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 somebodys 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.