A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections

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Abstract

Connected and autonomous vehicle technology has advanced rapidly in recent years. These technologies create possibilities for highly efficient, AI-based, transportation systems. One such system is the Autonomous Intersection Management (AIM), an intersection management protocol designed for the time when all vehicles are fully autonomous and connected. Experts, however, anticipate a long transition period during which human and autonomously operated vehicles will coexist. Unfortunately, AIM has been shown to provide little or no improvement over today’s traffic signals when less than 90% of the vehicles are autonomous, making AIM ineffective for a large portion of the transition period. This paper introduces a new protocol denoted Hybrid Autonomous Intersection Management (H-AIM), that is applicable as long as AIM is applicable and the infrastructure is able to sense approaching vehicles. Our experiments show that this protocol can decrease traffic delay for autonomous vehicles even at 1% technology penetration rate.

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Sharon, G., & Stone, P. (2017). A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10642 LNAI, pp. 151–167). Springer Verlag. https://doi.org/10.1007/978-3-319-71682-4_10

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