The Study: 10,000 Truck Routes vs. Google Maps — How Much Longer a 40-Tonner Really Drives
How far do real truck routes deviate from the Google Maps car route — in kilometers and in driving time? We measured it on 10,000 randomly sampled tours: by short haul, regional and long haul, with methodology, charts and real example tours. For the short version and the alternative, see the guide Google Maps for Trucks.
Methodology: how we measured
We took 10,000 real tours. Two calculations each: the legal 40-tonne route with IMPARGO — and the car route from Google Maps. Same origin, same destination.
Three things were chosen deliberately. Both routes without traffic — the comparison isolates the structural difference in routing and speed, not the conditions of the day; with live traffic, the gaps would tend to be larger. One 40-tonne profile — the heaviest standard case; lighter vehicles deviate less. Only tours of 5 km and up — micro-routes produce outsized percentages and would distort the statistics, in both directions.
The most important result first:
Averaged across all tours: driving time +21.6%. Kilometers +3.1%. So the time is wrong everywhere. The kilometers only in certain places — more on that in a moment.
At a glance — what applies to your tours?
Takeaway: The error has a direction — more than 95 out of 100 tours really do take longer.
The details come in two parts: kilometers first, then hours.
The big picture: two very different errors
Before we go into detail, one look at all 10,000 tours at once. The two distributions below show: distance and time go wrong in completely different ways.
Left: distance deviation truck vs. Google, share of tours per class. Right: the same for driving time. Basis: 10,000 tours (5 km and up).
On the left, the distance: a narrow peak — with a dangerous right tail. A good 8 in 10 tours sit within ±5%. So the kilometers are usually fine. But the right tail packs a punch: 8% of all tours are 10% or more longer, some by over 50%. That is not an averages problem. That is an outlier problem — and outliers strike without warning.
On the right, the time: the whole peak stands on the wrong side. Barely 3 in 100 tours are faster by truck. Almost 8 in 10 tours need 10 to 30% longer. One in ten needs more than 30%. There are no outliers here — here, the deviation is the normal case.
Takeaway: The distance usually goes fine and sometimes goes badly wrong. The time goes wrong practically always — just to different degrees.
That is exactly why we treat them separately: kilometers first, then hours.
Part 1: The kilometers
Your freight price sits on a price per kilometer. If the kilometers are wrong, the price is wrong. Here is how it looks — from short to long:
Short haul (up to 150 km): this is where the kilometers lie. On average +6.9%. But careful: that average is made of outliers. Most tours are fine. And then comes the one that isn't:
- 1 in 7 routes is at least 10% longer than on Google.
- Under 50 km, 1 in 10 routes is at least 22% longer. The reason is always the same: a bridge, a weight limit, a truck ban.
A real tour from the test (Rhine crossing, south-west Germany): Google says 15.9 km, 20 minutes. The truck needs 41.7 km, 40 minutes. Why? The river crossing is closed to 40 tonnes. Google doesn't know that. Whoever quoted this tour at 15.9 km paid the difference.
The same pattern applied to another relation from the dataset:
Regional (150–500 km): mostly fine — with landmines. On average +0.7%. Sounds harmless. But 1 in 19 routes hides a detour of 10% or more — without warning. And regional is the daily bread: run 40 of these tours a month and you catch two of them every month. A 10% detour on 300 km means roughly 30 unpaid kilometers plus half an hour of driver time. At a 2% margin, that quickly eats a full day's profit. One outlier, one day's profit gone.
Long haul (over 500 km): the kilometers are fine. On average +0.1%. A motorway is a motorway.
Still, long haul is not off the hook. The problem just sits elsewhere. Your per-kilometer price has to carry two kinds of cost:
- Time: driver, truck and trailer cost money by the hour, rolling or standing.
- Distance: diesel, tyres, wear per kilometer (this is how transport cost accounting works).
Your experience-based rate per segment has a time assumption priced in, plus buffer, empty kilometers, loading times. On long haul the distance is right. The risk sits in the time, but differently than you'd think: your rate is not wrong.
The question is how much the individual tour scatters around your rate, and whether over-recovery and under-recovery really balance out.
One curve, two truths: the distance error (black) is high on short tours and disappears on long ones. The time error (yellow) always stays at +15 to +25%. Interactive hover version: see embedded chart.
Takeaway: The shorter the tour, the more dangerous the kilometers. The longer the tour, the more the error moves into the time.
Part 2: The hours
Your promise to the customer is a time of day. Here is what the clock really does:
Ten minutes sounds harmless. Until it's ten minutes at every stop. Forty minutes on nearly every regional leg — no call, no alarm, just gone. And on long haul, it becomes a legal matter:
A real tour from the test (Lower Bavaria → Bremen area): Google says 769 km in 7 h 49 min, which looks completely uncritical within the 9-hour driving day, more than an hour of air. The truck really needs 9 h 51 min. Almost the same kilometers, but 2 hours more.
That puts the tour clearly above the regular daily driving limit of 9 hours. It is legally drivable only on one of the two 10-hour days allowed per week, and then with 9 minutes to spare.
One roadwork, one jam, one busy dock, and the tour tips into a violation or an unplanned overnight stop. The 4 p.m. delivery slot turns into demurrage.
Whoever plans with the paper time burns extension days and buffer without noticing — and systematically underestimates the driving-time risk.
Takeaway: The longer the tour, the more wrong the clock.
The rule of thumb: "X hours of driving time per 100 km"
This is how most people plan — in exactly this order:
- Pull the kilometers first. Enter the route in Google Maps, read off the kilometers. Say: 400 km.
- Then apply the factor. Kilometers divided by 100, times X hours of driving time: 400 ÷ 100 × 1 h 15 min = 5 hours of driving time.
- The price comes from the kilometers: km × your experience-based rate per segment. The driving time becomes your promise: arrival time to the customer, feasibility of the shift.
In plain terms: the dispatcher takes the kilometers from Google and multiplies them by an X. And where does the X come from? From experience. No measurement, no system value, felt hours per 100 kilometers, worn in over years. The result is gut feeling.
That is not meant as a put-down: this gut feeling is often astonishingly good. But it has two open flanks. The kilometers come from Google (what that can do to your price was Part 1), and the X sits unchecked in your promise and, as a time assumption, in your rate. We measured what the real X looks like:
Why one fixed X is not enough, in three sentences: Short haul needs a different X than long haul — one for all cannot work. Even the correct X (1:18 on long haul) is too tight on every third tour, because an average is not a route. And whoever takes 1:25 to be safe overplans the majority — wasted capacity.
One more effect on top: Google's pace (roughly 1 hour per 100 km) sits on your screen every day. It slowly pulls every gut feeling toward "too fast".
Takeaway: Even the correct X is too tight on every 3rd long-haul tour — an average is not a route.
Over-recovery and under-recovery: the real risk
Time for the model behind it all. This is how your price comes about: kilometers times an experience-based rate. One rate per segment — short haul, regional, long haul — and each has empty kilometers, loading and unloading times, a time assumption and a buffer baked in. No dispatcher prices with Google hours. Your price therefore hangs on two estimates: the kilometers of the tour, and the time it really takes.
And every single tour deviates from those estimates. Sometimes downward — the tour was shorter or faster than calculated, the price covered more than needed: over-recovery. Sometimes upward — longer or slower, the price didn't stretch: under-recovery. That is not a flaw in the system. That is the system: a fixed rate lives on the two balancing out across many tours.
The scatter has two sources — and we measured both:
Source 1: the kilometers. The real truck route is not the planned route — one closed bridge, one weight limit, one truck ban, and 20 km become 40. Because the price is kilometer-based, this error goes into your recovery one to one: every unrecognized extra kilometer is driven but not paid. This source hits short tours above all (Part 1: 1 in 10 routes under 50 km, 1 in 19 regional).
Source 2: the time. Same kilometers, different speed: road type, gradients, towns, borders, docks. The real driving time scatters around any time assumption — and with it, the time costs of the tour. This source hits long tours above all (Part 2: even the perfect rate is broken by every 3rd long-haul tour).
Why doesn't it simply balance out? Three reasons:
- The scatter is skewed. There is little room on the downside — you can't go much faster than the ideal line, or much shorter than the shortest legal route. The upside is open: diversions, closures and jams know no limit. Outliers are almost always extensions, practically never shortcuts. The distributions at the top of this study show exactly that picture.
- The follow-up costs are one-sided. A tour in under-recovery drags real money behind it: demurrage, a lost delivery slot, a broken driving-time limit. A tour in over-recovery generates barely any value — saved time is hard to sell; unless a follow-up tour can be pulled forward, and that is not the normal case. Even if the minutes balanced out: the euros don't.
- The average itself drifts. An experience-based rate is the average of the past. You built the average last year — this year brings a different roadworks situation, different traffic, new lanes, a different customer mix. The rate is off before the first tour is driven. Over- and under-recovery now scatter not around the right mean, but around a wrong one — and scatter turns into drift.
From that follows the goal, and it is reachable: the risk is exactly as big as the error in the two inputs. The closer your planned kilometers are to the real truck kilometers, and your planned time to the real truck driving time, the narrower the band of over- and under-recovery, and the smaller the buffer you have to hold and pay for.
The scatter never drops to zero; traffic and the dock remain. But the systematic part, the one that comes from wrong kilometers and a wrong time assumption, can be eliminated. That is precisely the part we measured in this study.
And one item is still missing here entirely: the toll. We deliberately left it out of all calculations, yet it moves in magnitudes that dominate everything above: a 40-tonner pays roughly 35 cents of toll per kilometer in Germany, depending on emission class.
At a 1-3% margin, only a fraction of that remains per kilometer as profit, so the toll is a multiple of your margin, and it depends on route and vehicle class. Without the toll per route, any €/km view is waste paper, no matter how good the experience-based rate is.
Takeaway: Over-recovery and under-recovery are not fate — they are exactly as big as the error in your two inputs: kilometers and time.
What that does to your margin
In transport, 1 to 3% profit is left at the end — up to 5% in good exceptional cases. The costs per tour are fixed: driver, diesel, vehicle, toll. Every percent missing from the price is therefore missing from the profit at the end.
An example with round numbers, step by step:
- You sell a tour for €1,000. Your costs: €980. That leaves €20 profit — the 2% margin.
- Now the price is just 0.5% too low — you quoted €995 instead of €1,000. The costs stay at €980. €15 profit remain instead of €20. A quarter is gone.
- If the price is 1% too low (€990), €10 remain — half is gone.
The reason: the costs always ride along. Every euro missing from the price is therefore missing from the profit in full — not proportionally.
Now plug in the numbers from this study, and watch how quickly half percents come about:
- The unrecognized 22% detour on local runs takes 22% of the freight price. At a 2% margin, eleven times the tour's profit.
- The regional outlier (Part 1): the extra costs eat the day's profit.
- The long-haul tour that breaks the experience-based rate (every 3rd) quickly eats a tour's profit in extra time alone.
- And if the delivery slot bursts on top: easily €150-300 in total damage, demurrage (Section 412 of the German Commercial Code, HGB) plus follow-up costs such as postponed connecting tours and burned driving time. The profit of five to ten tours.
That is the common thread of this study: none of these amounts is big. But at a 1–3% margin, none of them is small.
Takeaway: At a 2% margin, half a percent decides over a quarter of the profit.
Conclusion: seven sentences that sum up 10,000 tours
10,000 tours, two numbers per tour, one pattern. If you take away only the key sentences, you have understood the study:
This is the most important sentence of the study. An error that swings both ways would be a nuisance. An error that almost always points the same way is a system — and it works against you.
Two completely different error types: the kilometers are an outlier problem (8 in 10 tours fit, then comes the one with the closed bridge). The time is the normal case — almost 8 in 10 tours need 10 to 30% longer.
On local runs under 50 km, 1 in 10 routes is at least 22% longer — and because the price is kilometers times rate, those 22% are missing from the freight price one to one. The Rhine-crossing tour from the dataset: price collected for 15.9 km, costs paid for 41.7 km.
On long haul, an average of 2 h 15 min per tour is missing. The example tour Lower Bavaria–Bremen looks comfortably feasible on paper (Google: 7 h 49 min) — in reality it takes 9 h 51 min: above the regular 9-hour daily driving time, legal only on one of the two 10-hour days allowed per week, with 9 minutes to spare. Whoever doesn't know the gap plans exactly these tours — and finds out at the dock.
One X for all traffic types cannot work anyway: short haul needs a different factor and scatters by half per route. And whoever buffers generously to be safe overplans the majority of tours — wasted capacity. The dilemma cannot be solved with a fixed X.
There is little room on the downside; on the upside the scatter is open — outliers are almost always extensions. Follow-up costs like demurrage and lost slots hit only the under-recovery. And because roadworks, traffic and lanes shift every year, the experience-based rate eventually scatters around a wrong mean. The balancing act the fixed rate lives on never happens.
And half percents come about quietly: an unpaid detour here, an hour of under-recovery there, a toll surprise on top. None of these amounts is big. But at a 1–3% margin, none of them is small.
What follows from this? The experience-based price is good on average, but it is a bet that the individual tours will balance out. Our data shows: they don't. It only becomes reliable per route: real truck kilometers for the price, real truck driving time for the promise.
Professional truck route planners can do both today, and two things more, where every flat rate fails: they map driving and rest times directly into route and arrival time, so the promise is also a legal shift. And they calculate the toll per route and vehicle class into the costs, the item without which any €/km view remains waste paper.
What that looks like in practice is summed up in the guide: Google Maps for Trucks: the alternative.
Frequently asked questions about the study
How were the 10,000 routes sampled?
We started with all routes calculated by IMPARGO customers on a regular weekday. To ensure a consistent and comparable dataset, we included only simple point-to-point routes with one origin and one destination. Multi-stop routes, routes with intermediate waypoints, and other more complex route configurations were excluded.
From the remaining eligible routes, we selected 10,000 routes at random. The underlying customer base is European, with routes covering countries across Europe and a comparatively stronger representation of the DACH region: Germany, Austria, and Switzerland.
How many routes really take longer by truck than on Google Maps?
More than 95 out of 100 — 9 in 10 on short haul, nearly all on regional and long haul (99.8% and 99.9%). Basis: 10,000 compared tours.
How many hours does a truck need per 100 km?
Roughly 1 h 17 min on long haul, roughly 1 h 34 min on short haul — varying strongly per route, up to over 2 hours. Google calculates with roughly 1 hour.
How much longer is a truck route than the car route?
In kilometers, +3.1% on average (short haul +6.9%, long haul +0.1%). In driving time, +21.6% on average.
Why was the comparison run without traffic?
To compare the routing logic structurally. With live traffic, the results would be more volatile, but not better for the car route. A follow-up study with traffic is planned.
Why isn't a fixed €/km rate enough to cover costs?
The experience-based rate is good on average — but it lives on over-recovery and under-recovery balancing out. That balance never happens: the scatter is open on the upside and limited on the downside, the follow-up costs (demurrage, lost slot, driving time) hit only the under-recovery, and yesterday's average no longer fits today's roadworks and traffic. On top comes the kilometer risk: an unrecognized detour is missing from the price one to one.
Isn't planning with a fixed rule of thumb enough?
No. Even the correct average (1:18 on long haul) is too tight on every third route. It only becomes reliable with truck routing per route.
Methodology: 10,000 randomly sampled 40-tonne tours (IMPARGO, fastest route, no traffic; segment statistics on routes of 5 km and up), each compared with the Google car route for identical origin/destination pairs; 9,999 valid. Short haul < 150 km, regional 150–500 km, long haul > 500 km. Distance costs excluding toll; km share floored at zero per segment. Example tours are real routes from the dataset. Over-/under-recovery: deviation of the real tour from the calculation assumption (kilometers and time), downward or upward.
