The Impact of Smart Parking Systems on Reducing Urban Traffic Congestion: A Case Study of Bengaluru

Urban traffic congestion is a significant challenge in rapidly expanding cities like Bengaluru, primarily due to the surge in vehicle ownership and limited parking infrastructure. Smart Parking Systems (SPS) have been proposed as a solution to alleviate this issue by utilizing technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) to optimize parking space utilization and reduce traffic congestion. This paper examines the impact of SPS on urban traffic congestion, focusing on Bengaluru as a case study. The study analyzes existing literature and recent implementations of SPS in Bengaluru, including initiatives by the Bruhat Bengaluru Mahanagara Palike (BBMP) to establish smart parking facilities across the city. These facilities aim to streamline parking for approximately 3,300 four-wheelers and 10,000 two-wheelers, thereby enhancing traffic flow and reducing gridlock. Additionally, the integration of IoT and AI in parking management has shown promising results in improving parking efficiency and reducing the time spent searching for parking spaces. The findings suggest that the adoption of SPS in urban environments like Bengaluru can significantly alleviate traffic congestion by providing real-time information on parking availability, thus contributing to more sustainable urban mobility. Keywords: Smart Parking Systems, Urban Traffic Congestion, Internet of Things, Artificial Intelligence, Bengaluru