Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Investigating the effects of gradual deployment of market penetration rates (MPR) of connected vehicles on delay time and fuel consumption

Investigating the effects of gradual deployment of market penetration rates (MPR) of connected... This research paper aims to investigate the effects of gradual deployment of market penetration rates (MPR) of connected vehicles (MPR of CVs) on delay time and fuel consumption.Design/methodology/approachA real-world origin-destination demand matrix survey was conducted in Boston, MA to identify the number of peak hour passing vehicles in the case study.FindingsThe results showed that as the number of CVs (MPR) in the network increases, the total delay time decreases by an average of 14% and the fuel consumption decreases by an average of 56%, respectively, from scenarios 3 to 15 compared to scenario 2.Research limitations/implicationsThe first limitation of this study was considering a small network. The considered network shows a small part of the case study.Originality/valueThis study can be a milestone for future research regarding gradual deployment of CVs’ effects on transport networks. Efficient policy(s) may define based on the results of this network for Brockton transport network. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent and Connected Vehicles Emerald Publishing

Investigating the effects of gradual deployment of market penetration rates (MPR) of connected vehicles on delay time and fuel consumption

Download PDF

Investigating the effects of gradual deployment of market penetration rates (MPR) of connected vehicles on delay time and fuel consumption

Ansariyar, Alireza; Tahmasebi, Milad
Journal of Intelligent and Connected Vehicles , Volume 5 (3): 11 – Oct 11, 2022

Abstract

This research paper aims to investigate the effects of gradual deployment of market penetration rates (MPR) of connected vehicles (MPR of CVs) on delay time and fuel consumption.Design/methodology/approachA real-world origin-destination demand matrix survey was conducted in Boston, MA to identify the number of peak hour passing vehicles in the case study.FindingsThe results showed that as the number of CVs (MPR) in the network increases, the total delay time decreases by an average of 14% and the fuel consumption decreases by an average of 56%, respectively, from scenarios 3 to 15 compared to scenario 2.Research limitations/implicationsThe first limitation of this study was considering a small network. The considered network shows a small part of the case study.Originality/valueThis study can be a milestone for future research regarding gradual deployment of CVs’ effects on transport networks. Efficient policy(s) may define based on the results of this network for Brockton transport network.

Loading next page...
 
/lp/emerald-publishing/investigating-the-effects-of-gradual-deployment-of-market-penetration-mwqVU4ehPK
Publisher
Emerald Publishing
Copyright
© Alireza Ansariyar and Milad Tahmasebi.
ISSN
2399-9802
DOI
10.1108/jicv-12-2021-0018
Publisher site
See Article on Publisher Site

Abstract

This research paper aims to investigate the effects of gradual deployment of market penetration rates (MPR) of connected vehicles (MPR of CVs) on delay time and fuel consumption.Design/methodology/approachA real-world origin-destination demand matrix survey was conducted in Boston, MA to identify the number of peak hour passing vehicles in the case study.FindingsThe results showed that as the number of CVs (MPR) in the network increases, the total delay time decreases by an average of 14% and the fuel consumption decreases by an average of 56%, respectively, from scenarios 3 to 15 compared to scenario 2.Research limitations/implicationsThe first limitation of this study was considering a small network. The considered network shows a small part of the case study.Originality/valueThis study can be a milestone for future research regarding gradual deployment of CVs’ effects on transport networks. Efficient policy(s) may define based on the results of this network for Brockton transport network.

Journal

Journal of Intelligent and Connected Vehicles – Emerald Publishing

Published: Oct 11, 2022

Keywords: Connected vehicles (CVs); V2X module; AIMSUN microsimulation; Market penetration rate of CV; Delay time; Fuel consumption

References

  • User manual
  • Progress in fuel consumption modelling for urban traffic management
    Akçelik, R.
  • Wikipedia website
  • Modeling and simulating urban traffic flow mixed with regular and connected vehicles
    Cao, Z.
  • Model predictive cooperative cruise control in mixed traffic
    Chin, H.; Okuda, H.; Tazaki, Y.; Suzuki, T.
  • Microscopic traffic flow simulator VISSIM. Fundamentals of traffic simulation
    Fellendorf, M.; Vortisch, P.
  • Design of adaptive cruise control for road vehicles using topographic and traffic information
    Gaspar, P.; Nemeth, B.
  • Computer program MULTSIM for simulating output from vehicle detectors on a multi-lane signal controlled road
    Gipps, P.G.
  • A behavioural car-following model for computer simulation
    Gipps, P.G.
  • Traffic signal control with connected vehicles
    Goodall, N.; Smith, B.L.; Park, B.
  • Simulation-based traffic management system for connected and autonomous vehicles
    Gora, P.
  • Microscopic traffic simulation tool for intelligent transportation systems
    Jaworski, P.; Edwards, T.; Burnham, K.J.; Haas, O.C.L.
  • An empirical study of inter-vehicle communication performance using NS-2
    Jung, C.
  • Platoons of connected vehicles can double throughput in urban roads
    Lioris, J.; Pedarsani, R.; Tascikaraoglu, F.; Varaiya, P.
  • Multiple simulator interlinking environment for IVC
    Lochert, C.; Barthels, A.; Cervantes, A.; Mauve, M.; Caliskan, M.
  • Brockton transit lines information
  • A cellular automaton model for freeway traffic
    Nagel, K.; Schreckenberg, M.
  • A multi-vehicle communication system to assess the safety and mobility of connected and automated vehicles
    Rahman, M.; Abdel-Aty, M.; Wu, Y.
  • Dependence of cooperative vehicle system performance on market penetration
    Shladover, S.; Gungor, P.; Raja, S.; Joel, V.; Ergen, M.; Bougler, B.
  • Influence of connected and autonomous vehicles on traffic flow stability and throughput
    Talebpour, A.; Mahmassani, H.
  • Multiregime sequential risk-taking model of car-following behavior
    Talebpour, A.; Mahmassani, H.; Hamdar, S.H.
  • Congested traffic states in empirical observations and microscopic simulations
    Treiber, M.; Hennecke, A.; Helbing, D.
  • Traffic Analysis Toolbox Volume VI: definition, Interpretation, and Calculation of Traffic Analysis Tools Measures of Effectiveness
  • The impact of cooperative adaptive cruise control on traffic-flow characteristics
    Van Arem, B.; Van Driel, C.J.G.; Visser, R.
  • Traffic operations analysis tool guidebook version 1.1
  • Realistic car-following models for microscopic simulation of adaptive and cooperative adaptive cruise control vehicles
    Xiao, L.; Wang, M.; Van Arem, B.
  • Managing connected automated vehicles in mixed traffic considering communication reliability: a platooning strategy
    Yao, S.; Shetb, R.A.; Friedricha, B.
  • The penetration effect of connected automated vehicles in urban traffic: an energy impact study
    Zhang, Y.; Cassandras, C.