Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment

Bin Yu, Miyi Wu, Shuyi Wang and Wen Zhou
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Bin Yu: School of Transportation, Southeast University, Nanjing 211189, China
Miyi Wu: School of Transportation, Southeast University, Nanjing 211189, China
Shuyi Wang: School of Transportation, Southeast University, Nanjing 211189, China
Wen Zhou: School of Transportation, Southeast University, Nanjing 211189, China

IJERPH, 2019, vol. 16, issue 22, 1-15

Abstract: Connected vehicles (CVs) exchange a variety of information instantly with surrounding vehicles and traffic facilities, which could smooth traffic flow significantly. The objective of this paper is to analyze the effect of CVs on running speed. This study compared the delay time, travel time, and running speed in the normal and the connected states, respectively, through VISSIM (a traffic simulation software developed by PTV company in German). The optimization speed model was established to simulate the decision-makings of CVs in MATLAB, considering the parameters of vehicle distance, average speed, and acceleration, etc. After the simulation, the vehicle information including speed, travel time, and delay time under the normal and the connected states were compared and evaluated, and the influence of different CV rates on the results was analyzed. In a two-lane arterial road, running speed in the connected state increase by 4 km/h, and the total travel time and delay time decrease by 5.34% and 16.76%, respectively, compared to those in the normal state. The optimal CV market penetration rate related to running speed and delay time is 60%. This simulation-based study applies user-defined lane change and lateral behavior rules, and takes different CV rates into consideration, which is more reliable and practical to estimate the impact of CV on road traffic characteristics.

Keywords: connected vehicles; optimization speed model; VISSIM; running speed (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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