A Data-Driven Control Strategy for Urban Express Ramp

Area of Science:

• Intelligent Transportation Systems
• Traffic Engineering
• Networked Control Systems

Background:

• Urban expressways are critical for traffic flow but face increasing safety and congestion issues due to inadequate traffic control.
• Intelligent network technology offers a promising solution for optimizing expressway traffic management.

Purpose of the Study:

• To develop a data-driven ramp control model for urban expressways.
• To implement and evaluate a cooperative control strategy integrating variable speed limits (VSL) and ramp metering (RM) within an intelligent network environment.

Main Methods:

• Construction of a data-driven ramp control model for urban expressways.
• Utilization of intelligent network technology for traffic information interaction.
• Adoption of a cooperative control strategy combining VSL and RM, with mutual feedback based on an improved METANET model.
• Simulation experiments using VISSIM secondary development for validation.

Main Results:

• The collaborative control strategy significantly reduced vehicle travel time by 20.59%.
• The speed difference between adjacent expressway mainline sections decreased by 34.07%.
• Demonstrated coordinated control between the expressway mainline and on-ramps under an intelligent network environment.

Conclusions:

• The intelligent network-based collaborative control strategy effectively alleviates expressway traffic congestion.
• The proposed model enhances traffic pressure reduction and improves overall road network efficiency.
• This approach provides a viable solution for optimizing urban expressway operations through intelligent control.