025 commercial launches by Aurora and Kodiak, and impending 2027 entry by Daimler/Torc.

Highest Probability: Over-the-Road and Dedicated sectors, where 24/7 operation economics intersect with highway driving simplicity

Will Lag: Short-haul and Specialized freight, restricted by urban complexity and hazmat catastrophic risk profiles

Regulation is the Governor: Friction between federal preemption and state-level labor protectionism will create a fragmented map—autonomy flourishing in Sun Belt, stagnating in pro-labor jurisdictions near-term

The "Triad of Trust" for Success:

Technology Reliability Millions of driverless miles

Regulatory Robustness Inspections & liability clarity

Economic Validation TCO reduction proven by fleets

As 2025 unfolds, the industry is stepping out of the sandbox and onto the interstate, poised to redefine the movement of goods in the 21st century.

Works Cited

Autonomous Long-Haul Trucking Market Size, 2025-2034 Report. gminsights.com
Will autonomy usher in the future of truck freight transportation? - McKinsey. mckinsey.com
Mapping the Future of Autonomous Trucking | BCG. bcg.com
Autonomous Truck Corridors: Concept and Implementation Plan - Institute for Transportation. intrans.iastate.edu
Aurora: Self-driving freight is here. aurora.tech
Autonomous Trucks in 2025: A Global Snapshot - SeaRates. searates.com
Future of Autonomous Vehicles [2026-2035] - StartUs Insights. startus-insights.com
The Future of Automated Commercial Motor Vehicles - Congress.gov. congress.gov
Top 5 Autonomous Trucking Companies in the US (2025) - Fifth Level Consulting. fifthlevelconsulting.com
Autonomous Market Report & Forecast - ACT Research. actresearch.net
Challenges Facing OTR Truckers in 2025 - Bloom Services. bloomtrucks.com
California proposes to allow testing of driverless heavy-duty trucks - The Guardian. theguardian.com
PHMSA Requests Comments on Modernizing Hazardous Materials Regulations | Van Ness Feldman LLP. vnf.com
Hazardous Materials: Modernizing Regulations - Federal Register. federalregister.gov
The Future of Oversize Load Transportation - Cargobot. cargobot.io
Kodiak Driverless Trucks Revolutionize Permian Oilfield Logistics | Tank Transport. tanktransport.com
Kodiak AI Delivers First Customer-Owned Driverless RoboTrucks to Atlas. kodiak.ai
PACCAR, Aurora and FedEx Launch Autonomous Truck Commercial Pilot. paccar.com
PACCAR and Aurora Form Strategic Partnership. paccar.com
Hundreds of Driverless Trucks by 2026: What Aurora's Plan Really Means. amblogistic.us
Autonomy Leaderboard Q2 2025 Update. roadtoautonomy.com
Kodiak AI Announces Third Quarter 2025 Results. investors.kodiak.ai
Kodiak AI and Verizon Team Up for Autonomous Truck Connectivity. truckinginfo.com
Autonomous trucking developer Plus goes public via SPAC - The Robot Report. therobotreport.com
Plus completes driver-out autonomous truck testing. trucknews.com
MOVE America 2025: Commercialization of Autonomous Trucking | PlusAI. plus.ai
Waymo Business Breakdown & Founding Story | Contrary Research. research.contrary.com
Daimler Truck's Autonomous-Ready Freightliner Cascadia Hits Texas Roads. torc.ai
Autonomous Driving: Daimler Truck delivers latest autonomous-ready truck platform. daimlertruck.com
Torc Robotics achieves Driver-Out Validation Milestone. torc.ai
Torc Robotics Performs Successful Fully Autonomous Product Validation. torc.ai
Which States Allow Self-Driving Trucks on the Road Today? - Tech.co. tech.co
The Volvo VNL Autonomous – Proving the Way Forward. volvogroup.com
Congress Moves to Unify Rules for Autonomous Trucks with America Drives Act. act-news.com
Impact of Automated Vehicle Technologies on Workforce | US DOT. transportation.gov
California may be close to lifting ban on driverless trucks - Trucking Dive. truckingdive.com
Autonomous truck rules move forward at statehouses - Land Line Media. landline.media
Are Autonomous Trucks Redefining Liability in Truck Accidents? - KJT Law Group. kjtlawgroup.com
Is an AI-Driven Truck Liable After an Accident? - Bottlinger Law. bottlingerlaw.com
Products Liability and Driverless Cars - Brookings. brookings.edu
CVSA Announces New Enhanced CMV Inspection Program for Autonomous Trucks. cvsa.org
Enhanced Inspections: How CVSA is Revolutionizing Safety Standards - Road to Autonomy. roadtoautonomy.com
Enhanced Inspections: One Year In - Kodiak AI. kodiak.ai
Autonomous Trucking Conference | Enhanced Inspection Program - UGPTI. ugpti.org
All Inspection Levels - CVSA. cvsa.org
Operational Test of In-Motion CMV Inspections (Level VIII) | FMCSA. fmcsa.dot.gov
Level VIII Electronic Inspection FAQs - CVSA. cvsa.org
How the Drivewyze Weigh Station Bypass Saves Fleets Time and Money. drivewyze.com

Dedicated Transportation

Dedicated Network

A scaled, temperature-controlled dedicated fleet with proven financial performance, positioned as the foundation for Expedited service expansion.

142

Operating Areas

1,108

Lanes Analyzed

~7,000

Monthly Loads

Density Index

93.7%

Avg OR (Last 6 Mo)

95.2%

Avg OR (19 Mo)

Dedicated Network Overview

The Dedicated network operates as a contracted, asset-based transportation solution serving a defined customer base with assigned equipment and drivers. Unlike transactional freight, Dedicated volumes are planned, routes are repeatable, and capacity is committed, creating a stable operating environment with strong financial performance. Over the past 19 months, the network has delivered an average Operating Ratio of 95.2%, with recent performance improving to 93.7% over the last six months.

The network spans 142 operating areas and encompasses over 1,100 analyzed lanes, reflecting geographic reach combined with operational density. Load volumes are balanced: inbound and outbound movements align closely, reducing empty repositioning and supporting efficient asset utilization.

This combination of financial discipline, network density, and operational predictability positions the Dedicated division as a natural platform for layering additional service tiers, specifically an Expedited offering designed for customers requiring tighter transit windows and enhanced reliability.

Network Visualization

Network Characteristics That Support Expedited

Strong Overall Operating Ratio

Consistent sub-96% OR performance across 19 months of historical data demonstrates cost discipline and pricing integrity

Balanced Load Flows

Near-equal inbound and outbound volumes minimize deadhead and support round-trip efficiency

Dense Geographic Footprint

142 operating areas with a Density Index of 58 indicates concentrated activity supporting reliable coverage

Structured Lane Hierarchy

13 Power Lanes, 154 Repeat Lanes, and 994 Spider Lanes provide a foundation of high-frequency corridors

Predictable, Repeatable Operations

Contracted volumes and consistent schedules reduce variability and improve execution reliability

Temperature-Controlled Expertise

Existing cold-chain capabilities align with Expedited requirements for time-sensitive, high-value freight

Expedited as a Natural Upsell

The Expedited network should be positioned as a service tier layered onto the existing Dedicated network, not as a standalone offering. The commercial message should lead with reliability, control, and risk reduction rather than speed alone. Because the underlying network is dense and balanced, Expedited volumes can be accommodated with limited incremental complexity, allowing pricing to reflect service certainty and performance.

For existing Dedicated customers, Expedited represents a natural upgrade path, offering tighter transit commitments on lanes they already ship without requiring new carrier relationships or operational onboarding. For prospects, leading with the stability of the Dedicated platform before introducing Expedited establishes credibility and differentiates the offering from commodity time-definite services.

Expedited Value Drivers

Service Certainty: Defined transit windows backed by network density and operational discipline
Risk Reduction: Contracted capacity eliminates spot market exposure during peak demand
Operational Continuity: Same equipment, same drivers, same processes, with enhanced commitments
Simplified Procurement: Single carrier relationship spanning standard and expedited needs
Performance Accountability: Clear SLAs with visibility into execution metrics

Lane Structure Summary

Power Lanes

Highest volume corridors driving core network economics

154

Repeat Lanes

Consistent volume lanes supporting predictable operations

994

Spider Lanes

Network reach extending coverage across operating areas

Customer Concentration and Lane-Level Profitability Structure

The top four customers account for 46.4% of total Over the Road volume over the last four weeks, with a Core Operating Ratio of 97.3 versus a network average of 108.3. Performance across these customers has been consistently strong, with Operating Ratio remaining below 100 across the observed period and falling below 93.0 in nine of the last twenty periods. This concentration reflects a material share of network economics being anchored by a small group of large, operationally stable shippers that have delivered durable profitability relative to the broader book of business.

At the lane level, this concentration is balanced across both high-density and specialized freight patterns:

Power Lanes (18 lanes): Approximately 32% of top-four customer volume moves on these highest density lanes, representing 15% of total network freight and producing a 95.8 Operating Ratio.
Spider Lanes: An additional 20% of their volume moves on Spider Lanes (lowest density lanes), which operate at a 94.0 Operating Ratio despite lower volume, largely driven by protein-related freight.

Together, these patterns illustrate that customer concentration is supported not only by scale lanes, but also by defensible, specialized lane pairs that sustain pricing power. This mix enhances operational durability by combining density-driven efficiency with niche lane profitability, while also shaping the scalability profile of the network around a limited number of high-impact customers.

Protein Freight Share and Profitability Across the OTR Network

From August 2024 through the current period, protein-related customers across beef, pork, and poultry have represented a consistent and meaningful portion of the over-the-road network, accounting for approximately 28% to 34% of total freight. At the lane level, this freight category exhibits a favorable concentration and diversification profile, combining repeatable customer participation with strong underlying economics.

Operating ratios for protein freight averaged around 93 over this period, never exceeding 96 as a group and reaching lows near 88. Compared to other commodity types in the network, protein lanes consistently performed 15% to 20% better on operating ratio, pointing to a structurally advantaged segment rather than performance driven by a single year or isolated market conditions.

Strategic Implications

As market conditions improve and lift profitability across other commodity types, the relative network fit and operating ratio of protein freight is positioned to improve further. This reinforces protein lanes as both a stabilizing component during softer markets and a compounding contributor as the broader freight environment strengthens, supporting sustained network-level profitability over time.

Lane-Level Customer Diversification

Within this core set, customer concentration is high:

Only 13 of the 53 lanes have a top customer accounting for less than 85% of total lane volume
The remaining lanes are predominantly single-customer in nature, with 95% to 100% of freight tied to one shipper

This structure reflects strong lane incumbency but also means a relatively small number of customer decisions influences a disproportionate share of the carrier's most productive freight.

Key Takeaways

Customer Concentration: Top 4 customers = 46.4% of volume with 97.3 OR (11 points better than network average)
Protein Advantage: 28-34% of network volume with ~93 OR, 15-20% better than other commodities
Lane Incumbency: Strong positioning on 53 high-density lanes, but 40 are single-customer dependent
Diversification Opportunity: Only 13 lanes have meaningful customer diversification

Asset/Logistics Overlay Analysis

The Asset/Logistics Overlay reveals selective opportunities to convert brokered freight to asset-based capacity, improving network economics without requiring unrealistic deadhead reduction targets.

Key Observations

Protein Freight: It is not feasible to broker the protein freight due to service requirements and specialized handling.
Intra-CA Opportunity: A meaningful portion of the freight is intra-California and is potentially an Expedited target lane set.
Walmart Produce: The largest non-intra-CA opportunity appears to be Walmart Produce, which places 213 primarily outbound CA–LOS loads from Logistics to Assets.
Deadhead Reality: Moving from 172 to 75 deadhead is clearly not realistic. Focus on selective, high-impact segments.

CORE vs FM OR Analysis

The relationship between CORE and FM OR is a persistent challenge for protein-centric carriers due to the remote nature of kill plants and distributed consignees.

IL–CHI Opportunity

The IL–CHI lane represents a significant opportunity:

219 loads, or 34%, oversold
18% broker inbound
Material inbound and outbound deadhead exposure
Real Good Foods relates here, as it is entirely IL–CHI outbound

Project Celsius

Monthly Fleet Deployment Schedule

Full Executive Summary

Celsius Expedited Network

Executive Summary

SWOT Analysis: Celsius Expedited Network

Strengths (Internal)

Weaknesses (Internal)

Opportunities (External)

Threats (External)

Expedited Network Overview

The "Precision Standards" (Intentionality)

Leadership & Governance

Engineered Seasonality

The Incubation Process (Risk Mitigation)

Current Footprint & Infrastructure

Active Lanes & Capacity

Node Readiness & Expansion

Financial Implication: The "Infrastructure Burden"

Operating & Commercial Requirements

Operations: Execute the Schedule

Commercial: Contract for Behavior

Autonomous Trucking: The Force Multiplier

1. Operational Mechanics: The "Continuous Chain"

2. Financial Impact: Shifting the Cost Structure

3. Network Stability & Service Perfection

4. The "Hybrid Deployment" Strategy

5. Strategic Synergy: Why Celsius Wins with AV

Strategic Conclusion

Full Business Overview

Overview

Business Model

Over-the-Road (OTR) Refrigerated Transportation

Dedicated Transportation Solutions

Logistics & Brokerage Solutions

Customers and Revenue Profile

Market Opportunity

Competitive Advantages

Growth Strategy

1. Organic Growth

2. Strategic M&A and Industry Consolidation

3. Operational and Technology-Driven Margin Expansion

Financial Profile (Base Case)

Recapitalization and Investor Returns

Risk Profile and Mitigation

Investment Thesis

Full Research Report

The Future of Autonomous Trucking in the United States

A Comprehensive Analysis of Market Dynamics, Technological Deployment, and Regulatory Frameworks (2025–2035)

Executive Summary

1. The Economic and Operational Imperative

1.1 The Driver Shortage and Labor Demographics

1.2 Total Cost of Ownership (TCO) and Asset Utilization

2. Probability of Autonomy by Freight Segment

2.1 Over-the-Road (OTR) and Long-Haul

2.2 Dedicated Trucking

2.3 Short-Haul and Drayage

2.4 Specialized, Hazardous, and Oversize Loads

3. Technology and Competitive Landscape

Major Autonomous Technology Developers

OEM Platform Strategies

4. The Regulatory Ecosystem

4.1 Federal Regulations (NHTSA & FMCSA)

4.2 State Regulations: The Patchwork

4.3 Liability and Insurance

5. Operationalizing the Robot: Inspections and Prechecks

5.1 The CVSA Enhanced Inspection Program

5.2 Level VIII Electronic Inspections

5.3 Weigh Station Bypass Technologies

6. Future Roadmap (2025–2035)

Phase 1: Commercial Launch (2025–2026)

Phase 2: Corridor Expansion (2027–2028)

Phase 3: Network Density (2029–2030)

Phase 4: Widespread Adoption (2030–2035)

Conclusion

Works Cited

The Platform

Platform At-a-Glance

Three Complementary Divisions

Over-the-Road (OTR) Refrigerated