Yagnik M Bhavsar , Mazad S Zaveri , Mehul S Raval , Shaheriar B Zaveri
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引用次数: 0
Abstract
In the past decade, the number of vehicles in India has increased exponentially; however, road infrastructure has not scaled proportionately. As a result, road traffic problems such as congestion on urban roads, dangerous traffic violations, and road accidents have increased significantly. Due to limited road infrastructure, traffic violations (human errors) have intensified in densely populated urban areas. This paper presents a case study (at a multi-lane urban roundabout in Ahmedabad city, India) and the methodology based on computer vision to investigate road traffic and violations using drone/UAV-based aerial video. You Only Look Once-YOLOv7 is used for vehicle detection, and Simple Online and Real Time Tracking-SORT for tracking vehicles. Our methodology divides the road scene (roundabout) into certain zones. We then formulated the dictionary, which maps the traffic violations under Motor Vehicle Driving Regulations - MVDR/ Motor Vehicle Act - MVA and the movement of the vehicle (zone traversal sequences). Using the zone-based methodology, we could also probe other road traffic data such as the count of vehicles, speed of vehicles, rate of traffic flow, and congestion. Based on our results, we also infer some of the possible causes of traffic violations in terms of problems/limitations of road infrastructure. As per our analysis, around 23.26% of vehicles committed traffic violations. We detected traffic violations related to lane indiscipline, driving against the authorized flow of traffic, parking violations, and over-speeding within the roundabout. Our methodology of investigating road traffic and violations can be used for road infrastructure improvement, law enforcement drives, and policy making, for road traffic safety, in developing and densely populated countries.
在过去十年中,印度的汽车数量呈指数级增长;然而,道路基础设施并没有按比例扩大。因此,城市道路拥堵、危险交通违法和道路事故等道路交通问题显著增加。由于道路基础设施有限,在人口稠密的城市地区,交通违法行为(人为失误)加剧。本文介绍了一个案例研究(在印度艾哈迈达巴德市的一个多车道城市环岛),以及基于计算机视觉的方法,使用基于无人机/无人机的空中视频调查道路交通和违法行为。You Only Look Once-YOLOv7用于车辆检测,Simple Online和Real Time Tracking SORT用于跟踪车辆。我们的方法将道路场景(环形交叉路口)划分为某些区域。然后,我们制定了字典,它映射了《机动车驾驶条例》(MVDR/《机动车法》)下的交通违法行为和车辆的移动(区域穿越序列)。使用基于区域的方法,我们还可以调查其他道路交通数据,如车辆数量、车辆速度、交通流量和拥堵情况。根据我们的研究结果,我们还从道路基础设施的问题/限制方面推断了交通违法的一些可能原因。根据我们的分析,大约23.26%的车辆存在交通违法行为。我们发现了与违反车道纪律、违反授权交通流量行驶、违反停车规定和环岛内超速行驶有关的交通违法行为。我们调查道路交通和违法行为的方法可用于发展中国家和人口稠密国家的道路基础设施改善、执法和政策制定,以及道路交通安全。