Application of Advanced Driver-Assistance Systems in Police Vehicles

Author:

Nasr Vanessa1ORCID,Wozniak David1ORCID,Shahini Farzaneh1,Zahabi Maryam1ORCID

Affiliation:

1. Industrial and Systems Engineering Department, Texas A&M University, College Station, TX

Abstract

Motor vehicle crashes are one of the leading causes of injuries and deaths for police officers. Advanced driver-assistance systems (ADAS) are driving control systems that have been found to improve civilian drivers’ safety; however, the impact of ADAS on police officers’ driving safety has yet to be investigated thoroughly. Disparities between driver states and tasks performed while driving between police and civilian drivers necessitate this distinction. This study identified the types of ADAS used in police vehicles, their impact on officers’ safety, and proposed potential future ADAS features to be implemented in police vehicles. A systematic literature review was conducted using Google Scholar, Compendex, Web of Science, Transport Research International Documentation (TRID), and Google Patents databases to identify the most prevalent police vehicles used in the U.S., available ADAS features in those vehicles, and the impact of ADAS on officers’ safety. A list of recommended ADAS features was developed based on the review of literature, authors’ knowledge and experience in the field, and the findings of an online survey with 73 police officers. Results indicated the addition of multiple ADAS features including the front vehicle detection system, intersection collision avoidance, evasive steering systems, left turn assist, traffic sign detection system, traffic jam assist, two lane and lane-ending detection, wrong-way alert, and autonomous highway driving features have the potential to improve officer safety and performance while driving. However, there was a void of studies focused on ADAS effects on police driving safety which needs to be addressed in future investigations.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Designing an Experimental Platform to Assess Ergonomic Factors and Distraction Index in Law Enforcement Vehicles during Mission-Based Routes;Machines;2024-07-24

2. Non-driving-related tasks and drivers’ takeover time: A meta-analysis;Transportation Research Part F: Traffic Psychology and Behaviour;2024-05

3. Effects of non-driving related tasks during autonomous driving;Diskuze v psychologii;2023-11-22

4. Creation and Implementation of Scenario Database for ADAS Application Verification;2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA);2023-08-18

5. Near-term impact of COVID-19 pandemic on seniors’ crash size and severity;Accident Analysis & Prevention;2023-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3