Autonomous intersection management (AIM) systems can achieve three percent more traffic throughput than a traditional signal system, assuming 10 percent CAV market penetration.

The Texas Department of Transportation (TxDOT) examines various strategies to improve network operations using smart transport technologies.

Date Posted
08/22/2019
Identifier
2019-B01388
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Autonomous Intersection Management (AIM) was discussed for networks with connected automated vehicles (CAVs) and human-driven vehicles (HVs). The strategy included a reservation-based protocol in which CAVs could request to reserve trajectories crossing an intersection using a "first come, first served" (FCFS) policy, and an automated intersection manager would approve the reservation requests only if it did not conflict with any previously approved reservation or an HV.

The AIM protocol did not rely on communication capabilities between vehicles (V2V) but only between vehicles and the intersection manager (V2I). The protocol was robust to communication failures: if a message was lost, either by the intersection manager or by the CAV, the system's efficiency may have been reduced, but safety was not compromised. Safety was guaranteed also when considering a mixed scenario where both HVs and CAVs were present.

FINDINGS

Researchers found that by modifying the protocol to detect HVs, which were assumed to always stop at red signals and cross intersections on green signals, they could safely direct autonomous vehicles (AVs) through an intersection even if the AVs arrived on a lane that was assigned a red signal.

Results indicated that with a 10 percent CAV penetration rate, the hybrid AIM protocol (H-AIM) could achieve three percent more traffic throughput than a traditional traffic signal system. In addition, experimental results showed that H-AIM can decrease traffic delay for CAVs at penetration rate of only one percent.

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