Every transport company knows the feeling: your truck just delivered a load in Munich. Now it drives 600 km back to base — empty. No revenue. Full cost. In European road freight, this happens on 20-24% of all truck trips.
What are empty kilometers?
Empty kilometers are kilometers driven without cargo. Also called "empty miles," "lege kilometers," or "Leerkilometer" (German), they represent the most visible form of transport inefficiency.
The definition includes fully empty trips — where a truck drives from a dropoff point back to base or to find the next load. But it also includes partially loaded kilometers, where a truck isn't using its full capacity, though these are harder to quantify.
How big is the problem?
The scale is staggering.
20-24% of all European truck kilometers are empty (Eurostat, 2024). For a fleet of 50 trucks averaging 200 km per day, that's 2,000-2,400 empty km daily. At €1.20 per km in variable costs (fuel, wear, maintenance), that's €2,400-€2,880 per day in wasted spend — or €600,000-€720,000 annually.
For a carrier with 200 trucks, the annual cost balloons to €2.4-€2.88 million. For a 1,000-truck fleet, it's €12-€14.4 million per year running on empty.
What causes empty kilometers?
One-way freight contracts. A customer books a load from Berlin to Rotterdam. You deliver it. The customer doesn't need you for the return trip, so you drive back empty. This is the dominant cause in fragmented markets.
Lack of network visibility. Your planner doesn't know if there's a load from Rotterdam back to Berlin. The information exists somewhere — in a broker's system, a customer's TMS, your own historical data — but your planner can't see it in time to match the opportunity.
Geographic imbalance. Some regions are net-importers (more inbound loads than outbound). Others are net-exporters. Your fleet's geography may not align with those flows, forcing empty deadheading.
Time pressure. Sometimes it's faster and less risky to drive back empty than to wait for the next load. A truck that sits for 6 hours waiting for a load isn't earning revenue either — and the driver's still on the clock.
Fragmented data. Your planners can't see the full picture. Past quotes, declined loads, competitor intelligence, customer patterns — all of this is data that could predict the next opportunity. But if it's scattered across email, spreadsheets, and TMS records, it's effectively invisible.
How to reduce empty kilometers
Visualize your route network. Before you can fix the imbalance, you need to see it. Plot all your historical routes on a map. Which corridors run full? Which ones run empty? Which geographic regions are you loading vs. unloading? This pattern alone reveals opportunities.
Use historical data to predict future needs. Your past quotes and trips contain return load opportunities. If you quote 10 loads from Berlin to Rotterdam, how many reverse loads do you actually see? The answer is in your data.
Match follow-up loads in real-time. When a truck is due to unload in Rotterdam, run a proximity search against your open requests. Is there a load departing Rotterdam in the next 2-6 hours? This turns empty deadheading into a proactive optimization.
Share capacity with other carriers. You can't match every load yourself. But you can collaborate with complementary carriers. A carrier strong in Germany + France with weak UK coverage can partner with one strong in UK logistics to fill gaps on both sides.
Analyze quote history for signals. Which corridors do you quote but never execute? That gap often signals a market opportunity (a competitor is cheaper) or an operational blind spot (you don't have the right equipment or partner).
How FleetWish helps
FleetWish turns your TMS data and spreadsheets into a visual route network. Upload your routes — past and planned. See the heatmap of where trucks are loading versus unloading. Identify regional imbalances immediately. Then find follow-up loads with one click: "Show me available loads departing within 50 km of my next unload point."
Setup takes under 5 minutes. No IT projects. No waiting. Just data, mapped, ready to act on.