Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems

Download or Read eBook Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems PDF written by Seth Chalmers and published by SAE International. This book was released on 2023-07-18 with total page 48 pages. Available in PDF, EPUB and Kindle.
Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems
Author :
Publisher : SAE International
Total Pages : 48
Release :
ISBN-10 : 9781468606270
ISBN-13 : 1468606271
Rating : 4/5 (70 Downloads)

Book Synopsis Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems by : Seth Chalmers

Book excerpt: Thousands die or are injured each year in automobile crashes. Reducing the number of these tragedies requires reframing our approach to vehicle- and human-based transportation mobility and depends on whether the mobility industry and individual human drivers take a more aggressive approach to saving lives and preventing injuries. Bringing automated driving systems technologies into the advanced driver assist systems (ADAS) and connected vehicle space will help humans drive more safely and better prepare us for automated vehicles (AVs). Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems discusses the recent Partnership for Analytics Research in Traffic Safety report which shows that ADAS can indeed work. The path forward requires combining ADAS and ADS implementation with infrastructure engineering, law enforcement, education, emergency response, and public policy, with the goal of reaching zero deaths and serious injuries. It also requires fully embracing the US Department of Transportation Federal Highway Administration’s Safe System approach, backed by the addition of public policies that incorporate and expand ADAS’s role in achieving that safe system. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2023016


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