01660501

Component

This research presents a signal control strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method (TOAD). TOAD provides an optimal trajectory for automated vehicles while maintaining safe and uninterrupted movement of general traffic, consisting of regular unequipped vehicles. Signal status parameters such as cycle length and splits are continuously captured. At the same time vehicles share their position information with the control agent. Both inputs are then used by the control algorithm to provide optimal trajectories for automated vehicles resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. To determine the most efficient trajectory for automated vehicles an evolutionary-based optimization is utilized. The concept was evaluated using microsimulation in PTV VISSIM. The results for selected signalized corridor in Princeton, New Jersey indicate up to 18 % reduction in overall corridor travel time depending on different market penetration and lane configuration scenario.

This paper was sponsored by TRB committee AHB15 Standing Committee on Intelligent Transportation Systems.

18-03544

English

19p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Maps; References; Tables

Algorithms; Intelligent vehicles; Market penetration; Microsimulation; Optimization; Signalization; Traffic delays; Travel time; Vehicle trajectories

Princeton (New Jersey)

Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-03544

TRIS, TRB, ATRI

Jan 8 2018 10:53AM