Development of test scenarios and bicyclist surrogate for the evaluation of bicyclist automatic emergency braking systems. Issue 1 (7th August 2018)

• Record Type: Journal Article
• Authors: Yi, Qiang; Chien, Stanley; Li, Lingxi; Niu, Wensen; Chen, Yaobin; Good, David; Chen, Chi-Chih; Sherony, Rini
• Is Part Of: Journal of intelligent and connected vehicles. Volume 1:Issue 1(2018)
• Page Start: 15
• Page End: 27
• Publication Date: 2018-08-07
• Subjects: Bicyclist -- Surrogate bicyclist -- Automatic emergency braking (AEB) -- Crash scenarios -- Crash testing -- Naturalistic driving -- Radar cross section (RCS) -- Micro-Doppler; Intelligent transportation systems -- Periodicals; Automobiles -- Safety measures -- Periodicals; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; 629.2042
• DOI: 10.1108/JICV-02-2018-0005
• Languages: English
• ISSNs: 2399-9802

Abstract

Abstract : Purpose: To support the standardized evaluation of bicyclist automatic emergency braking (AEB) systems, test scenarios, test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute (TASI) at Indiana University-Purdue University Indianapolis. This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems. Design/methodology/approach: The harmonized general estimates system (GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data (NDD) are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions, vehicle speeds, bicyclist speeds, etc. A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA. A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems. Findings: Based on the analysis of the harmonized GES/FARS crash data, five crash scenarios are recommended for performance testing of bicyclist AEB systems. Combined with TASI 110-car naturalistic driving data, the crash environmental factors including lighting conditions, obscuring objects, vehicle speed and bicyclist speed are determined. The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA. The height of the bicycle rider mannequin is 173 cm, representing the weighted height of 50th percentile US male and female adults. The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame, respectively. Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems. Originality/value: The results have demonstrated that the developed scenarios, test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems. This is crucial for the development of advanced driver assistance systems.