A protocol for pedestrian crossing and increased vehicular flow in smart cities
With the technological drive for realizing smart cities, work on Autonomous Intersection Management (AIM) protocols opts to replace the traditional traffic light system by using cooperative Vehicle-to-Vehicle (V2V) communication in order to decrease road congestion and increase vehicular throughput....
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Published in: | Journal of intelligent transportation systems Vol. 24; no. 5; pp. 514 - 533 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Philadelphia
Taylor & Francis
02-09-2020
Taylor & Francis Ltd |
Subjects: | |
Online Access: | Get full text |
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Summary: | With the technological drive for realizing smart cities, work on Autonomous Intersection Management (AIM) protocols opts to replace the traditional traffic light system by using cooperative Vehicle-to-Vehicle (V2V) communication in order to decrease road congestion and increase vehicular throughput. However, these protocols simply ignore pedestrians as road users and do not provision for safe pedestrian crossing. Basically, a road intersection not only could be traffic bottleneck, but also nearly 23% of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year. This article opts to fill such a technical gap. We present a novel system that prioritizes pedestrians crossing and guarantees safety while preserving the efficiency of AIM based approaches. Our system does not require additional infrastructure or pedestrian-carried devices, and works for both self-driving and human-derived vehicles. The simulation results show that our proposed system for Autonomous Pedestrian Crossing (APC) protocol of non-signalized intersections significantly decreases the vehicle's delay and pedestrian walk duration compared to the conventional traffic light-based systems. The effectiveness of APC is validated for traffic scenarios with (1) self-driving vehicles, and (2) mix of human-based and self-driving vehicles. |
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ISSN: | 1547-2450 1547-2442 |
DOI: | 10.1080/15472450.2019.1683451 |