Connected vehicle-based adaptive signal control and applications

Yiheng Feng, Mehdi Zamanipour, Kenneth L Head, Shayan Khoshmagham

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Basic signal operation strategies allocate green time to different traffic movements to control the flow at an intersection. Signal control applications consider different objectives, such as coordination with multiple intersections, multimodal priority, and safety. Real-time signal control applications rely mainly on infrastructure-based detection data. With the emergence of connected vehicle technology, high-resolution data from connected vehicles will become available for signal control. This paper presents a framework that uses connected vehicle data for adaptive signal control and considers dilemma zone protection, multimodal signal priority, and coordination. Initially, the market penetration rate of connected vehicles will be low, so infrastructure-based detector actuation logic is integrated into the framework to improve performance. Simulation analysis demonstrated good results when the penetration rate was medium to high and that the actuation logic was necessary when the penetration rate was low.

Original languageEnglish (US)
Pages (from-to)11-19
Number of pages9
JournalTransportation Research Record
Volume2558
DOIs
StatePublished - 2016

Fingerprint

Detectors

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

Cite this

Connected vehicle-based adaptive signal control and applications. / Feng, Yiheng; Zamanipour, Mehdi; Head, Kenneth L; Khoshmagham, Shayan.

In: Transportation Research Record, Vol. 2558, 2016, p. 11-19.

Research output: Contribution to journalArticle

Feng, Yiheng ; Zamanipour, Mehdi ; Head, Kenneth L ; Khoshmagham, Shayan. / Connected vehicle-based adaptive signal control and applications. In: Transportation Research Record. 2016 ; Vol. 2558. pp. 11-19.
@article{711615bae0a348c5aa8470d8cf7444e6,
title = "Connected vehicle-based adaptive signal control and applications",
abstract = "Basic signal operation strategies allocate green time to different traffic movements to control the flow at an intersection. Signal control applications consider different objectives, such as coordination with multiple intersections, multimodal priority, and safety. Real-time signal control applications rely mainly on infrastructure-based detection data. With the emergence of connected vehicle technology, high-resolution data from connected vehicles will become available for signal control. This paper presents a framework that uses connected vehicle data for adaptive signal control and considers dilemma zone protection, multimodal signal priority, and coordination. Initially, the market penetration rate of connected vehicles will be low, so infrastructure-based detector actuation logic is integrated into the framework to improve performance. Simulation analysis demonstrated good results when the penetration rate was medium to high and that the actuation logic was necessary when the penetration rate was low.",
author = "Yiheng Feng and Mehdi Zamanipour and Head, {Kenneth L} and Shayan Khoshmagham",
year = "2016",
doi = "10.3141/2558-02",
language = "English (US)",
volume = "2558",
pages = "11--19",
journal = "Transportation Research Record",
issn = "0361-1981",
publisher = "US National Research Council",

}

TY - JOUR

T1 - Connected vehicle-based adaptive signal control and applications

AU - Feng, Yiheng

AU - Zamanipour, Mehdi

AU - Head, Kenneth L

AU - Khoshmagham, Shayan

PY - 2016

Y1 - 2016

N2 - Basic signal operation strategies allocate green time to different traffic movements to control the flow at an intersection. Signal control applications consider different objectives, such as coordination with multiple intersections, multimodal priority, and safety. Real-time signal control applications rely mainly on infrastructure-based detection data. With the emergence of connected vehicle technology, high-resolution data from connected vehicles will become available for signal control. This paper presents a framework that uses connected vehicle data for adaptive signal control and considers dilemma zone protection, multimodal signal priority, and coordination. Initially, the market penetration rate of connected vehicles will be low, so infrastructure-based detector actuation logic is integrated into the framework to improve performance. Simulation analysis demonstrated good results when the penetration rate was medium to high and that the actuation logic was necessary when the penetration rate was low.

AB - Basic signal operation strategies allocate green time to different traffic movements to control the flow at an intersection. Signal control applications consider different objectives, such as coordination with multiple intersections, multimodal priority, and safety. Real-time signal control applications rely mainly on infrastructure-based detection data. With the emergence of connected vehicle technology, high-resolution data from connected vehicles will become available for signal control. This paper presents a framework that uses connected vehicle data for adaptive signal control and considers dilemma zone protection, multimodal signal priority, and coordination. Initially, the market penetration rate of connected vehicles will be low, so infrastructure-based detector actuation logic is integrated into the framework to improve performance. Simulation analysis demonstrated good results when the penetration rate was medium to high and that the actuation logic was necessary when the penetration rate was low.

UR - http://www.scopus.com/inward/record.url?scp=85015428036&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015428036&partnerID=8YFLogxK

U2 - 10.3141/2558-02

DO - 10.3141/2558-02

M3 - Article

VL - 2558

SP - 11

EP - 19

JO - Transportation Research Record

JF - Transportation Research Record

SN - 0361-1981

ER -