Comparative Evaluation of Benefits from Traffic Signal Retiming and Green Light Optimized Speed Advisory Systems

摘要

One of the ways to reduce excessive stop-and-go driving on urban streets is to optimize signaltimings. More recently new methods in traffic signal optimization have incorporated changes indrivers’ behavior to achieve optimum performance at signalized intersections. One suchapplication is called GLOSA - Green Light Optimized Speed Advisory. GLOSA is a method thatuses traffic signal information to provide drivers (through infrastructure-to-vehiclecommunication) with speed advice for a more uniform commute with less stopping time throughtraffic signals. Recent results showed that a GLOSA system works efficiently only if exactdurations of signal phases are known. Objective of this paper is to further evaluate performanceof a GLOSA system in real-world-like conditions. Could GLOSA and similar speed-advisorymethods replace a need for retiming traffic signals? This paper attempts to answer this questionby applying a GLOSA approach on a set of (optimal and suboptimal) signal timings from anurban corridor in Salt Lake City, UT. A VISSIM model of a 5-intersection corridor, calibratedand validated with field data, is used to test two types of signal timings: fixed and actuated. Thefield signal timings from the case-study corridor are optimized by VISGAOST, a GeneticAlgorithm Stochastic Optimization tool based on VISSIM evaluations. The results suggest thatthe GLOSA does not have an equal effect on traffic with fixed-time and actuated-coordinatedsignal timings, where the latter ones are collected as averages from historic records andembedded into the GLOSA algorithm. If the phase durations are predictable, as with fixed-timesignal timings, then GLOSA has a significantly positive effect on number of stops and fuelconsumption. However, if accurate signal timings are not known then it is likely that GLOSAwill not bring a positive impact on traffic performance.