Fig 1.
Intelligent networked adaptive signal control for pedestrian crossing.
Fig 2.
Deep reinforcement learning process.
Fig 3.
EXP-DDQN algorithm framework.
Fig 4.
Simulated road network.
Fig 5.
Phase timing and signal timing of four-way intersections.
Fig 6.
Phase timing and signal timing of three-way intersections.
Table 1.
EXP-DDQN algorithm.
Table 2.
Parameter configuration for deep reinforcement learning algorithm.
Fig 7.
Cumulative reward variations at different CAV penetration rates.
Table 3.
Comparison of metrics across different methods.
Fig 8.
Comparison of conflict frequency across different algorithms.
Fig 9.
Comparison of average vehicle delay across different algorithms.
Fig 10.
Comparison of queue length across different algorithms.
Fig 11.
Comparison of pedestrian waiting time using different algorithms.