Applications
Optimal Scheduling of Road Maintenance Jobs Considering Impact on Traffic Flows
arXiv:2608.14491v1 Announce Type: cross Abstract: Network-level maintenance planning requires repeated evaluations of equilibrium traffic flows under road capacity reductions. While equilibrium traffi
arXiv:2608.14491v1 Announce Type: cross Abstract: Network-level maintenance planning requires repeated evaluations of equilibrium traffic flows under road capacity reductions. While equilibrium traffic assignment models are well established, their repeated solution quickly becomes computationally prohibitive and challenging to embed within maintenance scheduling problems. This paper investigates data-driven surrogate models that approximate equilibrium arc flows directly from origin-destination demand, using optimization-based equilibrium solutions as ground truth. A real-world case study based on traffic data from the Newark, New Jersey area demonstrates the effectiveness of the proposed approach as a scalable building block for future maintenance scheduling frameworks.
Related
- Calibrating Urban Traffic Simulation from Sparse Road Observations via Genetic Optimization
- A2TTA: Anchored-and-Agile Test-Time Adaptation for Evolving Traffic Sensor Networks
- Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation
- PedNStream: Scalable Network Flow Simulation for Pedestrian Traffic Management
Source: arXiv cs.AI | 2026-08-17