The 2019 Driving 
 Cities Index

The best and worst cities for drivers

At Mister Auto, we understand that many people spend a great deal of their lives behind the wheel. Considering that drivers lose over 200 hours a year commuting in the US alone, we decided to delve into the multiple factors that affect motorists on a daily basis. From infrastructure and congestion, to driver behavior, our comprehensive study takes a deeper look into cities which are successfully utilising infrastructure and legislation to improve conditions for vehicle users.

We began the study by collecting data for hundreds of cities worldwide which was whittled down to a shortlist of 100 cities. Each of these provided reliable and extensive data which also allowed for a wide range of scores, from excellent to needing improvement, with regards to their achievement in each factor. This ensured a range of results, allowing cities to stand out for their individual merits in comparison to other locations. We then decided to divide the parameters of the study into three categories that are most important to making a city a good location to drive: infrastructure, safety and costs.

To determine a city’s infrastructure, we examined factors such as the number of cars per capita, traffic congestion, road and public transport quality, among others. Next, we researched air quality levels in order to determine the city's commitment to providing fresh air and good visibility for its drivers and citizens alike.

Next, the safety of each location was analysed by the car accident fatality rate as well as conducting a poll focusing on incidents of road rage, in order to paint a picture of the aggressiveness and general driving culture brought to the city by motorists.

Finally, we looked at the costs associated with driving in each city, including not only at the price of combustibles in each location, but also the purchase parity of each country to determine how affordable driving was for its inhabitants. We also took into account the amount of city road tax paid on a yearly basis.

The final index combines a total of 15 factors to reveal the best and worst cities for car owners to drive-in across the globe.

Each column in the table below is filterable. All scores are out of 100, where the higher the score, the better, with the exception of the Road Rage Score, where the lower the score, the fewer the incidents.

The full methodology explaining how each factor was calculated can be found at the bottom of the page.
All currency figures are in USD.


  • # Cars / Capita
  • Daily Average Congestion Score
  • Road Quality Score
  • Public Transport Score
  • City Speed Sample Score
  • Average Car Age
  • Air Quality Score


  • Road Rage Score
  • Fatality Rate / 100,000 inhabitants


  • Cost of Parking / 2hrs
  • Cost of Parking by Affordability Score
  • Cost of Petrol / L
  • Cost of Petrol by Affordability Score
  • Annual Road Tax
  • Annual Road Tax by Affordability Score
Infrastructure Safety Costs
# City Country
1CalgaryCanadaNorth America0.6398.7890.6975.601009.0093.8229.162.603.5997.171.0298.1164.9597.22100
3OttawaCanadaNorth America0.5494.7390.6976.6688.939.0097.6330.262.906.5692.751.0298.1191.7794.7896.60
4BernSwitzerlandWestern Europe0.4397.9410079.6877.498.6082.1820.253.304.9398.321.6098.54266.5489.2696.23
5El PasoUSANorth America0.5710096.0360.7780.4010.2086.3148.5211.204.4395.980.7199.4578.8196.0196.01
6VancouverCanadaNorth America0.1189.5490.6982.3255.799.0098.0824.322.405.1794.821.0298.1155.3898.0895.99
7GothenburgSwedenNorthern Europe0.2699.3394.2892.2572.4710.0093.0423.112.404.5197.051.6496.8659.8298.6995.66
8DusseldorfGermanyWestern Europe0.5297.5094.9786.7673.659.3074.8514.752.303.3797.621.5696.1489.5795.1995.36
9BaselSwitzerlandWestern Europe0.4095.2110083.1186.188.6080.2115.302.006.6496.871.6098.54359.7484.4295.28
10DortmundGermanyWestern Europe0.4397.9494.9786.6084.839.3070.3817.832.702.9998.181.5696.1489.5795.1995.27
11ZurichSwitzerlandWestern Europe0.4492.6910090.9776.108.6081.4210.021.806.1497.291.6098.54161.5094.7295.17
12EssenGermanyWestern Europe0.4297.9494.9787.3888.119.3067.7614.753.403.3797.621.5696.1489.5795.1994.95
14MalmoSwedenNorthern Europe0.2910094.2891.0391.7010.0085.4324.652.506.3494.821.6496.8659.8298.6994.14
15GrazAustriaWestern Europe0.4795.2196.1980.7669.688.2069.746.836.106.2393.701.3996.91533.6857.0993.51
16CologneGermanyWestern Europe0.3595.8294.9787.4581.649.3075.6418.272.705.7094.251.5696.1489.5795.1993.09
17ViennaAustriaWestern Europe0.4093.9496.1985.6766.618.2074.8520.691.108.0891.081.3996.91533.6857.0992.98
18StockholmSwedenNorthern Europe0.2495.3094.2896.1872.4110.0098.5531.030.906.5394.591.6496.8659.8298.6992.88
19BremenGermanyWestern Europe0.3693.2294.9788.8456.109.3079.7415.301.905.0795.171.5696.1489.5795.1992.86
20DetroitUSANorth America0.6799.5496.0366.8790.1210.7083.7346.5412.206.7592.690.7699.23103.2493.9492.86
21OsloNorwayNorthern Europe0.4197.5089.9886.8793.6910.5088.1615.521.004.7498.321.9197.68317.6785.9692.44
22GenevaSwitzerlandWestern Europe0.4391.6110087.4953.728.6077.5022.452.705.0498.221.6098.54298.5687.6092.34
24StuttgartGermanyWestern Europe0.3593.2294.9789.6986.559.3077.7216.734.205.4894.571.5696.1489.5795.1991.88
25MunichGermanyWestern Europe0.3593.4394.9792.4567.609.3078.1523.224.704.4996.001.5696.1489.5795.1991.37
26FrankfurtGermanyWestern Europe0.3295.0994.9791.6585.489.3078.3732.243.405.9093.961.5696.1489.5795.1991.17
27BirminghamUKNorthern Europe0.3396.0789.6685.8463.187.8080.4535.762.004.2495.721.6095.30261.3377.5690.63
28MontrealCanadaNorth America0.4593.5390.6983.2858.289.0090.4946.431.8011.5185.371.0298.1190.2594.9290.35
30GlasgowUKNorthern Europe0.3596.1589.6674.8895.247.8088.1637.302.706.4692.161.6095.30261.3377.5689.67
31San AntonioUSANorth America0.5899.1996.0363.0978.8110.2086.9145.1116.0012.2584.420.6499.7052.3798.4089.63
32LiverpoolUKNorthern Europe0.3794.7389.6676.5366.177.8082.9527.621.706.6991.771.6095.30261.3377.5689.33
33ToulouseFranceWestern Europe0.5195.0597.1681.4168.108.8080.4535.215.903.8096.141.6794.66204.8482.1688.42
34CopenhagenDenmarkNorthern Europe0.3397.3095.0695.2171.828.8082.187.601.4010.4190.701.7596.87281.9783.5988.23
35OrlandoUSANorth America0.5798.1096.0362.7283.2410.6095.4553.8023.408.1589.580.6799.3832.1910087.86
36HamburgGermanyWestern Europe0.3491.7194.9788.7361.909.3079.5150.391.505.5694.461.5696.1489.5795.1987.76
37LeedsUKNorthern Europe0.3792.4889.6675.4367.417.8081.1734.551.905.6593.461.6095.30261.3377.5687.76
38PhiladelphiaUSANorth America0.5996.2296.0382.6668.5511.8082.8672.5013.905.9294.080.7799.2638.4799.7787.76
39AustinUSANorth America0.6295.9696.0365.6374.6210.2085.8638.9515.2014.3081.380.6599.6462.5197.4887.38
40BostonUSANorth America0.5995.2796.0388.7961.109.8094.3371.627.8015.8684.650.7410060.7298.9487.37
41BelfastUKNorthern Europe0.3891.0589.6675.9573.727.8085.4343.903.403.5096.911.6095.30261.3377.5687.25
42NiceFranceWestern Europe0.4693.5097.1680.1180.208.8076.4520.806.905.9092.621.6794.66237.1278.8687.15
43ValenciaSpainSouthern Europe0.4698.0093.1590.7268.5711.4082.9541.373.607.4584.931.4692.93143.5282.4687.08
44ManchesterUKNorthern Europe0.3892.1689.6689.8966.917.8081.1740.050.807.1691.021.6095.30261.3377.5686.88
45San FranciscoUSANorth America0.6190.2896.0393.0561.4911.2087.7250.618.908.6091.411.0198.73111.3494.3586.82
46SeattleUSANorth America0.6893.1596.0381.3494.0813.8095.1029.939.5014.9084.800.9299.28145.5092.5786.41
47UtrechtNetherlandsWestern Europe0.3197.5098.0583.3386.9410.4077.9442.803.107.6192.231.8395.55533.5059.1586.32
48BordeauxFranceWestern Europe0.5093.1797.1681.0659.008.8078.8238.296.204.5294.931.6794.66191.3983.5486.25
49AucklandNew ZealandOceania0.5693.7387.6167.7159.249.0098.4620.253.309.2688.001.5295.78557.1649.8686.17
50BristolUKNorthern Europe0.3892.1689.6682.1975.317.8081.6749.403.105.1094.341.6095.30261.3377.5686.06
51TorontoCanadaNorth America0.4989.8690.6979.7158.269.0092.6650.722.2014.3981.071.0298.1191.7794.7885.92
52BerlinGermanyWestern Europe0.2992.0794.9792.9550.269.3072.8061.061.305.8194.101.5696.1489.5795.1985.89
53SeoulSouth KoreaAsia0.2293.2394.4897.3891.5910.0058.8228.173.008.8282.401.2994.28188.5376.9085.46
54Las VegasUSANorth America0.5798.7296.0363.6266.9911.6090.7076.5717.306.4792.540.8698.66101.2293.6085.45
56AntwerpBelgiumWestern Europe0.3993.4588.0979.1152.798.9074.2738.625.006.7092.261.5595.85238.0480.9084.97
57LyonFranceWestern Europe0.4191.0497.1684.7957.938.8075.0547.424.905.5993.131.6794.66200.3582.6283.76
58MadridSpainSouthern Europe0.4896.3093.1594.1963.1711.4084.5852.261.9010.1878.491.4692.93144.5882.3083.57
59PragueCzechiaEastern Europe0.5494.5384.1488.0576.2514.5073.7149.841.403.6189.331.4188.30129.9874.1683.19
60San DiegoUSANorth America0.6392.8496.0375.5758.8511.2088.9745.5512.3015.1282.990.9998.81111.3494.3582.72
61RotterdamNetherlandsWestern Europe0.3296.6198.0589.0175.9510.4077.9451.272.705.2395.451.8395.55578.3355.4582.63
62MiamiUSANorth America0.5492.9796.0378.4862.5810.6096.4186.6917.0011.6084.110.6899.3032.1910081.89
63Buenos AiresArgentinaLatin America0.2488.7864.4277.8359.0311.6074.1671.403.702.9389.570.8492.1367.6184.8581.77
64BrightonUKNorthern Europe0.3491.0589.6674.7668.627.8082.4350.833.2010.4085.831.6095.30261.3377.5681.47
65MarseilleFranceWestern Europe0.4192.6297.1679.9473.968.8072.8049.736.908.0189.071.6794.66237.1278.8681.29
66BarcelonaSpainSouthern Europe0.3992.9193.1595.1862.0611.4077.9435.432.2012.9371.961.4692.93153.2081.0681.08
68EdinburghUKNorthern Europe0.3387.4189.6691.9854.207.8093.4356.442.709.9386.581.6095.30261.3377.5681.00
69BrusselsBelgiumWestern Europe0.4189.7788.0990.8877.468.9074.0846.212.5011.8684.361.5595.85238.0480.9080.75
70SalvadorBrazilLatin America0.2188.9559.7073.3854.249.7099.5351.164.203.5679.211.0683.33132.9350.2280.30
71AmsterdamNetherlandsWestern Europe0.2297.0998.0591.0867.1210.4078.1548.852.9011.6286.801.8395.55520.0560.2679.72
72ParisFranceWestern Europe0.3189.8297.1697.1550.018.8074.6667.991.809.3586.831.6794.66230.8479.5179.57
73ChicagoUSANorth America0.5994.2396.0392.6355.7710.9079.3781.3011.4016.2680.200.8599.09102.2394.5679.46
74LisbonPortugalSouthern Europe0.4494.5494.0376.9852.8112.6085.7260.622.305.9783.471.6687.93191.8665.8279.32
75TurinItalySouthern Europe0.6797.0782.6672.5670.8310.8061.9954.906.405.6290.921.7592.44260.3570.3378.87
76DublinIrelandNorthern Europe0.3386.3882.6491.6060.478.8087.2276.241.406.7292.821.5996.03313.8275.5178.85
77LondonUKNorthern Europe0.2983.1089.6698.0428.807.8091.9254.131.5012.5282.431.6095.30261.3377.5677.58
78Los AngelesUSANorth America0.5986.7296.0383.0744.3911.2081.4582.2911.9011.2887.950.9998.80111.3494.3576.99
79RomeItalySouthern Europe0.6192.3582.6675.9263.7910.8071.5668.875.206.6588.781.7592.44280.1167.8475.42
80WarsawPolandEastern Europe0.5686.0879.9384.6850.3413.6063.0973.933.803.3586.731.2985.8161.7485.4174.48
81NaplesItalySouthern Europe0.5794.2082.6672.6651.0610.8071.0578.554.107.8986.221.7592.44307.7364.3774.04
82MilanItalySouthern Europe0.5795.3482.6688.1863.6810.8059.5765.353.2011.9677.821.7592.44254.4771.0773.81
84Tel AvivIsraelAsia0.0783.8787.6263.8261.1313.0064.4443.904.205.8593.331.8094.58284.1275.9572.43
87New YorkUSANorth America0.4489.4996.0310043.809.8086.8874.377.5038.5455.530.8099.6279.9697.1769.06
89St. PetersburgRussiaEastern Europe0.3082.1075.3882.1543.0213.0042.0096.1518.002.0189.580.7189.9364.2677.9166.50
90AthensGreeceSouthern Europe0.7789.2181.6567.3658.1915.0068.6470.854.306.6179.531.7985.39280.2043.7866.30
91MoscowRussiaEastern Europe0.3083.4575.3890.6552.9413.0065.1598.4618.004.9870.450.7189.9345.9085.1165.97
92Rio de JaneiroBrazilLatin America0.1583.4659.7085.0080.969.7072.6286.4712.203.9177.011.0683.33212.6818.4965.38
93Mexico CityMexicoLatin America0.2477.8278.5581.4632.8814.0062.2393.6210.002.4583.861.0880.0735.9886.4564.43
94Sao PauloBrazilLatin America0.4783.6359.7078.7342.109.7066.8190.3215.405.2768.141.0683.33212.6818.4959.12
95BogotaColombiaLatin America0.1870.3659.3116.9443.5414.0062.7295.497.202.5675.660.7481.10102.0037.9156.16


The 2019 Driving Cities Index takes a comprehensive look into the numerous indicators that determine a city’s driving conditions. The index comprises of 100 global cities ranked according to 15 factors, resulting in an all-inclusive benchmark that illustrates exactly where each location succeeds, and where improvement is needed.


In order to allow for a wide range of scores across each factor, 100 cities that provided reliable and extensive data were selected from around the world. This ensured a range of results, allowing cities to stand out for their individual merits in comparison to other locations.

The 100 cities were then categorised by their Region, in order to allow for comparison on a regional level.


The study focuses on three main categories that impact driving conditions for motorists: Infrastructure, Safety and Costs. These three categories comprise of a total of 15 factors which are outlined below:


  • # Cars / Capita
  • Daily Average Congestion Score
  • Road Quality Score
  • Public Transport Score
  • City Speed Sample Score
  • Average Car Age
  • Air Quality Score


  • Road Rage Score
  • Fatality Rate / 100,000 inhabitants


  • Cost of Parking / 2hrs
  • Cost of Parking by Affordability Score
  • Cost of Petrol / L
  • Cost of Petrol by Affordability Score
  • Annual Road Tax
  • Annual Road Tax by Affordability Score

This score for each factor is obtained directly from the raw data and implements a normalisation of the form:

Score(i) = 99 * ( ( (x(i) - x(min) ) / ( (x(max) - x(min) ) ) + 1

The final total score for each city was then determined by calculating the sum of the weighted average score of the factors, which in turn has been normalised in order to create a final result between 1 and 100.

All of the information collected is based on the latest data available.


# Cars / Capita

The number of cars per capita of the total population, at a city level. Values for Tokyo, Athens, Buenos Aires, Lagos, Istanbul, Lisbon, Wellington, Dubai, Porto, Auckland, and Osaka were collected at a subnational level. The higher the number of cars per capita, the greater the demonstration of a city’s driving uptake and attractiveness for motorists.

Sources: United Nations, US Census Bureau, Eurostat, local statistics departments, local news resources.

Daily Average Congestion Score

The average amount of travel time lost to traffic congestion, as a score. Congestion levels are measured by comparing free-flow conditions in a city over a 24-hour period. The higher the score, the lower the impact of traffic congestion on an individual’s driving experience.

Sources: Tomtom 2018 Traffic Index, Inrix 2018 Traffic Scorecard, Waze 2016 Driver Satisfaction Index, TrafficIndex August 2019.

Road Quality Score

The quality of road infrastructure as perceived by residents and logistics experts. Data reflects survey results taken at a national level. The higher the score, the better the quality of the road infrastructure.

Sources: World Economic Forum, World Bank

Public Transport Score

A score based on the accessibility, reliability, and affordability of the public transportation system in a metropolitan area. Additional data was included on the ratio of the dedicated public transport infrastructure (MRT, BRT) per capita and per overall road length, as well as data on the share of residents who use public transportation to commute. The higher the score the better, as the increased accessibility and ease of public transport contributes to the fall in density of road traffic.

Sources: Local transport authorities, Deloitte 2019 City Mobility Index, Arcadis 2017 Sustainable Cities Mobility Index, McKinsey 2018 Urban Transport Systems, Numbeo, and others.

City Speed Sample Score

The average speed while driving within the city centre, expressed as a score. Data was collected by measuring the driving speed of a car’s first 10km on a trajectory from the main train station to the main airport. For cities without an interstate or international train station, the public library was used as a starting point. All measurements were taken at approximately 12:00PM local time, 2 September 2019, and the local congestion levels and road obstructions such as construction sites were accounted for in the final calculations. A greater speed measured equates to a higher score, which is preferential for this factor.

Sources: Google Maps, Tomtom, Inrix

Average Car Age

The average age of a car at a national level, expressed in years. State-level data was used for US cities. The lower the age the better, as the smaller the chances there are for issues to arise which may be detrimental to road users in the location.

Sources: Autoalan Tiedotuskeskus, Auto Alliance, TecAlliance, PricewaterhouseCoopers, and others.

Air Quality Score

The annual mean for the dispersion of particulate matter (PM) 2.5 ug/m3, at a city level. Fine particulate matter (PM2.5) was chosen as a means to determine air quality due to its status as an air pollutant that is of most concern for city-dwellers health at high levels. Therefore, the higher the score, the lower the amount of (PM) 2.5.

Sources: World Health Organisation, OECD


Road Rage Score

The degree of road rage experienced by locals in each city, obtained from survey results conducted in September 2019. Over 6000 drivers across all cities between the ages of 25 to 60 (who drive for more than 150 minutes per week) were asked to respond to the following questions:

  • In the last 6 months, how many times did you see an incident of road rage (1-5)?
  • In the last 3 months, have you been part of an incident of road rage started by someone else (Y/N)?

The results of the survey were then compiled and converted into a scoring system, where the lower the score, the fewer incidents of road rage witnessed by the respondents.

Source: Survey conducted from 2.9.2019 - 19.9.2019.

Fatality Rate / 100,000 inhabitants

The number of fatalities involving at least one vehicle per 100,000 inhabitants at a city-level. National data was used for cities in India, Mongolia, Nigeria, Russia, Turkey, and Israel.

Sources: Local official sources, World Health Organisation,, local news resources.


Cost of Parking / 2 hrs

The average cost of 2 hours of city parking in a garage and on the street at a city-level, between August-September 2019. Free parking was not included. The lower the cost, the more preferential for drivers in the city.

Sources: Parkopedia, Institute for Transport and Development Policy

Cost of Parking by Affordability Score

The cost of parking as a percentage of the 2017 national average wage. The 2018 average wage by state was taken for US cities (latest data available). The higher the score, the lower the percentage of the national average wage spent on parking.

Sources: World Bank, Stats America

Cost of Petrol / L

The average price of petrol per litre at a national level, as of 12.08.2019. State prices were taken for US cities. The lower the cost, the more preferential for drivers in the city. The lower the cost, the more preferential for drivers in the city.

Sources: Global Petrol Prices

Cost of Petrol by Affordability Score

The cost of petrol as a percentage of the 2017 national average wage. The 2018 average wage by state was taken for US cities (latest data available). The higher the score, the lower the percentage of the national average wage spent on petrol.

Sources: World Bank, Stats America

Annual Road Tax

The cost of ‘road tax’, or its local equivalent per year at a city-level, as of 2019. In places without a specified road tax, registration tax was taken instead. The charge used for this factor is based on a popular 2011 model car on the market with the following specifications: four (plus one) doors; M1 class; 1,596 CC; 88 kW/120 bhp; 1.6 lt; 134 g/km CO2; kg: 1,100; metres: 3.95; Euro Standard: 5; fuel type: petrol; drive: manual; Energy Performance Certificate: E. The lower the cost, the more preferential for drivers in the city.

Sources: Local road authorities, tax departments, and news resources.

Annual Road Tax by Affordability Score

The annual road tax as a percentage of the 2017 national average wage. The 2018 average wage by state was taken for US cities (latest data available). The higher the score, the lower the percentage of the national average wage spent on annual road tax.

Sources: World Bank, Stats America

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