Deadhead miles have long been treated as a trucking efficiency problem. Optimal Dynamics argues they should also be treated as one of the industry’s most actionable emissions reduction opportunities.
Jake Dettmer, SVP of Product at Optimal Dynamics, said empty miles are often viewed through the lens of utilization, fuel cost, driver hours, and asset productivity. But every mile a truck runs without freight also burns fuel and creates emissions without moving a shipment.
“Deadhead miles are often treated as a utilization problem when they are really a waste problem,” Dettmer said. “Every empty mile consumes fuel, emits carbon, uses driver hours, and creates equipment wear without moving freight or creating customer value.”
That distinction matters for fleets navigating a market where federal emissions policy may shift, but shipper expectations, operating costs, and carbon reporting requirements continue to influence transportation decisions. For carriers not ready to invest in new trucks, alternative fuels, or charging infrastructure, Optimal Dynamics sees a near-term opportunity in the planning and dispatch decisions fleets are already making every day.
Empty Miles as Operational and Carbon Waste
According to Dettmer, the industry’s long-standing focus on utilization can obscure the actual problem. A truck can be moving and still be creating waste if it is moving empty or being positioned in a way that limits future freight options.
“The reason it persists is that most fleets measure utilization instead of liquidity,” Dettmer said. “Utilization asks whether a truck is moving. Liquidity asks whether the network successfully converted a truck hour into productive work.”
Dettmer pointed to ATRI’s 2025 data, which put deadhead at 16.7% of all miles. At fleet scale, he said, the numbers can become significant. A 500-truck fleet running 100,000 miles per truck annually would cover 50 million miles. At a 16.7% empty-mile rate, approximately 8.35 million miles would produce emissions without moving freight.
“The opportunity is not simply reducing empty miles,” Dettmer said. “The opportunity is eliminating waste before those miles ever occur. The cleanest mile remains the mile the network never needed to run.”
Using the Environmental Defense Fund benchmark of 161.8 grams of CO2 per ton-mile, even small reductions in empty miles can add up across a large network. More importantly, those reductions can come from better operational decisions rather than major capital investments.
“The strategic opportunity for fleets is that those gains are available immediately,” he said. “Better load acceptance, driver assignment, and positioning decisions convert directly into avoided fuel burn and avoided emissions using the assets already in the yard.”
Why Dispatch Decisions Matter to Sustainability
A whitepaper produced by Optimal Dynamics argues that trucking AI should not be limited to predicting demand, pricing, ETAs, or service risk. According to Dettmer, the larger challenge is helping fleets make better sequential decisions, where every load accepted, rejected, or assigned affects the next set of options.
“A load that appears profitable today may strand a driver in a weak market tomorrow,” Dettmer said. “A decision that improves utilization in the moment may create empty miles and waste later.”
That is where the company’s concept of liquidity becomes central. Rather than focusing only on whether a truck is being used, liquidity evaluates whether the network is creating better future options, stronger revenue quality, and fewer recovery moves that lead to waste.
For dispatchers, that can mean recommendations that account for downstream consequences instead of only the next available load. For planners, it can mean evaluating thousands of load and driver combinations across the network. For executives, it connects profitability, service, driver experience, and sustainability.
“Our framing is simple: optimization decides, agents act,” Dettmer said. “The value is not automating isolated tasks. The value is making better network-aware decisions that reduce waste before it happens.”
Fleet Examples Show the Operational Impact
Fleets across Optimal Dynamics’ customer base have reduced empty miles by more than 20% through improved planning and dispatch decisions alone, without changing equipment, fuel type, or infrastructure.
The company’s fleet examples show how those improvements can play out differently depending on the carrier’s network and operational goals.
At Standard Logistics, the company needed a more scalable way to plan as its customer network, service offerings, and geographic footprint expanded. The fleet sought a system that could assess thousands of dynamic scenarios, prioritize the right freight, reduce empty miles, and improve network-wide efficiency without compromising service or profitability.
“No human can possibly see these opportunities or make all these decisions network-wide,” said Eric Hernandez, Manager of Fleet Optimization & Customer Service at Standard Logistics. “With the level of automation provided by Optimal Dynamics, now we can.”
At Grand Island Express, automation changed the daily role of dispatchers and planners. Roughly 80% of the team was reallocated to higher-value work as automation took over routine dispatching.
“Through automation, we can handle more volume with the same staff and focus on decisions that truly make us invaluable to our customers and drivers,” said Deen Albert, VP of Operations at Grand Island Express.
The company also reported measurable gains, with revenue per truck per week rising 17.3% and empty miles falling 20%.
Ploger Transportation saw load volume increase 21.4% and revenue per mile rise 14.6%. According to the company, the system helped planners make better decisions faster, especially when the AI-driven recommendation differed from a dispatcher’s first instinct.
“Manually dispatching and planning loads daily was a grind,” said Zach Cellar, Operations Manager at Ploger Transportation. “Optimal Dynamics helps us make better decisions faster, the difference has been night and day.”
Leonard’s Express used the technology to focus on revenue quality, not just volume. The company reported a 45% reduction in brokerage-booked loads, which it said improved asset utilization and the quality of revenue in its network.
“With smarter and more disciplined load planning, we had a 45% reduction in brokerage-booked loads, improving asset utilization and the quality of revenue in our network,” said Kyle Johnson, CEO of Leonard’s Express.
For Dettmer, these examples show why emissions reductions from deadhead reduction can be durable. The same decisions that reduce empty miles can also improve revenue per truck, reduce fuel burn, support more consistent driver schedules, and help fleets avoid unnecessary recovery moves.
“Reducing empty miles is not a trade-off against those goals,” Dettmer said. “It advances them.”
Sustainability Moves Closer to Operations
Federal emissions rules may change, but according to Dettmer, the business case for cutting empty miles does not depend on regulation. Empty miles still cost money, consume fuel, and reduce network efficiency regardless of the policy environment.
“We see that the business case for cutting empty miles does not depend on the regulatory environment,” Dettmer said. “Whatever happens at the federal level, an empty mile still costs fuel and money, and removing it still helps the bottom line.”
That places sustainability more directly inside operations. When a fleet reduces emissions by improving dispatch, load acceptance, and driver assignment, the effort can be tied to business performance rather than only compliance.
That shift also matters because many fleets still face sustainability expectations from customers. Shippers with Scope 3 emissions commitments continue to look for carriers that can provide measurable progress through frameworks such as SmartWay, SBTi, and GLEC.
“Federal rules can change, but a shipper’s carbon target tends not to,” Dettmer said. “For carriers, that means the demand signal increasingly comes from customers, not regulators.”
Avoided empty miles are measurable and defensible, which can help carriers demonstrate efficiency gains to customers.
“A carrier that can show a shipper concrete network-efficiency gains has a real story for SmartWay or GLEC reporting,” Dettmer said. “Increasingly that capability becomes a competitive differentiator in winning freight, not just a cost of compliance.”
Where Fleets Should Start
Before pursuing more advanced AI initiatives, carriers should first examine their empty-mile percentage, where those miles are concentrated, and whether their operational data is clean enough to support better decisions.
“Most fleets are surprised by how much avoidable empty mileage is hiding in their network and how much of it traces back to decisions made without full network visibility,” Dettmer said.
For fleets evaluating their next step, the starting point should be network visibility and decision quality. That includes understanding where deadhead occurs, why it occurs, and how load selection, driver assignment, and positioning decisions affect future options.
“Get visibility into your network and your data first, fix the decision quality that drives empty miles, and capture the efficiency that is already sitting in your existing operation,” Dettmer said. “That foundation is what makes any further AI investment actually pay off.”
