Factors contributing to commercial vehicle rear-end conflicts in China: A study using on-board event data recorders

Giulio Bianchi Piccinini*, Johan Engström, Jonas Bärgman, Xuesong Wang

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

27 Citations (Scopus)


Introduction: In the last 30 years, China has undergone a dramatic increase in vehicle ownership and a resulting escalation in the number of road crashes. Although crash figures are decreasing today, they remain high; it is therefore important to investigate crash causation mechanisms to further improve road safety in China. Method: To shed more light on the topic, naturalistic driving data was collected in Shanghai as part of the evaluation of a behavior-based safety service. The data collection included instrumenting 47 vehicles belonging to a commercial fleet with data acquisition systems. From the overall sample, 91 rear-end crash or near-crash (CNC) events, triggered by 24 drivers, were used in the analysis. The CNC were annotated by three researchers, through an expert assessment methodology based on videos and kinematic variables. Results: The results show that the main factor behind the rear-end CNC was the adoption of very small safety margins. In contrast to results from previous studies in the US, the following vehicles' drivers typically had their eyes on the road and reacted quickly in response to the evolving conflict in most events. When delayed reactions occurred, they were mainly due to driving-related visual scanning mismatches (e.g., mirror checks) rather than visual distraction. Finally, the study identified four main conflict scenarios that represent the typical development of rear-end conflicts in this data. Conclusions: The findings of this study have several practical applications, such as informing the specifications of in-vehicle safety measures and automated driving and providing input into the design of coaching/training procedures to improve the driving habits of drivers.

Original languageEnglish
JournalJournal of Safety Research
Pages (from-to)143-153
Number of pages11
Publication statusPublished - Sept 2017

Bibliographical note

Funding Information:
The authors are grateful to Vinnova and the China Sweden Research Centre for Traffic Safety (CTS) for providing funding for the project, to the colleagues at Chalmers for the interesting discussions, to Mia Cheng for the assistance during the management of the project, and to Rusty Weiss and Patrick Huang for their support in collection. The authors would also like to thank Kristina Mayberry for language revision. This work has been carried out at SAFER - Vehicle and Traffic Safety Centre at Chalmers, Sweden.

Publisher Copyright:
© 2017 The Authors


  • Active safety systems
  • Human factors
  • Naturalistic driving data
  • Traffic safety
  • Truck drivers
  • Road safety


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