Driving behavior and safety analysis at OSMS section for merged, one-way freeway based on simulated driving safety analysis of driving behaviour

PLoS One. 2020 Feb 13;15(2):e0228238. doi: 10.1371/journal.pone.0228238. eCollection 2020.

Abstract

In order to study driving performance at the opening section of median strip (hereafter OSMS) on the freeway capacity expansion project, this study separately controlled 9 different simulated experimental scenarios of OSMS length and freeway traffic flow. 25 participants were recruited to perform 225 simulated driving tests using the driving simulator, and the analysis of variance (ANOVA) was used to analyze the driving characteristics which can represent the safety context. The results show that the safety parameters of driving are different when the length of OSMS and the traffic flow are different. When the traffic flow is low or moderate, the OSMS length can significantly affect the speed of the vehicle and the maximum values of time to collision. The higher the traffic flow, the smaller the minimum values of time headway. As the length of the OSMS decreases, the vehicles are more generally concentrated at the end of the opening area with the minimum values of time headway. The study also found that when the traffic volume is high, the impact of the OSMS length on driving performance will be weakened. In addition, the OSMS length and the traffic flow have little impact on driving comfort. Additionally, when the traffic flow is low or moderate, the opening length can significantly affect the driving behavior and safety of the vehicle. However, when the traffic volume is high, the impact of the opening length on them will be relatively weakened to some extent. Therefore, it is advised that in the case of freeways with large traffic volume, merely extending the length of the opening section does not necessarily optimize safety. Rather, the actual traffic density of the road should be carefully considered before a design length is adopted.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic
  • Analysis of Variance
  • Automobile Driving / statistics & numerical data*
  • Computer Simulation*
  • Humans
  • Models, Statistical
  • Safety*

Grants and funding

This study was supported by The National Nature Science Foundation of China: Modeling driving cognition behavior and driving performance improvement methodology considering workload environment (51678460); The Natural Science Foundation of China (U1664262, 51775396); Wuhan Science and Technology Bureau Enterprise Technology Innovation Project (2018010402011175); the Qilu Transportation Development Group Co, Ltd (2016B20). The funders played the role of carrying out experiments in data collection. We confirm that the source is not for any commercial purpose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.