Investigating the Effect of Connected Vehicles (CV) Route Guidance on Mobility and Equity

dc.contributor.authorJeihani, Mansoureh
dc.contributor.authorAnsariyar, Alireza
dc.contributor.authorSadeghvaziri, Eazaz
dc.contributor.authorArdeshiri, Anam
dc.contributor.authorKabir, Md Muhib
dc.contributor.authorHaghani, Ali
dc.contributor.authorJones, Anita
dc.contributor.departmentUrban Mobility & Equity Center/National Transportation Centeren_US
dc.date.accessioned2024-05-01T19:38:28Z
dc.date.available2024-05-01T19:38:28Z
dc.date.issued2022-02-25
dc.description.abstractTraffic congestion is a serious and increasing national problem, especially for urban commuters. Providing accurate real-time traffic information is a key tool to reduce congestion. Recent studies have shown that connected vehicles (CVs) can help improve traffic mobility and safety while saving energy and reducing emissions. The research initially evaluates the gradual deployment of CVs and their effect on mobility, energy consumption, and the amount of pollutants. Then, our research investigates the CV guidance system as an emerging form of dynamic route guidance. This research develops and calibrates a microscopic traffic simulation model to replicate the fairly realistic behavior of such vehicles in the traffic simulation environment. Unlike the majority of prior studies that used hypothetical study areas with simple networks, this study develops a real-world medium urban road network. Different penetration rates of CVs (0%-100%) are developed, and the system-wide effects of CV equipped vehicles with route guidance features on mobility and equity are analyzed. The results showed that as the market penetration rate (MPR) of CVs increases, traffic parameters (e.g., total delay time), total emissions, and average travel time of re-routing paths decreases. In order to find the effects of new traffic reduction policies for mass public transportation systems, dynamic CV bus lanes were suggested. The results showed that increasing the service time of a dynamic CV bus lane may improve average travel time for CV buses, but it negatively affects the average travel time of non-CV and CV cars. Finally, a network-wide average travel time analysis is proposed. Based on the proposed methodology, 85% MPR was determined as a critical breakpoint of the network-wide weighted average travel time chart. The results of network-wide equity analysis highlighted that, as the MPR of CVs increases, the percentage of critical breakpoint decreases, and that point shifts to the left of the charten_US
dc.description.sponsorshipUS Department of Transportation Office of the Secretary-Researchen_US
dc.description.urihttps://www.morgan.edu/Documents/ACADEMIA/CENTERS/ntc/umec/Investigating%20the%20Effect%20of%20CV_Finalv2.pdf
dc.format.extent90 pagesen_US
dc.genreFinal reporten_US
dc.identifierdoi:10.13016/m2xeft-mzus
dc.identifier.urihttp://hdl.handle.net/11603/33573
dc.language.isoen_USen_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.subjectConnected Vehicle, Route Guidance, Travel Time, multimodal transport, Equity, Market Penetration Rate of Cen_US
dc.titleInvestigating the Effect of Connected Vehicles (CV) Route Guidance on Mobility and Equityen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0001-8052-6931en_US

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