An Optimization Model for Arterial Coordination Control Based on Sampled Vehicle Trajectories: Stream Model

Traditional arterial coordination control models adopt aggregated demand from fixed detectors or manual counts as main input, which lacks a self-feedback mechanism between the input and the optimization objective. With the population of connected vehicles and intelligent mobility, high-resolution trajectory data provide new possibilities for signal control evaluation and optimization. Therefore, the objective of this study is to propose a new arterial coordination control model for two-way arterial progression solely using sampled trajectories. Sampled trajectories are first used to extract prior arrival information and queuing states. Then, vehicle arrival time at the stop-line at each intersection is estimated as the function of signal timing parameters and prior arrival rates based on the shockwave theory, considering different sampled trajectory statuses. The delay of each sample vehicle is thus obtained as the difference between the actual arrival time and the projected arrival time. Sum of the delays of all the sampled trajectories at each intersection is selected to be the optimization objective, and the optimization problem is solved through a multi-sub-swarm Particle Swarm Optimization (PSO) algorithm. A simulation model is built to test the performance of the proposed model compared with the Synchro model and the MULTIBAND model under various demand scenarios. Results show that the performance of the proposed method is about 21% better than the Synchro model and 14% worse than the MULTIBAND model. This work demonstrates that the optimization of fixed-time arterial coordination control solely using sample trajectories is feasible, and a satisfactory performance can be expected as well.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Yao, Jiarong
  • Tan, Chaopeng
  • Tang, Keshuang
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 7p

Subject/Index Terms

• TRT Terms: Arterial highways; Connected vehicles; Intelligent vehicles; Optimization; Simulation; Traffic models; Traffic signal control systems; Trajectory
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01698308
• Record Type: Publication
• Report/Paper Numbers: 19-02679
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:51PM