A bi-level dynamic emergency route planning system considering signal preemption control using CV technology

Area of Science:

• Intelligent Transportation Systems (ITS)
• Traffic Engineering
• Control Systems

Background:

• Emergency vehicles (EVs) require efficient routing and traffic signal priority for timely response.
• Connected vehicle (CV) technology offers potential for optimizing EV operations and traffic flow.
• Dynamic traffic conditions necessitate adaptive planning for emergency response.

Purpose of the Study:

• To develop a bi-level dynamic emergency route planning system for multiple EVs in a partial CV environment.
• To integrate signal preemption control with route planning for enhanced EV efficiency and reduced traffic disruption.
• To prioritize EV mobility while minimizing the impact on general traffic flow.

Main Methods:

• A hierarchical bi-layer model predictive control (MPC) framework was employed.
• The upper layer dynamically plans road-level routes based on network-wide traffic flow estimation and CV data (loop detectors, C-V2X).
• The lower layer plans lane-level routes incorporating signal preemption control.

Main Results:

• The proposed system demonstrated reliable and practical emergency route planning and signal control.
• Effectiveness was validated through microscopic simulations in a real traffic network.
• The system successfully balanced EV prioritization with minimizing adverse effects on normal traffic.

Conclusions:

• The bi-level dynamic system effectively enhances emergency vehicle operations.
• Integration of CV technology and MPC is crucial for adaptive traffic management.
• The approach provides a robust solution for emergency response in complex traffic environments.