Architecture and key technologies of integrated guidance and control systems for expressways

Abstract

Expressway congestion at bottlenecks and merge areas continues to cause delays, energy waste, and safety risks. This study aims to overcome the fragmented operation of guidance measures and control measures by developing an integrated guidance-and-control framework for expressway traffic management. A three-layer Perception–Decision–Execution architecture is proposed to coordinate VMS route guidance, VSL, and ramp metering through shared traffic-state feedback. Methodologically, a METANET-based macroscopic simulation model is constructed, in which a logit-based probabilistic route choice model is used to estimate driver diversion behavior from perceived travel-time differences, while feedback VSL and ALINEA ramp-metering controllers regulate mainline speed and on-ramp inflow. Three demand scenarios and four strategies, including no control, control only, guidance only, and integrated guidance and control, are compared. The results show that the integrated strategy achieves the best performance in all scenarios, reducing total travel time by 32.0%–74.1% relative to no control and improving high-demand average speed from 19.1 to 85.2 km/h. These findings indicate that coordinated demand diversion and flow regulation can improve expressway efficiency and support practical active traffic management.