# Naturalistic Study of Cycling and E-Cycling in Marseille

Claire Naude, Ebrahim Riahi, Bastien Canu, Fanny Vincent, Thierry Serre

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Claire Naude, Ebrahim Riahi, Bastien Canu, Fanny Vincent, Thierry Serre. Naturalistic Study of Cycling and E-Cycling in Marseille. International Cycling Safety Conference (ICSC), Nov 2025, Oslo, Norway. hal-05359219

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# Naturalistic Study of Cycling and E-Cycling in Marseille

Submission #33

Claire Naude, Ebrahim Riahi, Bastien Canu, Fanny Vincent, Thierry Serre

Université Gustave Eiffel - Accident Mechanisms Laboratory

## Introduction

In urban areas facing congestion and pollution, bicycles and e-bikes are becoming popular sustainable mobility options, driving changes in use and infrastructure, and raising question safety and accessibility. Although the environmental and health benefits of cycling are well established, further research is needed to understand cyclists' behaviour in real-life conditions. This study uses a naturalistic approach to collect objective data and highlights the dynamics of cycling in Marseille, France.

## Material and Methods

The naturalistic cycling study conducted in Marseille tracked the daily trips of 10 cyclists on conventional bicycles (Bikes) and 7 on electric bicycles (eBikes, electric assistance up to 25 over a period of two months. Data was collected via a smartphone mounted on a 3D-printed handlebar holder (Figure 1) and a dedicated data acquisition app. The variables analysed include trajectories, speeds, accelerations and rotational velocities. Criteria for detecting emergency manoeuvres -hard braking and hard cornering-as well as strong jolts caused by road defects infrastructure, were established through controlled track tests and applied using appropriate and threshold values. The dataset enabled analysis of usage patterns and comparison between eBikes and Bikes. Finally, the results were mapped to identify locations where emergency manoeuvres and jolts are common, highlighting potentially hazardous spots possibly related to road layout design.

## Results

Nearly 900 trips covering 2,000 km were recorded, with three-quarters by Bike and one-quarter by eBike (Table 1).
<table><caption>Table 1 - Collection report</caption><thead><tr><th></th><th>N. drivers</th><th>N. trips</th><th>Distance (km)</th><th>Duration (h)</th></tr></thead><tbody><tr><th>Bike</th><td>10</td><td>552</td><td>1,465</td><td>137</td></tr><tr><th>eBike</th><td>7</td><td>311</td><td>522</td><td>43</td></tr><tr><th>All</th><td>17</td><td>363</td><td>1,987</td><td>180</td></tr></tbody></table>

Average trip durations were 16 minutes for Bikes and 12 minutes for eBikes, with mean speed 11.5 km/h and 13 km/h, respectively (Table 2, Figure 2). Both groups reached similar maximal speeds, around 25 km/h.

<table><caption>Table 2 - Trips dynamics (mean and standard deviation)</caption><thead><tr><th></th><th>Mean trip<br>duration (min)</th><th>Mean trip<br>distance (km)</th><th>Mean speed<br>(km/h)</th><th>Mean speed<br>without stops<br>(km/h)</th><th>Mean maximal<br>speed (km/h)</th></tr></thead><tbody><tr><th>Bike</th><td>16.1 [10.5]</td><td>2.9 [2]</td><td>11.5 [2.9]</td><td>12.1 [3.4]</td><td>25 [7.2]</td></tr><tr><th>eBike</th><td>12.0 [6]</td><td>2.6 [1.5]</td><td>13.0 [3.2]</td><td>13.3 [3.3]</td><td>25.3 [5.4]</td></tr><tr><th>All</th><td>14.4 [8.7]</td><td>2.8 [1.8]</td><td>12.1 [3.0]</td><td>12.7 [3.4]</td><td>25.2 [6.5]</td></tr></tbody></table>

eBike users spent 44% of their time above 15 km/h, compared to 30% for Bike users, while spent above 25 km/h was similar for both groups (Figure 3).

On average, cyclists stopped (for over 2 seconds) 2.1 times per kilometre, with eBike users more frequently (2.4 vs. 1.9) and showing greater variability between individuals (Table 3, 4). Bike users performed more emergency manoeuvres: hard braking (0.3 vs. 0.2 per km) and especially hard cornering (0.9 vs. 0.07 per km). Both groups experienced strong jolts about every 10 km.
<table><caption>Table 3 - Manoeuvres and dynamic events</caption><thead><tr><th>N. per km</th><th>Stops</th><th>Hard braking</th><th>Hard cornering</th><th>Strong jolts</th></tr></thead><tbody><tr><th>Bike</th><td>1.9</td><td>0.34</td><td>0.90</td><td>0.14</td></tr><tr><th>eBike</th><td>2.4</td><td>0.19</td><td>0.07</td><td>0.06</td></tr><tr><th>All</th><td>2.1</td><td>0.28</td><td>0.63</td><td>0.11</td></tr></tbody></table>

Analysis of the routes taken (see Figure 5) indicates that most Bike users tended to stay within city centre and southern districts, whereas e-Bike users ventured further afield, including the east, north, and north-west of the city. The lowest speeds were recorded in the city centre, falling below 15 km/h. Outside the central area, speeds generally ranged from 15 to 25 km/h only occasional instances exceeding 25 km/h.

When emergency manoeuvres and jolts were mapped (see Figures 6 and 7), certain locations out as hotspots for hard braking and cornering—likely areas where riders had to take evasive action. These specific zones need further analysis, as they may benefit from targeted infrastructure upgrades to improve safety for all users.

## Discussion

Several naturalistic studies have explored the behaviors of conventional cyclists and e-bike users often focusing on large Nordic cities or areas with strong cycling infrastructure. For instance, Gothenburg, Dozza and al. found that e-bike riders tend to travel faster and face more risky situations than traditional cyclists, often due to inadequate infrastructure. They suggested that making e-bikes more visible could help improve safety. However, these contexts differ from Marseille's Mediterranean environment.

In our study, average speeds in Marseille were lower-13 km/h for e-bikes and 11.5 km/h for bikes—compared to 19 km/h and 15 km/h in Gothenburg. This likely reflects Marseille's fragility and sometimes unsafe cycling network, hilly terrain, and frequent interactions with traffic, especially in the city centre, where cyclists face a lack of continuous cycle paths and must cede慢 down or stop.

## Conclusion

Our findings show that cyclists in Marseille experience lower speeds and more frequent stops.
those in Northern European cities, highlighting the impact of limited and discontinuous
infrastructure on mobility and safety. Mapping of emergency manoeuvres identified specific
risk areas, often linked to poor road design or lack of suitable facilities. Targeted improvements
in these zones could enhance safety and encourage cycling.

This study adds to the literature by focusing on a Mediterranean city with unique challenges
objective, real-world data.

Future work should expand the sample size and explore the effects of infrastructure upgrades
the aim of supporting safer, more efficient, and more attractive cycling in Mediterranean cities
Marseille. These analyses will be replicated in Lyon and Paris, as naturalistic studies are placed
both cities in the near future.

References

Dozza, M., Bianchi Piccinini, G. F., & Werneke, J. (2016). Using naturalistic data to assess cyclist behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 21– https://doi.org/10.1016/j.trf.2015.04.003

**Presentation type:** Oral presentation