Investigating the Effect of Connected Vehicles (CV) Route Guidance on Mobility and Equity
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Author/Creator ORCID
Date
2022-02-25
Type of Work
Department
Urban Mobility & Equity Center/National Transportation Center
Program
Citation of Original Publication
Rights
Public Domain Mark 1.0
Abstract
Traffic 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 chart