An Eco-Driving Advisory System for Continuous Signalized Intersections by Vehicular Ad Hoc Network

Wei Hsun Lee, Jiang Yi Li

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

With the vehicular ad hoc network (VANET) technology which support vehicle-to-vehicle (V2V) and vehicle to road side unit (V2R/R2V) communications, vehicles can preview the intersection signal plan such as signal countdown message. In this paper, an ecodriving advisory system (EDAS) is proposed to reduce CO2 emissions and energy consumption by letting the vehicle continuously pass through multiple intersections with the minimum possibilities of stops. We extend the isolated intersection model to multiple continuous intersections scenario. A hybrid method combining three strategies including maximized throughput model (MTM), smooth speed model (SSM), and minimized acceleration and deceleration (MinADM) is designed, and it is compared with related works maximized throughput model (MaxTM), open traffic light control model (OTLCM), and predictive cruise control (PCC) models. Some issues for the practical application including safe car following, queue clearing, and gliding mode are discussed and conquered. Simulation results show that the proposed model outperforms OTLCM 25.1%81.2% in the isolated intersection scenario for the CO2 emissions and 20.5%84.3% in averaged travel time. It also performs better than the compared PCC model in CO2 emissions (19.9%31.2%) as well as travel time (24.5%35.9%) in the multiple intersections scenario.

Original languageEnglish
Article number5060481
JournalJournal of Advanced Transportation
Volume2018
DOIs
Publication statusPublished - 2018 Jan 1

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All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management

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