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Expanding the capabilities of existing vehicle detection infrastructure to monitor red light running

Author

Listed:
  • Kelvin R. Santiago-Chaparro
  • Madhav Chitturi
  • Andrea Bill
  • David A. Noyce

Abstract

Understanding the red light running (RLR) at signalised intersections is useful when establishing enforcement programs and safety countermeasures. Unfortunately, acquiring RLR information requires the use of dedicated hardware or time-consuming manual data collection. This paper presents a software-based methodology that monitors the underlying dataset of existing radar-based vehicle detection infrastructure to continuously monitor RLR incidents. Through the use of custom software the trajectories of vehicles approaching an intersection were logged and combined with signal status information. By analysing the position of vehicles and signal status RLR incidents were detected. Statistics computed include the number of red light runners by hour of the day and a characterisation of their behaviour. This research is of interest to enforcement professionals, engineers, managers, and those dealing with budgetary issues since the concepts presented can be applied to obtain critical safety data without the need for new infrastructure investments.

Suggested Citation

  • Kelvin R. Santiago-Chaparro & Madhav Chitturi & Andrea Bill & David A. Noyce, 2015. "Expanding the capabilities of existing vehicle detection infrastructure to monitor red light running," International Journal of Engineering Management and Economics, Inderscience Enterprises Ltd, vol. 5(3/4), pages 196-208.
    • Handle: RePEc:ids:ijemec:v:5:y:2015:i:3/4:p:196-208
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