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kfzteile24
Best and Worst Cities to Drive 2017


At kfzteile24, we believe every city should be great to drive in. We conducted a study to discover which are the best and worst cities for driving, with the aim of enriching the debate around modern mobility and encouraging cities to learn from each other’s positive urban engagements and legislation.

The study examined several factors; congestion levels, public transport options, average cost of parking, cost of fuel, average speeds, levels of air pollution, accidents and fatalities, road quality and the frequency/perception of road rage. Any traffic delays or congestion caused by temporary construction work was not taken into account for this study. Once all factors were researched for 100 cities, a final score was calculated for each.

“Cars are an important accessory of modern life, and the means by which many use to get from A to B. Yet poor urban planning or a lack of civil education can make driving the most stressful experience of somebody’s day.” commented Thomas Kloubert, CMO of kfzteile24. “We hope that this study will act as a catalyst for those cities in the negative end of the ranking to invest in safer, cleaner and more efficient roads, and consider how methods adopted by higher scoring cities can be utilised in their own locations.”

Best and Worst Cities to Drive

  •  Congestion Level
  •  Gasoline (USD/Liter)
  •  Diesel (USD/Liter)
  •  Public Transport Alternative (Score)
  •  Cost of Parking (USD/hr)
  •  Downtown - Airport Speed (miles/hr)
  •  Air Pollution (Score)
  •  Road Traffic Injuries (Score)
  •  Road Quality (Score)
  •  Road Rage (Score)
  •  Rank

Global Results

#   City   Country  
1 Düsseldorf Germany 20% 1.52 1.31 8.88 1.74 21.20 5.55 7.03 9.23 8.96 1
2 Dubai UAE 26% 0.48 0.51 3.81 4.54 31.70 8.00 9.13 8.24 8.65 2
3 Zurich Switzerland 31% 1.42 1.49 9.59 3.65 25.50 7.00 8.78 9.80 9.86 3
4 Tokyo Japan 26% 1.14 0.94 10.00 4.18 30.50 4.27 6.94 8.83 8.45 4
5 Basel Switzerland 27% 1.42 1.49 9.01 2.55 17.50 7.64 10.00 9.80 9.91 5
6 Singapore Singapore 38% 1.44 0.99 8.56 1.39 32.40 3.45 8.69 10.00 8.25 6
7 Dortmund Germany 23% 1.49 1.26 7.39 1.74 19.90 5.18 7.03 9.23 9.01 7
8 Vienna Austria 31% 1.26 1.16 9.75 3.94 28.00 5.09 5.81 9.60 9.87 8
9 Munich Germany 30% 1.50 1.28 9.26 2.09 27.40 6.73 7.03 9.23 7.28 9
10 Calgary Canada 20% 0.93 0.77 8.27 10.96 26.80 10.00 5.19 8.83 7.19 10
11 Bern Switzerland 19% 1.42 1.49 8.65 2.78 12.40 6.45 10.00 9.80 9.78 11
12 Stuttgart Germany 28% 1.50 1.27 8.06 2.09 24.90 5.73 7.03 9.23 8.18 12
13 Montreal Canada 29% 0.93 0.77 9.01 7.04 23.00 8.82 5.19 8.83 8.81 13
14 Toronto Canada 30% 0.93 0.77 8.69 7.83 25.60 9.18 5.19 8.83 8.38 14
15 Helsinki Finland 31% 1.55 1.34 8.85 4.18 20.00 7.64 6.42 10.00 10.00 15
16 Seattle United States 34% 0.70 0.67 8.27 10.61 36.10 9.82 3.10 8.43 9.37 16
17 Frankfurt Germany 28% 1.51 1.27 7.64 3.13 20.50 4.73 7.03 9.23 8.78 17
18 Amsterdam Netherlands 22% 1.67 1.30 6.36 5.45 18.80 6.09 8.51 9.03 9.51 18
19 Perth Australia 27% 0.90 0.94 5.21 2.78 21.20 8.27 5.81 7.26 8.29 19
20 Essen Germany 28% 1.48 1.26 5.46 2.61 20.00 5.91 7.03 9.23 8.83 20
21 Madrid Spain 25% 1.29 1.17 3.97 2.90 24.30 7.91 8.17 8.83 6.15 21
22 Ottawa Canada 28% 0.93 0.77 7.52 6.66 18.10 9.91 5.19 8.83 8.45 22
23 San Antonio United States 20% 0.70 0.67 4.96 10.12 24.90 8.64 3.10 8.43 8.22 23
24 Geneva Switzerland 29% 1.42 1.49 8.87 3.57 11.20 7.27 10.00 9.80 9.73 24
25 Hamburg Germany 33% 1.49 1.25 8.42 1.74 12.50 6.82 7.03 9.23 9.26 25
26 Stockholm Sweden 28% 1.57 1.53 5.88 9.05 36.20 5.00 9.65 8.24 9.33 26
27 Marseille France 29% 1.46 1.31 4.06 2.67 29.90 4.09 6.42 10.00 8.45 27
28 Prague Czech Republic 23% 1.20 1.16 7.35 4.41 16.80 4.55 8.43 8.43 7.17 28
29 Graz Austria 29% 1.26 1.16 6.71 3.02 16.20 5.36 5.81 9.60 9.86 29
30 Rotterdam Netherlands 19% 1.67 1.30 8.76 4.64 13.10 6.00 8.51 9.03 6.54 30
31 Berlin Germany 29% 1.49 1.26 9.84 1.97 13.10 5.82 7.03 9.23 6.11 31
32 Barcelona Spain 31% 1.29 1.17 6.71 3.94 20.00 5.64 8.17 8.83 7.19 32
33 Cologne Germany 34% 1.51 1.27 6.94 2.09 20.60 5.45 7.03 9.23 7.03 33
34 Birmingham UK 40% 1.51 1.52 8.43 4.54 27.30 9.55 9.13 8.24 6.44 34
35 Bremen Germany 32% 1.51 1.27 8.22 2.67 11.20 7.09 7.03 9.23 8.81 35
36 Seoul Korea 30% 1.27 1.09 9.33 5.36 29.30 2.82 4.15 8.63 6.85 36
37 Oslo Norway 30% 1.83 1.70 8.09 6.15 44.10 6.36 8.08 4.33 9.48 37
38 Glasgow UK 30% 1.51 1.52 5.70 2.67 16.80 9.36 9.13 8.24 4.73 38
39 Bordeaux France 40% 1.46 1.31 6.94 2.78 13.80 6.45 6.42 10.00 10.00 39
40 Auckland New Zealand 38% 1.41 0.88 8.51 12.13 23.70 9.27 5.19 6.87 8.92 40
41 Austin United States 25% 0.70 0.67 5.21 6.07 16.20 8.18 3.10 8.43 7.35 41
42 Toulouse France 29% 1.46 1.31 4.64 3.13 13.20 7.36 7.03 9.23 7.91 42
43 Philadelphia United States 23% 0.70 0.67 5.30 17.19 18.70 7.73 3.10 8.43 6.00 43
44 Edinburgh UK 29% 1.51 1.52 8.09 5.94 13.70 6.18 9.13 8.24 6.17 44
45 Brisbane Australia 28% 0.90 0.94 4.22 14.72 17.40 8.73 5.81 7.26 8.42 45
46 London UK 38% 1.51 1.52 9.91 10.44 16.20 8.09 9.13 8.24 6.85 46
47 Wellington New Zealand 34% 1.41 0.88 7.77 3.82 10.70 9.64 5.19 6.87 8.94 47
48 Vancouver Canada 39% 0.93 0.77 8.18 5.87 15.00 9.73 5.19 8.83 5.59 48
49 Liverpool UK 40% 1.51 1.52 8.60 6.51 15.60 6.55 9.13 8.24 8.42 49
50 Boston United States 28% 0.70 0.67 6.94 16.44 16.80 7.36 3.10 8.43 5.81 50
51 Paris France 27% 1.46 1.31 9.50 4.99 15.00 4.45 6.42 10.00 2.31 51
52 Chicago United States 26% 0.70 0.67 9.26 15.16 13.80 6.64 3.10 8.43 4.22 52
53 Tallinn Estonia 26% 1.25 1.23 5.37 4.18 8.80 9.45 6.85 9.23 4.58 53
54 Budapest Hungary 22% 1.20 1.19 2.49 1.86 16.80 4.00 4.58 5.10 7.59 54
55 Melbourne Australia 33% 0.90 0.94 2.98 15.50 17.50 7.82 5.81 7.26 8.78 55
56 San Diego United States 27% 0.70 0.67 3.56 10.12 11.20 9.00 3.10 8.43 8.13 56
57 Adelaide Australia 27% 0.90 0.94 1.90 7.08 11.90 8.36 5.81 7.26 9.33 57
58 Lisbon Portugal 36% 1.57 1.32 7.19 2.09 8.10 9.09 4.50 9.80 4.73 58
59 Manchester UK 29% 1.51 1.52 9.10 5.89 14.30 1.36 3.01 10.00 7.21 59
60 Tel Aviv Israel 39% 1.69 1.55 5.63 1.72 21.90 2.64 8.34 6.47 3.68 60
61 Sydney Australia 39% 0.90 0.94 9.68 26.34 15.60 8.45 5.81 7.26 4.04 61
62 Cape Town South Africa 35% 0.96 0.96 7.19 1.02 17.50 2.18 1.09 6.87 3.70 62
63 Copenhagen Denmark 32% 1.61 1.35 5.79 4.41 16.20 4.82 4.67 5.50 9.35 63
64 Kuala Lumpur Malaysia 43% 0.49 0.47 2.82 1.06 30.50 2.73 1.35 7.84 4.22 64
65 Miami United States 30% 0.70 0.67 2.85 6.07 19.40 7.55 3.10 8.43 2.76 65
66 Nice France 38% 1.46 1.31 4.64 4.99 12.40 4.18 6.42 10.00 7.91 66
67 Johannesburg South Africa 47% 0.96 0.96 7.77 1.93 26.80 1.73 1.09 6.87 4.74 67
68 Riga Latvia 23% 1.14 1.01 2.57 2.90 18.10 3.55 4.06 3.54 5.28 68
69 Dublin Ireland 43% 1.44 1.28 4.47 3.19 9.40 8.91 7.99 7.84 6.65 69
70 New York United States 35% 0.70 0.67 9.42 27.61 11.20 8.55 3.10 8.43 2.58 70
71 Antwerp Belgium 30% 1.47 1.35 3.48 2.84 10.00 4.64 4.76 8.04 7.48 71
72 Brussels Belgium 38% 1.47 1.35 2.82 3.36 14.40 5.27 4.76 8.04 7.71 72
73 Athens Greece 36% 1.64 1.36 6.04 6.61 35.50 3.18 1.96 9.60 3.14 73
74 Santiago de Chile Chile 43% 1.13 0.73 2.08 2.74 22.40 2.00 2.83 8.24 4.55 74
75 Milan Italy 27% 1.63 1.47 1.99 6.03 34.90 3.27 4.93 5.70 4.19 75
76 Los Angeles United States 45% 0.70 0.67 4.22 10.12 20.50 7.27 3.10 8.43 3.68 76
77 Beijing China 46% 0.95 0.84 1.83 1.50 22.40 1.64 1.96 5.90 6.26 77
78 Shanghai China 48% 0.95 0.84 2.24 1.64 34.90 1.82 2.31 2.37 7.17 78
79 Rome Italy 35% 1.63 1.47 3.30 4.87 22.40 4.36 4.93 5.70 3.52 79
80 Buenos Aires Argentina 42% 1.30 1.14 4.96 2.01 25.60 4.91 2.75 3.16 1.92 80
81 Sofia Bulgaria 29% 1.11 1.08 2.66 1.18 13.20 2.91 4.41 2.17 3.02 81
82 Hong Kong China 41% 1.94 1.52 3.30 3.18 39.20 2.45 1.96 5.90 5.09 82
83 Warsaw Poland 37% 1.15 1.11 3.81 1.16 10.60 3.64 3.97 2.37 4.01 83
84 Moscow Russia 41% 0.70 0.65 4.96 3.34 18.10 3.73 1.79 1.77 2.12 84
85 Bangkok Thailand 61% 0.98 0.73 2.91 1.35 21.20 3.00 1.00 7.07 3.54 85
86 St Petersburg Russia 44% 0.70 0.65 6.04 3.34 17.40 3.73 1.79 1.77 1.00 86
87 Jakarta Indonesia 58% 0.63 0.68 1.09 0.38 17.50 2.09 2.66 3.93 3.68 87
88 Bucharest Romania 50% 1.11 1.10 2.31 0.57 16.20 3.91 4.32 1.00 3.99 88
89 Sao Paulo Brazil 30% 1.18 0.97 3.20 6.21 15.00 3.36 1.44 2.57 4.06 89
90 Rio de Janeiro Brazil 37% 1.18 0.97 3.56 4.13 12.50 2.55 1.44 2.57 4.51 90
91 Istanbul Turkey 49% 1.47 1.29 1.56 1.69 11.80 2.27 4.23 6.87 1.49 91
92 Mexico City Mexico 66% 0.92 0.87 5.46 6.97 17.50 3.09 2.92 6.09 4.62 92
93 Bogota Colombia 48% 0.75 0.69 1.56 5.22 12.50 2.36 4.93 4.53 1.22 93
94 Ho Chi Minh City Vietnam 64% 0.79 0.61 1.16 1.10 14.90 1.91 1.26 2.57 5.77 94
95 Bangalore India 64% 1.12 0.93 1.32 0.86 18.70 1.45 2.40 4.13 1.94 95
96 Mumbai India 67% 1.12 0.93 6.04 0.95 8.10 1.55 2.40 4.13 3.20 96
97 Ulaanbaatar Mongolia 65% 0.63 0.68 1.00 2.00 21.80 1.18 1.61 1.20 4.19 97
98 Lagos Nigeria 60% 0.46 0.65 1.25 0.32 10.70 1.00 1.70 2.76 3.50 98
99 Karachi Pakistan 59% 0.66 0.74 1.38 0.56 11.20 1.09 2.22 3.54 1.81 99
100 Kolkata India 69% 1.12 0.93 1.41 0.31 11.20 1.27 2.40 4.13 4.24 100

Methodology

To determine the 50 best and 50 worst cities for driving, we first examined the top 500 cities with the highest number of registered vehicles. Looking then into the cities with the most available traffic data, we decided on this definitive list of 100 cities.

To make a comparable quantification of how good or bad each city is to drive, we made a three-step evaluation of the data. First, we ranked the raw data from highest to lowest value and then we awarded a standard score based on their ranking in the following manner:

A low score indicates poor driving quality for that category, with each increasing number indicating that the city is better to drive in. A score of 1 represents the worst conditions possible and 10 indicates the best. Secondly, all categories were given an overall percentage. To create a comprehensive ranking, the Final Score is a weighted average of each individual category, as follows:

Final Score (i) =30% Congestion (i) + 15% Offroad (i) + 10% Parking (i) + 15% Speed (i) + 5% Air (i)+
+5% Petrol (i) + 10% Traffic Deaths (i) + 5% Road Quality (i) + 5% Road Rage (i)

Finally, we standardized the data to have a true final score. Note that for the congestion level category we represent the actual % of congestion and for the price of gasoline and diesel we put the actual price.

The study examined several key factors in order to determine the quality of driving in the 100 cities: congestion level, public transport options, the cost of parking, the cost of petrol, air pollution, the average speed between the city centre and the international airport, road fatalities, road quality and road rage.

 For the congestion level score, the data was provided primarily by the TomTom Traffic Index. For the cities not included in the TomTom index, data was provided by the city councils of the respective cities. Any traffic delays or congestion caused by temporary construction work was not taken into account for this study.

 The public transport options score affects the quality of driving in a city, because if there are poor public transport alternatives then there is no other option than for people to drive their cars, leading to increased congestion, faster degradation of road quality and increased road rage. A lack of off-road alternatives also means that elderly drivers are forced to continue using their cars when it might no longer be safe, leading to more road accidents. The score was calculated based on the length of the rapid transit system and suburban railway network for each city, with more kilometres of metro rail per capita equating to a higher score. Information on the size of the networks was provided by the system operators.

 The parking score was calculated based on the cost of parking for one hour. Information on parking was provided by the official parking authority of the city.

 The average speed score was based on the average speed between the city centre and the international airport. The average speed was calculated for three times of the day (morning rush hour, midday and evening rush hour), and then the three scores were averaged for a final score.

 The air pollution score was calculated based on data provided by the World Health Organisation’s 2016 air quality in cities database.

 The petrol price score was based on information from local stations taken on August 18th 2017.

 The World Health Organisation’s status report on road safety 2013 was used to calculate the road traffic injuries score for the cities.

 The road quality score was based on the Travel & Tourism Competitiveness Report 2013 produced by the World Economic Forum, where citizens of each country were asked to assess the quality of the roads in their country. This is also a national score and does not account for minor differences between cities.

 The road rage score was calculated based on the results of a poll conducted in each of the cities asking over 1000 drivers to rate their perception of road rage and the number of incidents witnessed in the past 12 months.

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