Berlin
Amsterdam
Dublin
The cost of standing still How Europe’s capitals move goods — and what it costs when they don’t European Urban Freight Efficiency Index
London
Paris
Rome
Madrid
Powered by Geotab Connected Vehicle Data | Full-Year 2025
Executive Summary
Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
Contents
Executive summary
City snapshots
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12
About this report The European Urban Freight Efficiency Index analyses how efficiently commercial vehicles move through seven major European capitals. Using full-year 2025 data from Geotab’s connected vehicle platform, we benchmark each city across two dimensions — how well traffic flows and the operational waste that congestion creates — to deliver a data-driven efficiency score for each capital. All scores are based on normalised comparisons, not absolute counts.
Foreword
What this means for you
04
19
Introduction: the rankings
Outlook
06
20 21
Two pillars, two stories
Methodology
07 10
The safety dimension
The fleet management dividend
11
Data period: January 1, 2025 to December 31, 2025
Scale: 0–100 (higher = more efficient)
Questions: pr@geotab.com
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Executive Summary
Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
Executive summary
Geotab analysed a full year of connected vehicle data across seven major European capitals to benchmark urban freight efficiency at scale. Cities were scored on two dimensions: how well traffic flows through the network and the operational waste (in fuel, emissions and time) that congestion creates. Berlin and Amsterdam form a clear efficiency tier, with strong performance across both dimensions. Dublin and Rome occupy the middle ground, each with distinct strengths. Paris, London and Madrid face the greatest challenges — but for very different reasons. Congestion management is the biggest differentiator between cities — not vehicle behaviour. And across the study, truck fleets consistently outperform passenger vehicle fleets — not because of different technology, but because of operational discipline: structured routing, scheduled delivery windows and freight-specific infrastructure. Combined, the study fleet burned over 1.5 million litres of fuel while stationary in 2025 — estimated cost of idle fuel waste across connected vehicles in the study, in 2025.
Overall ranking
144% 5 of 7 The efficiency gap between the best and worst performing cities.
Cities where truck fleets outperform passenger vehicle fleets.
Rank City
Overall Score (0-100)
1 Berlin
61
2 Amsterdam
59
3 Dublin
49
4 Rome
48
39% €2.6m Collective improvement possible if all cities matched Berlin’s efficiency.
5 Paris
37
Estimated cost of idle fuel waste across connected vehicles in the study, in 2025.
6 London
29
7 Madrid
25
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Executive Summary
Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
MESSAGE FROM EDWARD KULPERGER
performance specifically, required a different approach. This report analyses twelve months of real operations, across seven European capitals, scored on two dimensions that map directly to what fleet operators care about: does the network allow vehicles to move efficiently, and if not, what is the cost? The findings are honest, and likely not comfortable for every city in this report. However, honest data is what the industry needs. Berlin and Amsterdam demonstrate that high-performing freight environments are achievable. Madrid and London show how much ground there is still to close, which requires both infrastructure investment and operational discipline from fleets. Geotab’s role is to give operators the data insights that provide visibility into how to execute: in the planning phase, on the road, and in operations review. That is what connected vehicle technology at scale makes possible. The operating environment facing European fleets is demanding. The leaders in this study are navigating it every day. Geotab is committed to providing deep data expertise and analytics that give fleet managers every possible advantage, ensuring ongoing success and resilience within their organisations.
Every morning, millions of vehicles pull out of depots across Europe. They carry food to supermarkets, components to factories, parcels to front doors, medicines to hospitals. The scale is easy to understate: commercial transportation is not a logistics sector — it is the operating layer that keeps everything else functioning. I have spent years working with fleet operators across this region. The pressure is visible in the details: tighter delivery windows, more stops per route, more regulations per city. Fuel costs are part of that pressure. The data in this report covers 2025 — a year of relative stability in European energy markets. Since then, geopolitical instability in the Middle East has pushed European diesel prices above €2 per litre, a 30% rise in a matter of weeks. At those prices, the idle fuel waste recorded in this study would cost an estimated €1 million more. The drivers navigating this complexity are skilled professionals operating under conditions that get harder each year. What is changing is the environment around them. European cities are growing. Zero-emission zones are expanding. Compliance requirements vary by city, by vehicle class, by year. The operators who can adapt, those with the data insights and visibility to act in real time, will navigate this period well. Those without that visibility are making decisions on assumptions. This is what made this index worth building. For years, we could observe congestion. Measuring it continuously, objectively, and at the level of commercial vehicle
The road ahead for European freight
Edward Kulperger Senior Vice President, EMEA, at Geotab
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Executive Summary
Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
Why urban freight efficiency matters
Freight is the circulatory system of European cities. Every product on a shelf, every parcel at a door, every component on a production line depends on the road network. When that system flows, economies thrive. When it slows, costs compound across entire supply chains: wasted fuel, excess emissions, unpredictable delivery windows, driver fatigue and increased costs to consumers.
How we measured city efficiency Data source: Geotab connected vehicle platform. Period: January–December 2025. Scope:
This Index measures both.
Using a full year of real-world connected vehicle data from the Geotab platform, we benchmarked seven major European capitals across two dimensions: 01 How well traffic flows Can vehicles move through the network efficiently? How predictable are journey times? How many hours per day does traffic flow freely? 02 What congestion actually costs When traffic slows, how much waste does it create? How much fuel is lost to idling? What is the real operational cost of gridlock?
7 European capitals — Berlin, Amsterdam, Dublin, Rome, Paris, London, Madrid. Vehicles: Passenger vehicles and trucks, analysed separately. Scoring: 0–100 scale (higher = more efficient). Note: Scores are based on a sample of connected vehicles and represent normalised, relative comparisons.
The results reveal dramatic differences between regions and between cities separated by only a few hundred kilometres.
Full methodology on page 21.
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Executive Summary
Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
The rankings
Berlin recorded the highest overall score (61), the only city where both dimensions score above 60. At the other end, Madrid (25) and London (29) face the greatest challenges. The gap between top and bottom is 36 points, a 144% difference. Three clear tiers emerge: the efficiency leaders (Berlin, Amsterdam), the middle ground (Dublin, Rome), and the cities under pressure (Paris, London, Madrid).
Performance
Rank City
Overall Score (0-100)
49
1 Berlin
61
29
59
61
2 Amsterdam
59
3 Dublin
49
4 Rome
48
“We expected variation between cities. A 144% efficiency gap between Berlin and Madrid was the finding that stopped us. Fleets operating across multiple European capitals are navigating fundamentally incomparable environments. How you plan, price, and schedule needs to reflect that.”
5 Paris
37
37
6 London
29
7 Madrid
25
48
25
High Above 50 Mid 30–50 Low Below 30
Abhinav Vasu AVP Solutions Engineering EMEA, Geotab
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Executive Summary
Foreword
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Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
Two pillars, two stories
Cities ranked by congestion performance:
The Index measures two dimensions for each city. Together, they tell very different stories about why some cities enable efficient freight movement and others do not. How traffic flows This dimension measures three things: congestion burden (how much congestion accumulates across the day), uncongested windows (how many hours traffic flows freely), and predictability (how consistent journey times are day to day).
The predictability insight
Rome and Paris have severe congestion but highly predictable journey times (variability scores of 80 and 82 respectively). Extreme congestion creates its own predictability: when roads are saturated, traffic settles into a stable, slow-moving equilibrium. London sits in the worst position: congested AND unpredictable. The same delivery route can take 20 minutes one day and 50 minutes the next. Predictable congestion lets fleet managers plan around it. Unpredictable congestion breaks schedules, customer commitments and driver utilisation.
61 Berlin
55 Amsterdam
Scores span a 3.8x range — this is where the real differentiation between cities happens.
48 Dublin
Madrid scores essentially zero on both congestion burden and uncongested windows, meaning congestion exceeds critical levels at every hour of the day. London is close behind with near-zero scores on both measures. Berlin benefits from a polycentric city layout and wide boulevards that distribute traffic load across the network. Its variability score (82) is among the highest: congestion is not only moderate, it is predictable.
39 Rome
30 Paris
21 London
16 Madrid
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What congestion costs
Trip inefficiency scores for each city:
This dimension measures mid-trip vehicle idling: the waste the system produces when traffic slows. Cities ranked by trip inefficiency: The surprise: these scores cluster in a narrow band (52 to 74, just 1.4x variance), compared to 3.8x for congestion. Performance differences between cities come overwhelmingly from congestion management. Rome illustrates this perfectly: worst-tier congestion but the best trip inefficiency score (74). Traffic is slow but flowing, vehicles creep along steadily rather than stopping and starting. Less pollution per kilometre than you might expect. Amsterdam achieves near-identical performance (72) through a very different model: compact urban form, shorter trips and optimised signal timing that keeps traffic moving.
“The trip inefficiency scores surprised us. They cluster in a narrow band — 1.4x variance, compared to 3.8x for congestion. Rome has the worst congestion in the study and the least idle waste for trucks. Traffic that moves slowly but steadily produces less waste than traffic that stops and starts. What separates the top cities from the bottom is almost entirely how the road network manages congestion.”
74 Rome
72 Amsterdam
62 Berlin
58 Paris
Abhinav Vasu AVP Solutions Engineering EMEA, Geotab
54 Madrid
52 Dublin
52 London
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Fuel data confirms what the efficiency scores suggest: less efficient road networks waste more fuel.
The waste is clearest when isolated to idle fuel — fuel burned while stationary:
London is the least fuel-efficient city for passenger vehicles at 15.60 L/100km, nearly 2.4x the Paris figure of 6.51 L/100km. Longer average trip distances in Paris and Madrid allow engines to reach operating temperature; London’s stop-and- go environment never allows this. Rome carries the worst congestion in the study and the least idle waste for trucks (2.8%). Slow- but-flowing traffic is more fuel-efficient than stop- and-start gridlock. Paris trucks waste nearly 1 in 5 litres while stationary. The Périphérique’s stop-and- go delivery environment is at its most damaging. Connected vehicles in this study burned an estimated 1.58 million litres of fuel while stationary in 2025 — approximately €2.6 million at that year’s European average fuel prices. Commercial trucks accounted for around €600,000 in wasted diesel; passenger and service vehicles a further €2 million in wasted petrol.
Trucks (idle fuel as % of total):
Passenger vehicles (idle fuel as % of total):
13.6%
18.2%
1 London
Paris
1
13.2%
2 Berlin
Amsterdam
12.5%
2
12.9%
3 Dublin
London
11.1%
3
10.5%
4 Amsterdam
Berlin
8.5%
4
8.2%
5 Madrid
Dublin
5.8%
5
7.9%
6 Rome
Rome
2.8%
6
5.7%
7 Paris
Madrid
2.8%
7
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The safety dimension
Two cities diverge from the pattern. Paris is the most dangerous city per trip despite a mid-table efficiency score — 78.5% of all harsh events are harsh accelerations. Drivers apply maximum throttle habitually from every standstill. High efficiency and high harm can coexist when driver behaviour, not road design, is the primary cause. London is anomalously safe relative to its low efficiency score (29). Despite the second-highest absolute event volume in the study, its per-trip rate of 462 is less than half of Madrid’s. Congestion charging, active enforcement, and lower aggression norms compensate for poor infrastructure. London’s safety record is a policy achievement as much as a network design achievement. Rome reinforces the point: some of the worst congestion in the study, just 393 harsh events per 1,000 trips. Slow-but- flowing traffic is safer than stop-and-start gridlock. Where harsh events cluster matters as much as how many. Amsterdam: 13.7% of all city events concentrate at the Schiphol motorway interchange (a solvable, infrastructure- specific problem). Dublin: the N7/Naas Road generates 71% of cornering events in its top hotspot cell. Paris: the Périphérique forces constant merge-and-weave with no policy mitigation. Berlin: hotspots dispersed across western districts — distributed demand, no single bottleneck. City-normalised benchmarking separates driver behaviour from road conditions. A driver generating 1,000 harsh events per 1,000 trips is at the city average in Madrid and well above it in Berlin. Performance targets should reflect the network your drivers operate in.
Using GPS-derived harsh driving event data (harsh acceleration, harsh braking, and harsh cornering) from Geotab connected vehicles in 2025, the pattern is consistent across all seven cities: efficient road networks produce safer driving conditions. Cities with higher efficiency scores generate fewer harsh events per trip:
Score City
Events per 1,000 trips
225
61 Berlin
315
49 Dublin
356
59 Amsterdam
“The road network structures when vehicles stop, how they accelerate, what the merge conditions look like at every junction. That’s why efficiency scores and harsh event rates track together in five of the seven cities. City-normalised benchmarking lets operators separate driver behaviour from infrastructure. A driver’s harsh event rate only means something when you know the city they’re operating in.”
393
48 Rome
462
29 London
1,088
25 Madrid
Abhinav Vasu AVP Solutions Engineering EMEA, Geotab
1,191
37 Paris
The gap between Berlin (225) and Paris (1,191) is 5.3x. Between Berlin and Madrid: 4.8x.
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Executive Summary
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What This Means Fleet Management The fleet management dividend City Snapshots Outlook
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Rome’s +26 gap is the clearest example: trucks navigate Rome’s narrow streets significantly better than passenger vehicles, benefiting from designated freight windows and professional routing. London and Madrid are the only cities where trucks underperform. In London, bus lane restrictions, narrow streets and complex loading regulations create unique freight challenges. In Madrid, truck variability (33) is the lowest
Across the study, truck fleets consistently outperform passenger vehicle fleets in five of seven cities. Both groups have Geotab devices. The advantage comes from operational structure: scheduled routing, designated delivery windows, off-peak scheduling and freight-specific infrastructure. Passenger vehicle fleets (service vehicles, sales teams, field technicians) are more often tied to customer schedules and business-hours destinations, with less flexibility to avoid peak congestion.
in the study — conditions are extremely unpredictable for commercial vehicles.
Passenger vs Truck scores
■ Passenger ■ Trucks
71 (+16)
65 (+10)
“In five of seven cities, commercial trucks outperform passenger vehicle fleets, due to how they operate, including scheduled routing, delivery windows, and freight-specific access. In Rome, where congestion is severe, structured freight operations perform dramatically better than unstructured passenger fleets. The difference is operational discipline, and it is something every fleet operator can act on.”
63 (+26)
57 (+14)
55
55
46 (+15)
43
37
31
29 27 (-2)
28
22 (-6)
Edward Kulperger Senior Vice President, EMEA, Geotab
Rome
Berlin
Paris
Dublin
Amsteram
London
Madrid
Ordered by truck performance advantage
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Berlin leads the Index with the highest overall score (61), the only city where both dimensions score above 60. Its polycentric layout distributes traffic load across the network — no single corridor dominates congestion, and no single chokepoint defines the operating day. Predictability is where Berlin separates itself further. Its variability score of 82 is among the highest in the study. Congestion is moderate, but more importantly, it is consistent — fleet operators can build schedules around it with confidence. Truck fleets (71) outperform passenger vehicles (55) by 16 points. The structured nature of freight operations maps well onto a network that already rewards planning.
City snapshot: 01 Berlin: The benchmark
For fleets operating here Berlin is the closest thing this study has to a benchmark operating environment. Journey times are reliable, harsh event rates are low, and the network’s predictability means scheduling commitments are achievable. The primary task for fleet operators is to maintain that discipline rather than build around uncertainty.
Score: 61
Driving profile
Congestion: 61
Trip Inefficiency: 62
Passenger: 55
Truck: 71
225 harsh events per 1,000 trips — safest in the study
11.06 L/100km 13.2% of fuel wasted idling
16 points Trucks outperform passengers by 16 points
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Amsterdam achieves its score through a very different model from Berlin. Compact urban form, shorter average trip distances and optimised signal timing combine to produce the best trip inefficiency score in the study (72) — less mid-trip idling than any other city. The network moves vehicles cleanly. Congestion performance is solid (55) but not exceptional. The 6-point gap with Berlin comes down to urban scale: Berlin’s polycentric network has more capacity to absorb demand. Amsterdam compensates through efficiency — fewer kilometres wasted, less fuel burned per trip. One notable hotspot: 13.7% of all city harsh events concentrate at the Schiphol motorway interchange. A significant share for a single location, and one that points to a solvable infrastructure problem rather than a systemic issue across the network.
City snapshot: 02 Amsterdam: Compact and flowing
For fleets operating here Amsterdam’s short trip profile suits urban last-mile and delivery operations well. Low idle waste keeps fuel costs manageable. The Schiphol interchange is the one location where active route planning around peak times pays off — the rest of the network is clean.
Score: 55
Driving profile
Congestion: 55
Trip Inefficiency: 72
Passenger: 55
Truck: 65
356 harsh events per 1,000 trips — safest in the study
11.10 L/100km 10.5% of fuel wasted idling
10 points Trucks outperform passengers by 10 points
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What This Means
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Methodology
Dublin’s overall score (49) masks a significant divide between vehicle types. Passenger vehicles score 43, dragging the city’s overall position down. Trucks score 57 — a 14-point gap that is the most operationally instructive finding in Dublin’s data. The explanation is scheduling. Truck operators in Dublin make effective use of off-peak delivery windows, shifting activity away from peak congestion. Passenger fleets — tied to business hours and customer schedules — have less room to do the same. The data is a direct case study in what structured operations achieve in a mid-tier congestion environment. One network-specific risk: the N7/Naas Road generates 71% of cornering harsh events in its top hotspot cell. The geometry of this corridor creates consistent risk for vehicles on it — a planning consideration for any fleet running regular routes along this stretch.
City snapshot: 03 Dublin: The truck town
For fleets operating here Off-peak scheduling is the
Score: 49
primary lever in Dublin. The truck-passenger gap
demonstrates it works at scale — fleets that adopt structured delivery windows measurably outperform those that do not. The N7/Naas Road warrants specific attention in route planning and driver briefings.
Driving profile
Congestion: 48
Trip Inefficiency: 52
Passenger: 43
Truck: 57
315 harsh events per 1,000 trips — safest in the study
11.97 L/100km 12.9% of fuel wasted idling
14 points Trucks outperform passengers by 14 points
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Rome is the study’s most counterintuitive result. It holds the worst congestion score (39) of any city — yet records the best trip inefficiency score (74), the lowest truck idle waste, and the largest truck-passenger performance gap in the study. Traffic is slow, but it flows. Vehicles creep along steadily rather than stopping and starting, and that distinction produces better outcomes than the congestion score alone would suggest. The truck advantage (+26) is not despite Rome’s conditions — it is partly because of them. Designated freight windows and professional routing give structured operations a significant edge in a network where narrow streets and historic urban form make ad hoc navigation genuinely difficult. Trucks that work within the system outperform those that do not, by a wider margin here than anywhere else in the study. Predictability reinforces the picture (variability score 80). Rome’s congestion is severe by the numbers, but consistent in its timing. Fleets that schedule around the known pattern operate more reliably than the raw score implies.
City snapshot: 04 Rome: Slow but flowing
For fleets operating here Build congestion into the schedule rather than planning against it. Rome’s predictability means arrivals can be timed reliably when the network’s patterns are respected. Freight windows are the critical tool — the data shows a 26-point performance advantage for fleets that use them.
Score: 48
Driving profile
Congestion: 39
Trip Inefficiency: 74
Passenger: 37
Truck: 63
396 harsh events per 1,000 trips — safest in the study
2.8% Truck idle waste — lowest in the study
26 points Trucks outperform passengers by 26 points
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Paris presents a contradiction the data makes precise. Passenger congestion exceeds the threshold at every hour — zero uncongested windows — yet the city’s variability score is 83, among the highest in the study. Congestion is constant, but remarkably consistent. Gridlock so predictable it becomes plannable. The safety profile tells a different story. Paris generates 1,191 harsh events per 1,000 trips, the highest of any city. 78.5% are harsh accelerations — drivers apply full throttle habitually from every standstill. The Périphérique and inner arrondissements produce conditions that are congested but not flowing in the way Rome’s are. Paris congestion is stop-and-start; Rome’s is steady. That difference is visible in the fuel data: Paris trucks waste 18.2% of all fuel idling, the worst figure in the study. Trucks still outperform passenger vehicles (+15), demonstrating that structured freight operations find ways to work even in the most constrained environments.
City snapshot: 05 Paris: Gridlocked but predictable
For fleets operating here The predictability of Paris congestion is the operational asset. Daytime deliveries should be scheduled around the congestion pattern, not against it. Off-peak and night- time windows are where the real efficiency gains sit — Paris’s variability score means timing precision is achievable for fleets willing to structure around it.
Score: 37
Driving profile
Congestion: 30
Trip Inefficiency: 58
Passenger: 31
Truck: 46
1,191 harsh events per 1,000 trips — safest in the study
18.2% of truck fuel wasted idling — highest in the study
15 points Trucks outperform passengers by 15 points
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London scores low on efficiency (29) but defies the pattern on safety. Its harsh event rate of 462 per 1,000 trips is significantly lower than Madrid or Paris — anomalously safe given the infrastructure. The explanation lies in policy: congestion charging, active enforcement and lower aggression norms have produced a safety record the road network alone would not generate. The fuel picture is harder. London is the least fuel-efficient city in the study for passenger vehicles at 15.60 L/100km, nearly 2.4x the Paris figure. The stop-and-go environment prevents engines reaching operating temperature, and idle waste at 13.6% is among the highest in the study. Persistent low-speed operation, not distance, drives the cost. London is one of only two cities where trucks underperform passenger vehicles. Bus lane restrictions, narrow streets and complex loading zone regulations neutralise the operational advantages freight fleets typically carry. Unpredictability compounds everything: the same delivery route can take 20 minutes one day and 50 minutes the next.
City snapshot: 06 London: The planning challenge
For fleets operating here Schedule with wider delivery windows than the distance suggests. Dynamic routing is not optional in London — fixed routes fail when journey times are this variable. The safety record reflects policy, not network conditions; it should not be read as evidence that the operating environment is forgiving.
Score: 29
Driving profile
Congestion: 21
Trip Inefficiency: 52
Passenger: 29
Truck: 27
432 harsh events per 1,000 trips — safest in the study
15.60 L/100km highest in the study; 13.6% idle waste
2 points Trucks score 2 points below passenger vehicles
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What This Means
Outlook
Methodology
Madrid sits at the foot of the Index with the lowest overall score (25) and the lowest congestion score (16). Congestion exceeds critical levels at every hour for both vehicle types — there is no manageable window in the operating day. The congestion readiness measure is effectively zero. What makes Madrid particularly difficult for freight operators is unpredictability compounding congestion. Truck variability (33) is the lowest in the study. Conditions for commercial vehicles are not just consistently poor — they are erratic. Planning around the network is harder when the network itself behaves differently from day to day. Madrid is one of only two cities where trucks underperform passenger vehicles, scoring 6 points below. The combination of congestion patterns, urban road layout and timing restrictions means the structured advantages of freight operations do not translate here the way they do elsewhere.
City snapshot: 07 Madrid: Under pressure
For fleets operating here Near-real-time routing and dynamic dispatching are baseline requirements. With no reliable congestion window and the lowest truck variability in the study, rigid scheduling will consistently underperform. Madrid rewards adaptability over planning.
Score: 25
Driving profile
Congestion: 16
Trip Inefficiency: 54
Passenger: 28
Truck: 22
1,088 harsh events per 1,000 trips — safest in the study
6.82 L/100km passenger; truck idle waste 2.8%
6 points Trucks score 6 points below passenger vehicles
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Foreword
Introduction
Rankings
Two Pillars
Safety
Fleet Management
City Snapshots
What This Means
Outlook
Methodology
What this means for you
For fleet operators
For city planners
For drivers
For policymakers
The data shows that operational structure — routing discipline, delivery scheduling, freight-specific strategies — measurably outperforms less structured approaches, even when the same connected vehicle technology is in place. A fleet running on-time in London is achieving something structurally different from one doing the same in Berlin — the road network is a fundamentally different constraint. Cities with high variability (London, Madrid) reward operational flexibility — wider delivery windows, near-real-time routing, the ability to adapt. Cities that are congested but predictable (Rome, Paris) reward scheduling
The data makes clear where the primary lever is: congestion management, not individual vehicle behaviour. The cities that score highest have invested in distributing traffic load (polycentric layouts, wider arterials, coordinated signal networks). That structural difference explains far more of the variation between cities than anything fleets do with their own vehicles. Connected vehicle data makes it possible to measure infrastructure performance continuously and objectively — not just at the point of investment, but over time, against a comparable baseline across cities.
The city shapes the data more than most benchmark systems acknowledge. A driver averaging 900 harsh events per 1,000 trips in Madrid is performing at the city average. The same rate in Berlin would be four times above it. Most variation in harsh event data comes from the road network, not the driver — and that has consequences for how performance data is read and how improvement targets are set.
The interventions that made Berlin and Amsterdam perform well (distributed road networks, coordinated signal timing, designated freight infrastructure) are not unknowns. The harder question is whether cities will invest at scale, and whether they will have access to objective, continuous measurement of what is working. This Index provides one part of that foundation. The scale of what is structurally possible is significant. If all seven cities matched Berlin’s efficiency score, the collective improvement across the region would be 39% (reduced congestion, lower emissions and more reliable journey times).
discipline — congestion is severe, but consistent enough to plan around.
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Outlook
Data is reshaping both sides of this equation. Cities that invest in evidence- based infrastructure decisions — measuring freight movement continuously rather than periodically — are better positioned to adapt to shifting demand. Fleets that build near- real-time routing and dynamic scheduling into standard operations are outperforming those that do not. The efficiency gap documented in this study is a static snapshot of a dynamic system. The question is who closes that gap, and with what tools.
Urban freight volumes are rising faster than road capacity. The seven cities in this study are already at different points of that curve — Berlin managing demand through distributed infrastructure, Madrid at the limit of what its network can absorb without structural change. That gap will widen if the patterns holding today continue. Zero-emission zone expansion is adding a layer of complexity to an already constrained environment. London, Paris, Amsterdam, Brussels and Madrid have all introduced or extended access restrictions for combustion vehicles in recent years. Fleet operators working across multiple European markets are managing compliance frameworks that vary by city and change with political cycles. The operational penalty for a failed delivery inside a restricted zone is higher than it was five years ago — and rising.
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Outlook
Methodology
Methodology
Dimension 1: How traffic flows [ 75% of vehicle score]
Dimension 2: What congestion costs [ 25% of vehicle score]
Measures how easily vehicles move through the network. Comprises three sub- components:
Measures waste produced by vehicles in the system, focusing on mid-trip idling. Higher idle ratios signal congestion, poor signal timing and bottlenecks.
Congestion burden (AUC) — 50% weight — cumulative congestion across the day.
Overall score = (Passenger score x 0.60) + (Truck score x 0.40)
Uncongested windows (Hours Below Threshold) — 25% weight — hours per day with free-flowing traffic.
The 60/40 weighting reflects that most road demand comes from passenger vehicles, while the truck component captures logistics efficiency. Scores are evaluated separately because the same road network can perform very differently for cars versus heavy vehicles.
Travel Time Variability — 25% weight — predictability of journey times.
Data caveats: –
Sample, not census: Geotab data represents a sample of connected vehicles. Scores are normalised and relative. Full-year analysis: All scores based on full-year 2025 data (Jan–Dec), smoothing seasonal variation, holidays and one-off events. City-level aggregation: Scores represent the overall urban road network. Individual corridors or districts may differ. Vehicle classification: Based on Geotab device configuration. Mixed-use vehicles are excluded.
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Congestion threshold: Defined as average travel times exceeding 120% of free-flow conditions, validated against known peak-hour patterns.
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– Fuel cost calculations: Idle fuel costs were estimated using 2025 average pump prices from the European Commission’s Weekly Oil Bulletin (EU average: diesel €1.55/L, petrol €1.63/L) for EU cities, and the UK Government’s Weekly Road Fuel Prices dataset (diesel 143p/L, petrol 135p/L) for London. UK prices converted to EUR at the 2025 average GBP/EUR rate of 1.185.
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European Urban Freight Efficiency Index 21
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