PAIM: Platoon-based Autonomous Intersection Management
Topics & Keywords
Research Topics:
Keywords:
Key Insights
Introduction of a reservation-based policy for platoon-based intersection management.
Focus on minimizing average delay and variance in vehicle movement.
Utilization of vehicle dynamics modeling for realistic traffic simulations.
Development of a communication protocol for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) interactions.
Comparison of proposed methods with traditional traffic light systems.
Simulation results demonstrate improved intersection throughput and reduced fuel consumption.
Scalability of the proposed solution for varying traffic levels and platoon sizes.
Integration of advanced algorithms to optimize scheduling and reduce computational complexity.
Abstract
With the emergence of autonomous group transportation and advancements in Intelligent Transportation Systems, Autonomous Intersection Management (AIM) has garnered significant attention. AIM addresses critical traffic challenges, including delays, fuel consumption, and safety. This paper introduces a reservation-based policy for platoons of vehicles, ensuring efficient and safe intersection management. The proposed policy minimizes average delay and variance while maintaining safety by avoiding conflicting movements in the conflict zone. The methodology leverages vehicle dynamics modeling and a communication protocol to optimize intersection throughput and fuel consumption.
Methodology
The study employs a reservation-based policy for platoon-based intersection management, supported by vehicle dynamics modeling and a communication protocol. The methodology includes simulations of a 4-way intersection scenario, comparing the proposed policy with traditional traffic light systems. Metrics such as average delay, intersection throughput, and fuel consumption are analyzed. The approach integrates advanced algorithms to optimize scheduling and reduce computational complexity.
Key Findings
- The proposed policy significantly reduces average delay per vehicle compared to traditional traffic light systems.
- Fuel consumption is reduced by 8% on average, demonstrating environmental benefits.
- Intersection throughput is increased by 13% on average, enhancing traffic flow efficiency.
- The policy minimizes variance in delay, ensuring more predictable travel times.
- Scalability of the solution is validated for varying traffic levels and platoon sizes.
Visual Content
4-way Intersection Geometry
Illustrates the geometry and turning policy of the intersection used for simulations. The diagram shows the layout of lanes and the movement of platoons.
Phase Plan
Depicts the phase plan for the baseline traffic light policy, showing the sequence of traffic movements.
Timing Diagram
Shows the timing diagram for the baseline traffic light policy, detailing the cycle times for each phase.
Average Delay Per Vehicle
Graph comparing average delay per vehicle across different policies and platoon sizes.
Delay Standard Deviation
Graph illustrating the computed standard deviation of delays for different policies and platoon sizes.
Intersection Traffic Flow
Graph showing the average traffic flow for different policies and platoon sizes.
Fuel Consumption
Graph demonstrating fuel consumption per vehicle for different policies and platoon sizes.
Conclusion
The study presents a centralized platoon-based controller for cooperative intersection management, leveraging realistic vehicle dynamics and communication protocols. The proposed policy outperforms traditional traffic light systems in terms of delay, fuel consumption, and intersection throughput. Simulation results confirm the effectiveness of the approach, highlighting its scalability and potential for real-world applications.