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Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment
Most existing signal timing plans are optimized given vehicles’ arrival time (i.e., the time for the upcoming vehicles to arrive at the stop line) as exogenous input. In this paper, based on the connected vehicle (CV) technique, vehicles can be regarded as moving sensors, and their arrival time can...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982858/ https://www.ncbi.nlm.nih.gov/pubmed/31905744 http://dx.doi.org/10.3390/s20010191 |
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author | Wu, Wei Huang, Ling Du, Ronghua |
author_facet | Wu, Wei Huang, Ling Du, Ronghua |
author_sort | Wu, Wei |
collection | PubMed |
description | Most existing signal timing plans are optimized given vehicles’ arrival time (i.e., the time for the upcoming vehicles to arrive at the stop line) as exogenous input. In this paper, based on the connected vehicle (CV) technique, vehicles can be regarded as moving sensors, and their arrival time can be dynamically adjusted by speed guidance according to the current signal status and traffic conditions. Therefore, an integrated traffic control model is proposed in this study to optimize vehicle arrival time (or travel speed) and signal timing simultaneously. “Speed guidance model at a red light” and “speed guidance model at a green light” are presented to model the influences between travel speed and signal timing. Then, the methods to model the vehicle arrival time, vehicle delay, and number of stops are proposed. The total delay, which includes the control delay, queuing delay, and signal delay, is used as the objective of the proposed model. The decision variables consist of vehicle arrival time, starting time of green, and duration of green for each phase. The sliding time window is adopted to dynamically tackle the problems. Compared with the results optimized by the classical actuated signal control method and the fixed-time-based speed guidance model, the proposed model can significantly decrease travel delays as well as improve the flexibility and mobility of traffic control. The sensitivity analysis with the communication distance, the market penetration of connected vehicles, and the compliance rate of speed guidance further demonstrates the potential of the proposed model to be applied in various traffic conditions. |
format | Online Article Text |
id | pubmed-6982858 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69828582020-02-06 Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment Wu, Wei Huang, Ling Du, Ronghua Sensors (Basel) Article Most existing signal timing plans are optimized given vehicles’ arrival time (i.e., the time for the upcoming vehicles to arrive at the stop line) as exogenous input. In this paper, based on the connected vehicle (CV) technique, vehicles can be regarded as moving sensors, and their arrival time can be dynamically adjusted by speed guidance according to the current signal status and traffic conditions. Therefore, an integrated traffic control model is proposed in this study to optimize vehicle arrival time (or travel speed) and signal timing simultaneously. “Speed guidance model at a red light” and “speed guidance model at a green light” are presented to model the influences between travel speed and signal timing. Then, the methods to model the vehicle arrival time, vehicle delay, and number of stops are proposed. The total delay, which includes the control delay, queuing delay, and signal delay, is used as the objective of the proposed model. The decision variables consist of vehicle arrival time, starting time of green, and duration of green for each phase. The sliding time window is adopted to dynamically tackle the problems. Compared with the results optimized by the classical actuated signal control method and the fixed-time-based speed guidance model, the proposed model can significantly decrease travel delays as well as improve the flexibility and mobility of traffic control. The sensitivity analysis with the communication distance, the market penetration of connected vehicles, and the compliance rate of speed guidance further demonstrates the potential of the proposed model to be applied in various traffic conditions. MDPI 2019-12-29 /pmc/articles/PMC6982858/ /pubmed/31905744 http://dx.doi.org/10.3390/s20010191 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wu, Wei Huang, Ling Du, Ronghua Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title | Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title_full | Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title_fullStr | Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title_full_unstemmed | Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title_short | Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment |
title_sort | simultaneous optimization of vehicle arrival time and signal timings within a connected vehicle environment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982858/ https://www.ncbi.nlm.nih.gov/pubmed/31905744 http://dx.doi.org/10.3390/s20010191 |
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