Urban Traffic Signal Control With Connected and Automated Vehicles: A Survey

Details

• Creators:
  Guo, Qiangqiang ; Li, Li ; Ban, Xuegang (Jeff)
• Corporate Creators:
  Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART)
• Subject/TRT Terms:
  • Autonomous vehicles
  • Connected vehicles
  • Highway traffic control
  • Remote sensing
  • Surveys
  • Traffic flow
  • Traffic signal control systems
  • Urban highways Urban Traffic Control (UTC)
  • Connected and Automated Vehicles (CAVs)
  • Mobile Sensing
  More +
• Resource Type:
  Journal Article
• Geographical Coverage:
  United States
• Corporate Publisher:
  Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART)
• Abstract:
  Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we systematically review the potential solutions that take advantage of connected and automated vehicles (CAVs) to improve the control performances of urban signalized intersections. We review the methods and models to estimate traffic flow states and optimize traffic signal timing plans based on CAVs. We summarize six types of CAV-based traffic control methods and propose a conceptual mathematical framework that can be specified to each of six three types of methods by selecting different state variables, control inputs, and environment inputs. The benefits and drawbacks of various CAV-based control methods are explained, and future research directions are discussed. We hope that this review could provide readers with a helpful roadmap for future research on CAV-based urban traffic control and draw their attention to the most challenging problems in this important and promising field.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/42376/dot_42376_DS1.pdf
• File Type:
  [PDF - 1.10 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:acb2a0c457b279a81ad682b68319f2a6700cad9b21ac28c7299488c044577c97813bc0356d2df1bd1ed290792f796c587e2e2a0aee22cfe06cb52f3b505604a9