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ZENODO
Dataset . 2021
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2021
License: CC 0
Data sources: Datacite
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Traffic and accident data for AEB environmental impact research

Authors: Wu, Guoyuan; Liao, Xishun;

Traffic and accident data for AEB environmental impact research

Abstract

As one of the key advances in vehicle safety, Automatic Emergency Braking (AEB) has been introduced in the U.S. and the number of vehicles equipped with this technology has increased significantly in recent years. Most of existing studies have evaluated this technology at the individual vehicle level or focused on its safety performance. In this study, we tried to quantify its effectiveness on the energy consumption and tailpipe emissions. 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) developed a data-driven method to estimate the environmental impacts caused by the accidents that could be mitigated by AEB; and 4) conducted case study to show the efficacy of the proposed method. The results showed that the AEB technology may 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.

The main data sources include California Freeway Performance System (PeMS) and Highway Safety Information System (HSIS). The former is related to real-world traffic information collected from inductive loop detectors across California highways, while the latter involves accident related records, roadway geometry, and limited meteorological data. These two datasets need to be synchronized in both space and time for estimating environmental impacts of target accidents.

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Keywords

FOS: Civil engineering

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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