Citation

Bhavsar YM, Zaveri MS, Raval MS, Zaveri SB. Transp. Eng. (Amsterdam) 2023; 14: e100207.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.treng.2023.100207

PMID

unavailable

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.

Language: en

Keywords

Aerial imagery; Computer vision; Motor vehicle driving regulation; Road traffic monitoring; Traffic violation; UAV