Back of Queue Warning and Critical Information Delivery to Motorists

Li, Lingxi; Chen, Yaobin; Tian, Renran; Li, Feng

doi:10.5703/1288284317102

i

Back of Queue Warning and Critical Information Delivery to Motorists

2019-08-01
By Li, Lingxi ; Chen, Yaobin ; Tian, Renran

File Language:

English

Details

Creators:

Li, Lingxi ; Chen, Yaobin ; Tian, Renran ; Li, Feng
Corporate Creators:

Purdue University. Joint Transportation Research Program
Corporate Contributors:

Indiana. Dept. of Transportation ; United States. Department of Transportation. Federal Highway Administration
Subject/TRT Terms:
Publication/ Report Number:

FHWA/IN/JTRP-2019/24
DOI:

https://doi.org/10.5703/1288284317102
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

Purdue University. Joint Transportation Research Program
Abstract:

Back-of-queue crashes are one of the main sources for fatal accidents on U.S. highways. A variety of factors including low visibility, slippery road surface, and driver distraction/drowsiness during highway cruising, all contribute to this type of fatal crashes. Thus, it is very important to improve the driver’s situational awareness before they approach traffic queues on highways. In this project, we develop a prototype in-vehicle back-of-queue alerting system that is based on the probe vehicle data from INDOT. Speed changes among different road segments are used to identify slow traffic queues, which are compared with vehicle locations and moving directions to detect potential back-of-queue crashes. This prototype system is designed to issue alerting messages to drivers approaching the highway traffic queues via an Android-based smartphone app and an Android Auto device. The performance of this system has been evaluated using the driving simulator and a limited number of on-road test runs. The results showed the effectiveness and benefits of this prototype system.
Format:

PDF
Funding:

SPR-4306
Download URL:

https://rosap.ntl.bts.gov/view/dot/54692/dot_54692_DS1.pdf
File Type:

[PDF - 2.11 MB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:c2d58ed2eface730d99ed29a357b26d22fba587581276e3bb586139b810c94f4

File Language:

English

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