Citation

Hou L, Duan J, Wang W, Li R, Li G, Cheng B. J. Adv. Transp. 2019; 2019: e4023970.

Copyright

(Copyright © 2019, Institute for Transportation, Publisher John Wiley and Sons)

DOI

10.1155/2019/4023970

PMID

unavailable

Abstract

Bicycling is one of the popular modes of transportation, but bicyclists are easily involved in injuries or fatalities in vehicle-bicycle (V-B) accidents. The AEB (Autonomous Emergency Braking) systems have been developed to avoid collisions, but their adaptiveness needs to be further improved under different motion patterns of V-B conflicts. This paper analyzes drivers' braking behaviors in different motion patterns of V-B conflicts to improve the performance of Bicyclist-AEB systems. For safety and data reliability, a driving simulator was used to reconstruct two typical conflict types, i.e., SCR (a bicycle crossing the road from right in front of a straight going car) and SSR (a bicycle cut-in from right in front of a straight going car). Either conflict contained various parameterized motion patterns, which were characterized by a combination of parameters:




V


c




(car velocity), TTC (time-to-collision),




V


b




(bicycle velocity), and




D


l
a
t




(lateral distance between the car and the bicycle) or




V


l
a
t




(maximum lateral velocity of the bicycle). Some 26 licensed drivers participated in an orthogonal experiment for braking behavior analysis.

RESULTS revealed that drivers brake immediately when V-B conflicts occur; hence the BRT (brake reaction time) is independent of any motion pattern parameters. This was further verified by another orthogonal experiment with 10 participants using the eye tracking device. BRT in SSR is longer than that in SCR due to the less perceptible risk and drivers' lower expectation of a collision. The braking intensity and brake Pedal Speed are higher in short-TTC patterns in both conflict types. Therefore, TTC is not a proper activation threshold but a reasonable indicator of braking intensity and Pedal Speed for driver-adaptive AEB systems. By applying the findings in the Bicyclist-AEB, the adaptiveness and acceptability of Bicyclist-AEB systems can be improved.

Language: en