A decision-making system for traffic management during large-scale road network construction

Abstract

As urban development progresses, large-scale road network construction projects are often required to upgrade key infrastructure. However, such projects pose significant traffic management challenges, including reduced network capacity and increased travel delays. To address these issues, this study proposes an end-to-end decision-making system for managing traffic during large-scale construction. The system consists of three key components: (1) a traffic state modeling module based on the user equilibrium traffic assignment model, which estimates pre-construction traffic conditions; (2) an origin-destination (OD) matrix calibration module using a bi-level optimization model and a gradient-descent-based algorithm, which aligns modeled flows with observed data to improve accuracy by 40 %; and (3) a traffic management strategy module that simulates construction-period scenarios and evaluates mitigation strategies. The system is applied to the Pinglu Canal bridge reconstruction project in Qinzhou, China. The results show that a lane-addition strategy, recommended by the system, can reduce the average peak-hour travel delay per commuter from 6.57 to 5.82 min, achieving an 11.42 % improvement. The proposed system serves as a practical decision-support tool for managing traffic during complex, large-scale infrastructure projects.