Conflict-Free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-Based Modeling and Optimality Analysis

@article{Chen2022ConflictFreeCM,
  title={Conflict-Free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-Based Modeling and Optimality Analysis},
  author={Chaoyi Chen and Qing Xu and Mengchi Cai and Jiawei Wang and Jianqiang Wang and Keqiang Li},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2022},
  volume={23},
  pages={21897-21914}
}
Connected and automated vehicles have shown great potential in improving traffic mobility and reducing emissions, especially at unsignalized intersections. Previous research has shown that vehicle passing order is the key influencing factor in improving intersection traffic mobility. In this paper, we propose a graph-based cooperation method to formalize the conflict-free scheduling problem at an unsignalized intersection. Based on graphical analysis, a vehicle’s trajectory conflict… 

Reachability Analysis Plus Satisfiability Modulo Theories: An Adversary-Proof Control Method for Connected and Autonomous Vehicles

A control method named reachability analysis plus satisfiability modulo theories (RA-SMT) for CAVs against integrity attacks caused by bounded adversary enables vehicles to possess the reach-avoid specification and strict control safety ensurance even in the worst case scenario.

Distributed Model Predictive Control of Connected Multi-Vehicle Systems at Unsignalized Intersections

This paper develops a real-time receding-horizon planning approach, which improves plan consistency by reasoning about and reusing the previous trajectory, and develops a distributed model predictive controllers, which track the resulting reference trajectories and avoid collisions by allowing neighboring vehicles to exchange their intentions.

CAVSim: A Microscope Traffic Simulator for Connected and Automated Vehicles Environment

  • Jiawei ZhangChen Chang Li Li
  • Computer Science
    2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
  • 2022
CAVSim is modularly developed according to the emerging architecture for the CAVs environment, emphasizes more detailed driving behaviors of CAVs, and highlights the decision and planning components in the CAV environment.

A Platooning Strategy for Connected Automated Vehicles in Passing a General Conflict Area

A platooning strategy for connected automated vehicles when passing a general conflict area is proposed that clusters vehicles into platoons and treats each platoon as a scheduling unit instead of every vehicle to reduce the problem dimension.

An Efficient and Robust Object-Level Cooperative Perception Framework for Connected and Automated Driving

An object-level cooperative perception framework is proposed, in which data of the 3D bounding boxes, location, and pose are broadcast and received between the connected vehicles, then fused at the object level, which outperforms the state of the art benchmark methods when location or pose errors occur.

Cooperation Method of Connected and Automated Vehicles at Unsignalized Intersections: Lane Changing and Arrival Scheduling

Connected and automated vehicles (CAVs) have shown great potential in improving traffic efficiency in the area of intersection management. Numerous researches have been accomplished to solve the CAV

Multi-Lane Unsignalized Intersection Cooperation With Flexible Lane Direction Based on Multi-Vehicle Formation Control

Simulations indicate that this method outperformances the fixed-lane-direction unsignalized cooperation method and the signalized method, and the results indicate that the formation reconfiguration method is utilized to achieve collision-free longitudinal and lateral position adjustment of vehicles.

Modeling and Analysis of Mixed Tra c Networks with Human-driven and Autonomous Vehicles

This study addresses the research gap in macroscopic traffic modeling of mixed traffic networks where CAV and human-driven vehicles coexist by describing the approaching and departure vehicle number in discrete time and verifying the accuracy and effectiveness of the proposed algorithm.

Planning and Decision-making for Connected Autonomous Vehicles at Road Intersections: A Review

The evolving planning and decision-making methods based on vehicle infrastructure cooperative technologies are summarized and connected autonomous vehicles (CAVs) is the future direction for the automated driving area.

References

SHOWING 1-10 OF 46 REFERENCES

A Multiagent Approach to Autonomous Intersection Management

This article suggests an alternative mechanism for coordinating the movement of autonomous vehicles through intersections and demonstrates in simulation that this new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs.

Cooperative Conflict Detection and Resolution and Safety Assessment for 6G Enabled Unmanned Aerial Vehicles

Design of a Conflict Prediction Algorithm for Industrial Robot Automatic Cooperation

A Pairing Algorithm for Conflict-Free Crossings of Automated Vehicles at Lightless Intersections

This paper introduces a control method for CAV pairing allowing for the safe, collision-free crossing of the intersecting area and optimize traffic conditions, i.e., total delays of the system.

Formation Control with Lane Preference for Connected and Automated Vehicles in Multi-lane Scenarios

A Graph-based Conflict-free Cooperation Method for Intelligent Electric Vehicles at Unsignalized Intersections

  • Chaoyi ChenQing Xu Chunyu Qi
  • Computer Science
    2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
  • 2021
A graph-based cooperation method is proposed to formalize the conflict-free scheduling problem at unsignalized intersections and find the local optimal passing order for each vehicle.

Mixed platoon control of automated and human-driven vehicles at a signalized intersection: dynamical analysis and optimal control

Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios

Simulation results prove that the proposed multi-vehicle formation control framework can apply to multiple typical scenarios and have better performance than existing methods.