DeCoR co-optimizes crosswalk placement and signal control via reinforcement learning on a real 750 m urban corridor, reporting 23% faster pedestrian access to crossings and 79%/65% reductions in pedestrian/vehicle wait times versus fixed-time baselines.
IEEE transactions on intelligent transportation systems24(2), 2024–2034 (2022)
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DeCoR: Design and Control Co-Optimization for Urban Streets Using Reinforcement Learning
DeCoR co-optimizes crosswalk placement and signal control via reinforcement learning on a real 750 m urban corridor, reporting 23% faster pedestrian access to crossings and 79%/65% reductions in pedestrian/vehicle wait times versus fixed-time baselines.