Abstract

Road Transportation is a crucial component of today's society, which drives several facets of our lives. The goal of intelligent transportation systems (ITS) is to improve the effectiveness, efficiency, and safety of the transportation system. Traffic signals are an elementary component of all road transportation systems. In order to maximize the productivity of a city, traffic signals must be able to efficiently control the flow of vehicles. Traditionally, current traffic signal optimization is based on traffic arrival rates, either estimated or forecasted. In this paper, we illustrate that arrival time-based solutions can outperform arrival rate-based approaches. To the best of our knowledge, this is the first work that exploits arrival times of vehicles to improve traffic signal efficiency in order to reduce stopped delays and fuel consumptions, thus in turn reducing greenhouse gases and emissions. We show that arrival time knowledge can be utilized in realizing drastic gains in sparse load scenarios and significant gains in moderate load scenarios. The performance improvement translates to reducing stopped delays by over 40,000 hours daily and in reducing fuel consumption by over 650 gallons/signal/day. © 2013 IEEE.

Department(s)

Computer Science

Comments

National Science Foundation, Grant 1205695

Keywords and Phrases

Optimization; Scheduling; Traffic signals; Vehicular networks

International Standard Book Number (ISBN)

978-076954953-8

International Standard Serial Number (ISSN)

1550-445X

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

08 Aug 2013

Download

Full Text Link

Share

 
COinS