Citation

Scanlon JM, Sherony R, Gabler HC. IEEE Trans. Intel. Transp. Syst. 2018; 19(3): 774-786.

Copyright

(Copyright © 2018, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2017.2699079

PMID

unavailable

Abstract

Drivers involved in intersection collisions are at high risk of serious or fatal injury. Intersection advanced driver assistance systems (I-ADAS) are emerging active safety systems designed to help drivers safely traverse intersections. The effectiveness of I-ADAS is expected to be greatly dependent on pre-crash vehicle acceleration during intersection traversals. The objective of this paper was to develop pre-crash acceleration models for non-turning drivers involved in straight crossing path crashes and left-turning drivers in left turn across path opposite direction and lateral direction crashes. This paper used 348 event data recorder pre-crash records taken from crashes investigated as part of the National Automotive Sampling System/Crashworthiness Data System. The acceleration models generated from this pre-crash data were evaluated using a leave-one-out cross-validation procedure. Previously developed non-crash models from the literature were compared with the pre-crash models. Our hypothesis was that drivers involved in crashes would accelerate more aggressively than the "typical" driving population. This result suggests that drivers in pre-crash scenarios tend to accelerate more aggressively than drivers in normal scenarios (p<;0.001). This has important implications for the design of I-ADAS. Specifically, higher acceleration results in less available time for I-ADAS to detect and respond to an imminent collision.

Language: en

Keywords

Acceleration; active safety system; active safety systems; autonomous vehicles; Computer crashes; Crashworthiness Data System; Databases; driver acceleration; Driver assistance system; driver assistance systems; driver behavior; driver information systems; I-ADAS; intersection; intersection collisions; intersection traversals; lateral direction crashes; National Automotive Sampling System; noncrash models; pre-crash acceleration models; pre-crash data; pre-crash models; pre-crash scenarios; pre-crash vehicle acceleration; real-world intersection crashes; road accidents; road safety; road vehicles; Safety; Turning; Vehicle crash testing; Vehicles