Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: Theoretical analysis with generalized time geography

This paper studies a problem of designing trajectories of a platoon of vehicles on a highway segment with advanced connected and automated vehicle technologies. This problem is very complex because each vehicle trajectory is essentially an infinite-dimensional object and neighboring trajectories have complex interactions (e.g., car-following behavior). A parsimonious shooting heuristic algorithm is proposed to construct vehicle trajectories on a signalized highway segment that comply with boundary conditions for vehicle arrivals, vehicle mechanical limits, traffic lights and vehicle following safety. This algorithm breaks each vehicle trajectory into a few sections that are analytically solvable. This decomposes the originally hard trajectory design problem to a simple constructive heuristic. Then the authors slightly adapt this shooting heuristic algorithm to efficiently solve a leading vehicle problem on an uninterrupted freeway. To study theoretical properties of the proposed algorithms, the time geography theory is generalized by considering finite accelerations. With this generalized theory, it is found that under mild conditions, these algorithms can always obtain a feasible solution to the original complex trajectory design problem. Further, the authors discover that the shooting heuristic solution is a generalization of the solution to the classic kinematic wave theory by incorporating finite accelerations. The authors identify the theoretical bounds to the difference between the shooting heuristic solution and the kinematic wave solution. Numerical experiments are conducted to verify the theoretical results and to draw additional managerial insights into the potential of trajectory design in improving traffic performance. In summary, this paper provides a methodological and theoretical foundation for advanced traffic control by optimizing the trajectories of connected and automated vehicles. Building upon this foundation, an optimization framework will be presented in a following paper as Part II of this study.

• Record URL:
  https://doi.org/10.1016/j.trb.2016.05.007
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261515301806
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhou, Fang
  • Li, Xiaopeng (Shaw)
  • 0000-0002-5264-3775
  • Ma, Jiaqi
  • 0000-0002-8184-5157
• Publication Date: 2017-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 394-420
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 95
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Algorithms; Automated highways; Heuristic methods; Highway traffic control systems; Intelligent vehicles; Mobile communication systems; Theory; Trajectory
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01626035
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 15 2017 5:03PM