Red-Light-Running (RLR) is the leading cause of urban crashes. This report presents the findings from an investigation of signal control-related countermeasures to reduce the occurrences of RLR and related collisions. The objectives of this study were to identify and evaluate potential modifications to signal timing schemes in reducing the frequency of RLR and to develop online adaptive RLR collision avoidance algorithms to reduce the possibility of RLR collisions. High quality, second-by-second vehicle count and signal timing and phasing data were collected at arterial intersections. A signal-cycle-based data analysis was performed to determine RLR contributing factors that are statistic significant, having substantial impact on RLR and controllable via signal timing modifications. These findings were then applied to develop signal timing schemes that aim to increase the probability of stopping and online signal timing adaptation strategies to avoid potential collision when RLR occurs. We demonstrate the effectiveness of signal timing modifications in reducing RLR while maintaining intersections' level of service, under both microscopic simulation and macroscopic simulation environments. In addition, an investigation of drivers' decision making at signalized intersections using real world data and a probabilistic RLR prediction model are presented. (Author/publisher)
Abstract