Modelling overtaking strategy and lateral distance in car-to-cyclist overtaking on rural roads: A driving simulator experiment

Haneen Farah*, Giulio Bianchi Piccinini, Makoto Itoh, Marco Dozza

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

37 Citations (Scopus)


The involvement of cyclists in road crashes has not been decreasing with the same magnitude as the involvement of other road users. In particular, the interactions between cyclists and motorized traffic can lead to high-severity crashes. To improve the safety of these interactions, a thorough understanding of road user behaviour is first needed. In this study, we focused on drivers overtaking cyclists on rural roads. The two main objectives of this study were to develop models that predicted: (a) drivers’ decisions to perform either a flying or an accelerative overtaking manoeuvre in the presence of oncoming traffic, and (b) the lateral comfort distance that drivers maintain from cyclists during the overtaking. A driving simulator study was designed to assess driver decision-making during the overtaking. The 37 drivers who participated in the study each performed seven overtaking manoeuvres with oncoming traffic. Out of the 259 overtaking manoeuvres, 168 were flying and 91 were accelerative. Binary logistic-regression models with mixed effects predicted the type of overtaking strategy (flying or accelerative). Driving speeds were found to significantly affect the strategy. The overall performance of the models predicting the strategy was 85–90%. Models were also developed for predicting the lateral comfort distance. The results show that the lateral comfort distance is mostly affected by the longitudinal distance between the subject vehicle and the oncoming vehicle, the longitudinal distance between the subject vehicle and the cyclist, and the presence of an oncoming vehicle—as well as by the drivers’ characteristics (sensation seeking in flying overtaking manoeuvres and ordinary violations in accelerative manoeuvres). The root mean square error, which was used to assess the performance of the models, ranged from 0.56 to 0.62. In conclusion, the models predicting the overtaking strategy performed reasonably well, while the models predicting lateral distance did not provide accurate predictions. The models predicting overtaking strategy may support (1) the development and evaluation of active safety systems, (2) the design of automated driving, and (3) policy making.

Original languageEnglish
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Pages (from-to)226-239
Number of pages14
Publication statusPublished - May 2019

Bibliographical note

Funding Information:
The authors thank the ADS project sponsored by the Area of Advance Transport at Chalmers. Dr. Haneen Farah thanks the Aspasia Grant Faculty 2016 for funding her research visit to SAFER Vehicle and Traffic Safety Centre at Chalmers. We would like to thank Kristina Mayberry for language revision.

Publisher Copyright:
© 2019 Elsevier Ltd


  • Active safety systems
  • Automated driving
  • Cyclists
  • Driver behaviour
  • Driving simulator
  • Overtaking
  • Human factors
  • Model


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