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Research Projects

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STATUS: Complete YEAR: 2019 TOPIC AREA: Sustainability, energy, and health Transportation planning, policy, and finance CENTER: PSR

Estimating the Impacts of Automatic Emergency Braking (AEB) Technology on Traffic Energy and Emissions

Project Summary

Project number: PSR-19-26a
Funding source: US DOT
Contract number: 69A3551747109
Funding amount: $99,995
Performance period: 1/15/2020 to 6/30/2021

Link to project datahttps://doi.org/10.6086/D1D11H

Project Description

As one of the key advances in vehicle safety, Automatic Emergency Braking (AEB) has been introduced in the last several years and the number of vehicles equipped with this technology has been steadily increasing. To date, most of existing studies on AEB systems have been focused on evaluating the safety performance of this technology. In this study, we attempt to quantify the AEB system benefits on environmental sustainability, due to its ability to mitigate accidents and any resulting traffic congestion avoidance. We have developed a data-driven method that analyzing the impact of rear-end accidents that could potentially be avoided due to AEB systems, resulting in improvements to traffic flow. Towards this end, we: 1) performed literature review on AEB technology; 2) built a database including real-world traffic state measurements, traffic accident records, roadway geometry, and weather information; 3) selected the target accident that could be potentially mitigated by AEB systems; 4) developed a data-driven method to estimate the spatial-temporal region caused by the target accident; and 5) estimated the excessive energy consumption and tailpipe emissions that could be potentially avoided due to the deployment of AEB systems. To show the efficacy of the proposed method, we conducted a case study for a real-world scenario along SR-91 in Riverside, California. The results showed that a small penetration of AEB technology could potentially improve energy economy by up to 34.6% and reduce pollutant emissions (e.g., CO, HC, NOx and PM) by as much as 22.5%, if the selected accidents could be avoided.


P.I. NAME & ADDRESS

Guoyuan Wu
Associate Researcher
Department of Electrical and Computer Engineering
Riverside, CA 92521
United States
[email protected]

CO-P.I.

Matthew Barth
Director, Bourns College of Engineering - Center for Environmental Research & Technology
1084 Columbia Avenue
Riverside, CA 92507
United States
[email protected]