01711233

Component

https://doi.org/10.1177/0361198119850470

Passing collisions are one of the most serious traffic safety problems on two-lane highways. These collisions occur when a driver overestimates the available sight distance. This paper presents a framework for a passing collision warning system (PCWS) that assists drivers in avoiding passing collisions by reducing the likelihood of human error. The system uses a combination of a camera and radar sensors to identify the impeding vehicle type and to detect the opposing vehicles traveling in the left lane. The study involved the development of a steering control model providing lane-change maneuvers, the design of a driving simulator experiment that allows for the collection of data necessary to estimate passing parameters, and the elaboration of the algorithm for the PCWS based on sensor signals to detect impeding vehicles such as trucks. Simulation tests were carried out to confirm the effectiveness of the proposed PCWS algorithm. The impact of driver behavior on passing maneuvers was also investigated. Mathematical and imitation models were enhanced to implement Simulink for replications of real-life driving scenarios. The different factors that affect system accuracy were also examined.

The Standing Committee on User Information Systems (AND20) peer-reviewed this paper (19-05906). © National Academy of Sciences: Transportation Research Board 2019.

19-05906

English

pp 1-12

2019-11

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

References (16)

Crash avoidance systems; Driving simulators; Opposing traffic; Passing; Traffic crashes; Two lane highways; Vehicle detectors; Warning devices

Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment

TRIS, TRB, ATRI

Apr 26 2019 3:05PM