Bologna Città 30: Understanding the Influence of the Policy on Travel Times and Speeds Through TomTom Datasets

Bologna Città 30: Understanding the Influence of the Policy on Travel Times and Speeds Through TomTom Datasets

In January 2024, Bologna implemented the “Città 30” policy, lowering urban speed limits to 30 km/h to improve safety and livability. A study was conducted to assess the policy’s impact on traffic flow, using TomTom data to analyze changes in vehicle speeds and travel times. Results showed a significant reduction in average speeds, especially during peak hours, though compliance was lower during off-peak times. Minor increases in travel time were observed, but traffic flow remained largely unaffected. The study suggests the policy’s success in reducing speeds, with potential future research on enhancing compliance and evaluating long-term safety effects.

Introduction

On January 16, 2024, Bologna became the first major Italian city to implement the “Città 30” policy, which reduces the maximum speed limit in urban areas to enhance public safety and livability. Following the policy’s introduction, extensive discussions emerged regarding its effectiveness. These open questions prompted the need to develop a thorough study using various analytical techniques to explore all aspects of its implementation.

The initial focus of the research was to evaluate the 30 km/h speed limit policy on all urban roads. Through an extensive literature review, the policy’s potential benefits, particularly environmental improvements, and road safety enhancements, were analyzed. Then, the study focuses on leveraging extensive datasets provided by TomTom to analyze changes in Bologna’s traffic flow before and after the introduction of the “Città 30” policy. The overall goal is to understand the influence of the policy on travel times and speeds.

Figure 1 Bologna, 30 km/h campaign

Enabling Data and Methodology

Two main steps of the research are presented in this article:

  1. Literature Review: This qualitative phase involved the selection and review of 23 research papers and their classification under three categories: (i) environment (e.g., noise, air pollution, health); (ii) road safety (e.g., risk exposition, fatalities, collisions, traffic); and (iii) user needs (e.g., drivers’ behaviors, users’ information, and perception);
  2. TomTom Data Analysis: Traffic data was collected for 11 weeks from January to March in 2023 and 2024 (pre- and post-policy implementation) and was analyzed for vehicle counts and speeds. To streamline the analysis, the study targeted four specific hours each day—two peak (8-9 a.m., 7-8 p.m.) and two off-peak (6-7 a.m., 10-11 p.m.).

The methodology for the following data analyses began with data cleaning and reorganization to ensure sample robustness. Then, only streets where speed limits changed year-to-year were selected, excluding primary roads that retained a 50 km/h limit and roads under construction. Statistical analyses focused on average vehicle speeds and travel times over 11-week periods in both 2023 and 2024, along with year-over-year changes in these metrics, assessing citizens’ compliance to the new policy and potential changes in congestion and driving patterns.

Results

Literature Review

The literature review on the “Città 30” policy implementation focuses on three main areas: road safety, environmental impact, and citizen behaviors. For road safety, studies examine how a 30 km/h speed limit affects accident rates and traffic dynamics in urban areas. Of the 14 papers analyzed, several highlight a reduction in accident rates, including fatal accidents, in cities like Toronto, London, and Turin (Bassani et al., 2020; Fridman et al., 2020; Grundy et al., 2009). Some studies assess the policy’s effect on traffic flow (Grundy et al., 2009; Lu et al., 2023; Pazzini et al., 2023).

On environmental impacts, research is divided. Studies address noise pollution, air quality, focusing on CO2, CO, NOx, and particulate matter, fuel types, and public health outcomes. Simulations suggest that a lower speed limit could reduce NOx emissions by up to 40% and particulates by 10%, though some researchers find that the policy’s actual impact on emissions is limited due to variables like driver behavior, fuel type, and vehicle characteristics (Brink, Mathieu and Rüttener, 2022; Panis et al., 2011; Rossi et al., 2020; Tang et al., 2019).

The third area, citizen behaviors and perceptions, explores demographic factors (like age and gender) that affect public response to the policy, along with implementation strategies and communication approaches. Studies compare gradual versus citywide policy rollouts and examine how municipalities communicate benefits, emphasizing either safety or sustainability (Bordarie, 2019; Williams et al. 2022). Research also tracks changes in driver behavior and the time needed for compliance with new speed limits (Bordarie, 2019; Williams et al. 2022).

Overall, while environmental benefits remain inconclusive according to the selected literature, the policy demonstrates clear gains in road safety, with consistent reductions in urban accident rates across multiple cities. This evidence highlights road safety as a central motivator in adopting the “Città 30” policy.

TomTom Data Analysis

Data Validation

Data analysis was conducted in two phases, with the first focusing on assessing the robustness of the TomTom dataset by comparing it to vehicular counts from the Municipality of Bologna. The analysis, conducted during the last week of January for both 2023 and 2024, focused on peak hours (8-9 a.m. and 7-8 p.m.) and off-peak hours (6-7 a.m. and 10-11 p.m.). In 2023, the sample ranged from 8.24% to 9.88%, with the lowest representativeness of 5.73% during 6-7 a.m. (see Chart 1). In 2024, the sample ranged from 7.25% to 9.65%, with the 10-11 p.m. period showing a higher representativeness of 23.84% (see Chart 2).

Chart 1 Data Validation 2023
Chart 2 Data Validation 2024

Average Vehicle Speed

The second phase of analysis examined vehicle speeds across time periods over 11 weeks in both 2023 and 2024, assessing the impact of the “Città 30” policy. Average vehicle speed, a key indicator for traffic behavior and policy impact, revealed a significant reduction in speeds in 2024 compared to 2023. Results are detailed in Chart 3. During peak hours, speeds decreased by an average of 2.56 km/h in the morning and 2.29 km/h in the evening, with the largest reductions occurring during the first week after policy implementation. Non-peak hours also saw declines, with average speed differences of 2.34 km/h and 3.61 km/h for various time slots. Aggregated data over 11 weeks showed a consistent reduction in average speeds, with some areas even recording speeds below the 30 km/h limit. A T-test confirmed statistically significant differences in speed averages between 2023 and 2024 (p < 0.05), supporting the policy’s effectiveness in reducing traffic speeds.

Chart 3 Average Speed Comparison 2023-2024

Maps were created to visualize the spatial distribution of average vehicle speeds before and after the policy. Despite the reduction in speeds in 2024, compliance with the 30 km/h speed limit was not uniform across Bologna. Non-compliance was most evident during off-peak hours, with many streets exceeding the limit. In peak hours, the increase in traffic naturally slowed vehicles, resulting in better compliance. Figure 2-5 outline spatial diffusion in speed compliance.

Figure 2 Bologna, Compliance with the 30 km/h speed limit between 6-7 a.m.
Figure 3 Bologna, Compliance with the 30 km/h speed limit between 8-9 a.m.
Figure 4 Bologna, Compliance with the 30 km/h speed limit between 7-8 p.m.
Figure 5 Bologna, Compliance with the 30 km/h speed limit between 10-11 p.m.

Travel Time

The travel time analysis evaluated the impact of the “Città 30” policy on vehicle travel times across various routes in Bologna. The analysis revealed a slight increase in travel times following the policy’s introduction (see Chart 4). The largest increase occurred between 6-7 a.m., equal to 1.11 seconds on average over 11 weeks, and the smallest increase was between 10-11 p.m., equal to 0.26 seconds. During peak hours, the 8-9 a.m. period saw an average increase of 0.97 seconds, while the 7-8 p.m. period saw an increase of 0.48 seconds. Unlike the speed data, travel times did not peak in the first week after the policy was implemented. Instead, the largest increases were observed in the third week for non-peak hours and between the seventh and eighth weeks for peak hours. The aggregated results confirmed a consistent but modest increase in travel times in 2024, with T-test results indicating statistically significant differences in travel times between the two years (p < 0.05).

Overall, the analysis shows that the “Città 30” policy had a clear impact on reducing average speeds and increasing travel times, although compliance with the new speed limits was inconsistent, particularly in off-peak hours. The policy’s effects were statistically significant, but the modest changes in travel time suggest limited disruption to overall traffic flow.

Chart 4 Travel Time Comparison 2023-2024

Conclusions and Future Works

The implementation of the “Città 30” policy in Bologna has had a significant impact on reducing average vehicle speeds across the city. The analysis of TomTom data revealed clear decreases in speeds, particularly during peak hours, aligning with the intended goal of enhancing road safety and livability. However, while the policy has led to lower speeds overall, compliance with the new speed limit was inconsistent, with higher non-compliance observed during off-peak hours. Travel time analysis also showed slight increases, although these were modest, indicating that the policy did not cause substantial disruptions to traffic flow. These results suggest that while the policy has achieved its primary goal of reducing speeds, further measures may be needed to improve compliance, particularly during off-peak periods.

Future studies could explore strategies to improve compliance with the speed limit, particularly through better enforcement or public education. Additionally, further research could investigate the long-term impacts of the policy on driving behaviors and on accident rates.

Acknowledgments

The research work has been carried out in collaboration with Cristiano Carenzi, as part of his M.Sc. in Sociology at the Università degli Studi di Milano-Bicocca (Milan, Italy). We thank Prof. Matteo Colleoni (Department of Sociology and Social Research, University of Milan-Bicocca) for his contribution to this research. We thank citiEU Consultancy LTD for their fruitful collaboration and for sharing data. The analyzed data were treated according to the GDPR-General Data Protection Regulation (EU, 2016/679). This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

References

Bassani, M., Rossetti, L., & Catani, L. (2020). Traffic crash pattern modification as a result of a 30 km/h zone implementation. A case study in Turin (Italy). Transportation Research Procedia, 45, 402-409. https://doi.org/10.1016/j.trpro.2020.03.032

Bordarie, J. (2019). Predicting intentions to comply with speed limits using a ‘decision tree’ applied to an extended version of the theory of planned behaviour. Transportation Research Part F: Traffic Psychology and Behaviour, 63, 174–185. https://doi.org/10.1016/j.trf.2019.04.005

Brink, M., Mathieu, S., & Rüttener, S. (2022). Lowering urban speed limits to 30 km/h reduces noise annoyance and shifts exposure–response relationships: Evidence from a field study in Zurich. Environment International, 170, 107651. https://doi.org/10.1016/j.envint.2022.107651

Fridman, L., Ling, R., Rothman, L., Cloutier, M. S., Macarthur, C., Hagel, B., & Howard, A. (2020). Effect of reducing the posted speed limit to 30 km per hour on pedestrian motor vehicle collisions in Toronto, Canada-a quasi-experimental, pre-post study. BMC public health, 20, 1-8. https://doi.org/10.1186/s12889-019-8139-5

Grundy, C., Steinbach, R., Edwards, P., Green, J., Armstrong, B., & Wilkinson, P. (2009). Effect of 20 mph traffic speed zones on road injuries in London, 1986-2006: controlled interrupted time series analysis. BMJ, 339. https://doi.org/10.1136/bmj.b4469

Lu, Q. L., Qurashi, M., & Antoniou, C. (2023). Simulation-based policy analysis: the case of urban speed limits. Transportation Research Part A: Policy and Practice, 175, 103754. https://doi.org/10.1016/j.tra.2023.103754

Panis, L. I., Beckx, C., Broekx, S., De Vlieger, I., Schrooten, L., Degraeuwe, B., & Pelkmans, L. (2011). PM, NOx and CO2 emission reductions from speed management policies in Europe. Transport Policy, 18(1), 32-37. https://doi.org/10.1016/j.tranpol.2010.05.005

Pazzini, M., Lantieri, C., Vignali, V., Dondi, G., Giovannini, A., & Mora, A. (2023). Road users’ behaviour in the “30 km/h zones”. The case study of Bologna. Transportation Research Procedia, 69, 504-511. https://dx.doi.org/10.1016/j.trpro.2023.02.201

Rossi, I. A., Vienneau, D., Ragettli, M. S., Flückiger, B., & Röösli, M. (2020). Estimating the health benefits associated with a speed limit reduction to thirty kilometres per hour: A health impact assessment of noise and road traffic crashes for the Swiss city of Lausanne. Environment International, 145, 106126. https://doi.org/10.1016/j.envint.2020.106126

Tang, J., McNabola, A., Misstear, B., Pilla, F., & Alam, M. S. (2019). Assessing the impact of vehicle speed limits and fleet composition on air quality near a school. International Journal of Environmental Research and Public Health, 16(1), 149. https://doi.org/10.3390/ijerph16010149

Williams, A. J., Manner, J., Nightingale, G., Turner, K., Kelly, P., Baker, G., … & Jepson, R. (2022). Public attitudes to, and perceived impacts of 20mph (32 km/h) speed limits in Edinburgh: An exploratory study using the Speed Limits Perceptions Survey (SLiPS). Transportation Research Part F: Traffic Psychology and Behaviour, 84, 99-113. https://doi.org/10.1016/j.trf.2021.11.022