Advanced Traffic Signal Control Algorithms

Advanced signal control strategies, based on real-time information on vehicles’ location, speed and characteristics as well as communication to the signal control infrastructure, can enhance mobility, safety, and the environment. Several performance measures are proposed for evaluating signal control algorithms, and procedures for estimating the performance measures from connected vehicle data are developed using statistical techniques and kinematic wave theory. A number of control strategies are developed and tested through simulation to improve mobility: queue spillback avoidance, control for congested networks, and dynamic lane allocation. Results indicate that the proposed strategies improve traffic performance. Strategies for improving intersection safety with emphasis on avoidance of red light running (RLR) related collisions are also developed. A prototype in-vehicle driver speed advisory system for minimum fuel consumption and emissions is developed and field tests show significant fuel savings.

• Record URL:
  https://dot.ca.gov/-/media/dot-media/programs/research-innovation-system-information/documents/final-reports/ca13-2157a-finalreport-a11y.pdf
• Record URL:
  https://merritt.cdlib.org/api/presign-file/ark%253A%252F13030%252Fm5nc7fc1/3/producer%252FCA13-2157-A.pdf
• 
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/884613548
• Supplemental Notes:
  • Caltrans version of this report has incorrect report number (UCB-ITS-PRR-2013-XX).
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  California Department of Transportation

  Division of Research and Innovation
  1227 O Street, MS-83
  Sacramento, CA  United States  94273-0001

  BMW Group

  Department of Science and Traffic Policy/Traffic Technology
  Max-Diamand Strasse 13
  Munich,   Germany  80937

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590

  University of California, Riverside

  Center for Environmental Research and Technology
  900 University Avenue
  Riverside, CA  United States  92521-0425
• Authors:
  • Skabardonis, Alexander
  • Shladover, Steven
  • Zhang, Wei-bin
  • Zhang, Liping
  • Li, Jing-Quan
  • Zhou, Kun
  • Argote, Juan
  • Barth, Matthew
  • Boriboonsomsin, Kanok
  • 0000-0003-2558-5343
  • Xia, Haitao
  • Winckler, Andreas
  • Liccardo, Darren S
• Publication Date: 2013-9

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; References; Tables;
• Pagination: 123p
• Serial:
  • PATH Research Report
  • Publisher: University of California, Berkeley
  • ISSN: 1055-1425

Subject/Index Terms

• TRT Terms: Adaptive control; Algorithms; Fuel consumption; Mathematical models; Measures of effectiveness; Microsimulation; Red light running; Traffic congestion; Traffic signal control systems; Vehicle to vehicle communications
• Geographic Terms: Berkeley (California); Houston (Texas)
• Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01539294
• Record Type: Publication
• Report/Paper Numbers: CA13-2157-A, UCB-ITS-PRR-2014-4
• Contract Numbers: 65A0376
• Files: CALTRANS, TRIS, ATRI, STATEDOT
• Created Date: Sep 26 2014 2:42PM