Utilizing street-view video sequences for constructing time-space diagrams offers valuable insights into traffic patterns and transportation infrastructure design.
Deep learning with CNN-LSTM architecture enhances traffic flow prediction using cellular automata-based models.
Estimating traffic demands and paths in road networks using Dynamic Programming.
Designing an incentive-compatible vertiport reservation mechanism for efficient coordination in advanced air mobility.
Optical flow technique improves moving object detection and tracking for autonomous vehicles.
Optimizing car parking allocation on university campuses.
Proposing a new approach using genetic programming for efficient and explainable traffic signal control.
Reinforcement learning improves safety, efficiency, and stability in mixed traffic.
Efficient traffic management is crucial for the operation of on-demand urban air mobility systems, maximizing throughput and reducing passenger waiting times.
Developing efficient algorithms for vehicle routing with time-dependent travel times is crucial for optimizing real-world routing problems.