01656866

Component

There is a growing interest in analyzing lateral interactions between two wheelers and automobiles due to the significant influence of the interactions on traffic performance and safety. This paper examines the lateral distance between two wheelers and automobiles during overtaking at a shared traffic street. A video-based computer vision technique is used to track road-users, collect their trajectories, and measure the lateral distance. A full Bayesian logit model is developed to investigate the factors that may affect the likelihood of two wheelers to accept the critical lateral distance. The analysis results show that (a) the average lateral distance between two wheelers and automobiles is 1.542 m; (b) the lateral distance for bicycles is significantly larger than that for e-bikes and e-scooters; (c) the lateral distance follows a best-fitted Gamma distribution; (d) 90% of lateral distance exceeds 1.1 m. Further results from the full Bayesian logit model show that: (1) the two wheelers type, the evasive action manner, the occurrence of a platoon of moving two wheelers, and two wheelers’ yaw rate ratio are significantly positively related to the probability of two wheelers accepting the critical lateral distance; (2) the presence of heavy vehicles and the speed difference between two wheelers and the interacting automobiles are negatively associated with the above probability.

This paper was sponsored by TRB committee ANF30 Standing Committee on Motorcycles and Mopeds. Alternate title: Analysis of the Lateral Distance Between Two Wheelers and Automobiles During Overtaking at Shared Traffic Facility

18-03174

English

17p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Photos; References

Automobiles; Computer vision; Distance; Gap acceptance; Logits; Passing; Two wheeled vehicles; Vehicle mix

Highways; Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-03174

TRIS, TRB, ATRI

Jan 8 2018 10:46AM