Situation-Aware Left-Turning Connected and Automated Vehicle Operation at Signalized Intersections
نویسندگان
چکیده
One challenging aspect of the connected and automated vehicle (CAV) operation in mixed traffic is development a situation-awareness module for CAVs. While operating on public roads, CAVs need to assess their surroundings, especially intentions non-CAVs. Generally, demonstrate defensive driving behavior, expect other nonautonomous entities road will follow rules or common behavior. However, presence aggressive human drivers surrounding environment, who may not behave abruptly, can lead serious safety consequences. In this article, we have addressed CAV non-CAV interaction by evaluating left-turning operations an urban area. Existing literature does consider intent following CAV's movement, existing controllers do non-CAV's intents. Based our simulation study, situation-aware controller reduces up 47% abrupt braking non-CAVs scenarios with different opposing through movement compared base scenario autonomous vehicle, without considering vehicle's intent. The analysis shows that average travel time reductions opposite volumes 600, 800, 1000 vehicle/hour/lane are about 58%, 52%, 62%, respectively, both driver if considered making left-turn at intersection.
منابع مشابه
Pedestrian Accidents with Left-turning Traffic at Signalized Intersections: Characteristics, Human Factors and Unconsidered Issues
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ژورنال
عنوان ژورنال: IEEE Internet of Things Journal
سال: 2021
ISSN: ['2372-2541', '2327-4662']
DOI: https://doi.org/10.1109/jiot.2021.3064041