Imperial College London
Portrait Picture

ProfessorMohammedQuddus

Faculty of Engineering, Department of Civil and Environmental Engineering

Chair in Intelligent Transport Systems
 
 
 
//

Contact

 

+44 (0)20 7594 6121m.quddus Website

 
 
//

Assistant

 

Ms Maya Mistry +44 (0)20 7594 6100

 
//

Location

 

308Skempton BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Wang:2023:10.1016/j.aap.2023.107265,
author = {Wang, X and Ye, C and Quddus, M and Morris, A},
doi = {10.1016/j.aap.2023.107265},
journal = {Accident Analysis and Prevention},
title = {Pedestrian safety in an automated driving environment: calibrating and evaluating the responsibility-sensitive safety model},
url = {http://dx.doi.org/10.1016/j.aap.2023.107265},
volume = {192},
year = {2023}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The severity of vehicle-pedestrian crashes has prompted authorities worldwide to concentrate on improving pedestrian safety. The situation has only become more urgent with the approach of automated driving scenarios. The Responsibility-Sensitive Safety (RSS) model, introduced by Mobileye®, is a rigorous mathematical model developed to facilitate the safe operation of automated vehicles. The RSS model has been calibrated for several vehicle conflict scenarios; however, it has not yet been tested for pedestrian safety. Therefore, this study calibrates and evaluates the RSS model for pedestrian safety using data from the Shanghai Naturalistic Driving Study. Nearly 400 vehicle-pedestrian conflicts were extracted from 8,000 trips by the threshold and manual check method, and then divided into 16 basic scenarios in three categories. Because crossing conflicts were the most serious and frequent, they were reproduced in MATLAB's Simulink with each vehicle replaced with a virtual automated vehicle loaded with the RSS controller module. With the objectives of maximizing safety and minimizing conservativeness, the non-dominated sorting genetic algorithm II was applied to calibrate the RSS model for vehicle-pedestrian conflicts. The safety performance of the RSS model was then compared with that of the commonly used active safety function, autonomous emergency braking (AEB), and with human driving. Findings verified that the RSS model was safer in vehicle-pedestrian conflicts than both the AEB model and human driving. Its performance also yielded the best test results in producing smooth and stable driving. This study provides a reliable reference for the safe control of automated vehicles with respect to pedestrians.
AU  - Wang,X
AU  - Ye,C
AU  - Quddus,M
AU  - Morris,A
DO  - 10.1016/j.aap.2023.107265
PY  - 2023///
SN  - 0001-4575
TI  - Pedestrian safety in an automated driving environment: calibrating and evaluating the responsibility-sensitive safety model
T2  - Accident Analysis and Prevention
UR  - http://dx.doi.org/10.1016/j.aap.2023.107265
UR  - https://www.ncbi.nlm.nih.gov/pubmed/37619318
UR  - https://doi.org/10.1016/j.aap.2023.107265
VL  - 192
ER  -
Download