Utilizing intelligent transportation infrastructures can significantly improve the throughput of intersections of Connected Autonomous Vehicles (CAV), where an Intersection Manager (IM) schedules the cross-time of incoming CAVs. In addition, accidents that happen at intersections due to human errors can be reduced.
In Crossroads, we identified the effect of Round-Trip Delay (RTD) on the safety of existing approaches and proposed a deterministic solution that is safe and efficient.
After clock synchronization, IM assigns an actuation time to a CAV which is greater than the worst-case RTD to make sure it will be delivered on-time. In case the delay is larger, the CAV stops.
In RIM, we studied challenges of intersection management when the considered model is uncertain and external disturbances exist.
We proposed a new interface between the IM and CAVs where CAVs create their own desired trajectory and track it.
We improved our previous work (Crossroads) and proposed a new algorithm (Crossroads+) that accounts for model mismatches by knowing the configuration of the speed controller and dynamics of the vehicle.
By compensating for the response time of the vehicle (to maintain the desired velocity), a safe schedule of the intersection is possible.
Existing intersection management techniques are built assuming all CAVs send the correct information when sharing their status with the intersection manager (IM) and obey IM’s command accurately. This is, however, a strong assumption to keep since CAVs are prone to cyberattacks and unexpected faults can happen during the operation of the intersection.
In R2IM approach, we refer to a dishonest or disobedience CAV a “Rouge Vehicle” and propose an intersection management technique that with the help of a surveillance system can ensure that no accidents happen inside the intersection area as long as only one rouge vehicle is present at a time.
we have done a broad survey on intersection management of connected autonomous vehicles, which studies different aspects of intersection management.
1) intersection management interface, 2) scheduling policy, 3) existing wireless technologies 4) existing vehicle models used by researchers and their impact, 5) conflict detection, 6) extension to multi-intersection management, 7) challenges of supporting human-driven vehicles, 8) safety and robustness required for real-life deployment, 9) graceful degradation and recovery for emergency scenarios, 10) security concerns and attack models, and 11) evaluation methods