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Mitigating Urban Traffic Congestion Through OPSAM in Delhi: A YOLO-v4 Based Parking Guidance and Information System
Abdul Ahad
Mitigating Urban Traffic Congestion Through OPSAM in Delhi: A YOLO-v4 Based Parking Guidance and Information System - p357-372
The rapid increase in private vehicle ownership in major Indian cities, particularly in Delhi has led to significant traffic congestion. Although India's car ownership rates are lower than the global average, the increasing demand for street parking has significantly reduced road capacity and slowed traffic flow in urban areas. This study addresses a crucial gap in the literature by quantifying the impact of parking on traffic congestion within the Indian context. It focuses on Delhi, where traffic congestion is a persistent issue, particularly during peak hours on highways and arterial roads. Factors contributing to this problem include high vehicle density, illegal parking, inadequate parking facilities, mixed traffic flow, and inefficient traffic management. To mitigate these challenges, this paper introduces the Optimal Parking Space Allocation Model (OPSAM), an innovative online platform that provides real-time parking status information across multiple parking spaces within a designated area. OPSAM is designed to align with driver preferences, significantly reducing the time spent searching for parking spaces and thereby alleviating congestion. The model leverages the YOLO-v4 detection algorithm to detect real-time parking vacancies via security cameras and mobile applications. The model was tested in both day and night conditions, demonstrating effective detection capabilities with an average reduction of 20% in parking cruising time compared to traditional methods. A paired t-test analysis showed a statistically significant difference in search times, with a mean reduction of 9.775 min (p-value < 0.001), supporting the system's effectiveness. Compared to conventional parking approaches, OPSAM also reduced the incidence of illegal parking by 12% and improved parking occupancy efficiency from 70 to 85%. These results suggest that efficient parking management, such as OPSAM's can play a crucial role in alleviating urban congestion, enhancing traffic flow, and improving urban mobility in New Delhi.
Automotive Infrastructure and Services
Motion Detection
Optimization
Smart Infrastructure
Transport Research
Transportation Technology and Traffic Engineering
Mitigating Urban Traffic Congestion Through OPSAM in Delhi: A YOLO-v4 Based Parking Guidance and Information System - p357-372
The rapid increase in private vehicle ownership in major Indian cities, particularly in Delhi has led to significant traffic congestion. Although India's car ownership rates are lower than the global average, the increasing demand for street parking has significantly reduced road capacity and slowed traffic flow in urban areas. This study addresses a crucial gap in the literature by quantifying the impact of parking on traffic congestion within the Indian context. It focuses on Delhi, where traffic congestion is a persistent issue, particularly during peak hours on highways and arterial roads. Factors contributing to this problem include high vehicle density, illegal parking, inadequate parking facilities, mixed traffic flow, and inefficient traffic management. To mitigate these challenges, this paper introduces the Optimal Parking Space Allocation Model (OPSAM), an innovative online platform that provides real-time parking status information across multiple parking spaces within a designated area. OPSAM is designed to align with driver preferences, significantly reducing the time spent searching for parking spaces and thereby alleviating congestion. The model leverages the YOLO-v4 detection algorithm to detect real-time parking vacancies via security cameras and mobile applications. The model was tested in both day and night conditions, demonstrating effective detection capabilities with an average reduction of 20% in parking cruising time compared to traditional methods. A paired t-test analysis showed a statistically significant difference in search times, with a mean reduction of 9.775 min (p-value < 0.001), supporting the system's effectiveness. Compared to conventional parking approaches, OPSAM also reduced the incidence of illegal parking by 12% and improved parking occupancy efficiency from 70 to 85%. These results suggest that efficient parking management, such as OPSAM's can play a crucial role in alleviating urban congestion, enhancing traffic flow, and improving urban mobility in New Delhi.
Automotive Infrastructure and Services
Motion Detection
Optimization
Smart Infrastructure
Transport Research
Transportation Technology and Traffic Engineering