DYNAMIC RIGHT-OF-WAY FOR TRANSIT VEHICLES: INTEGRATED MODELING APPROACH FOR OPTIMIZING SIGNAL CONTROL ON MIXED TRAFFIC ARTERIALS
operations - coordination, operations - traffic, infrastructure - vehicle, infrastructure - bus/tram priority, infrastructure - bus/tram priority, infrastructure - traffic signals, ridership - commuting, mode - bus
Traffic signal networks, Traffic signal coordination, Traffic signal control systems, Traffic flow, Traffic delay, Synchronization (Traffic signals), Optimization, Optimisation, Neural networks, Minimization, Minimisation, Linked signals, Interconnection (Traffic signals), Integrated models, Innovation, Genetic algorithms, Dynamic right-of-way, Computer controlled signals, Bus priority, Automatic traffic signal control, Artificial neural networks, ANNs (Artificial neural networks)
Public transit and general traffic on many urban arterials are controlled by the same set of signals and must compete for shared road space. In these situations, transit vehicles typically face considerable delays because their dwell times at transit stops remove them from the coordinated green wave for general traffic flow. Although existing control systems allow for local adjustments of signal timings to provide transit priority, these short-term actions often contradict the network control scheme and may preclude a priority scheme or significantly disrupt traffic flow. A new concept for a corridor control system is introduced--the dynamic right-of-way, which serves the demands of public transit and general traffic using an integrated model for evaluation and optimization. The control system is intended to (a) reduce critical interferences between both modes of transport by dynamically controlling inflow and outflow for all network links, (b) provide a green signal whenever a transit vehicle approaches an intersection, and (c) minimize general traffic disruption by maintaining overall signal coordination. Through linking an event-based simulator with a genetic algorithm-based optimization routine, delay-minimizing multicycle signal control schemes are calculated. In offline experiments, the potential for achieving substantial reductions in delays is demonstrated. Finally, a method is presented by which these control schemes are implemented and adjusted dynamically, based on online measurements and a control modification function derived from a neural network model.
Duerr, P. (2000). DYNAMIC RIGHT-OF-WAY FOR TRANSIT VEHICLES: INTEGRATED MODELING APPROACH FOR OPTIMIZING SIGNAL CONTROL ON MIXED TRAFFIC ARTERIALS. Transportation Research Record, 1731, p. 31-39.