A Smart, Sustainable, and Optimal Parking Allocation Scheme for Vehicles in Smart Cities

ABSTRACT

Unregulated parking search is a major source of urban inefficiency, leading to unnecessary cruising, wasted time, driver frustration and increased emissions. Moreover, when drivers select spots solely based on immediate self‐interest, ignoring others' dynamic needs and preferences, this behaviour exacerbates congestion, conflict and overall discomfort. To address these challenges and advance towards a smart, sustainable and user‐centric mobility system, this paper proposes an Optimal Parking Allocation Scheme (OPAS). By intelligently integrating user behaviour and real‐time demand, OPAS dynamically assigns parking spaces that enhance overall system efficiency while flexibly providing each user with an optimal spot, balancing collective sustainability with individual comfort. The proposed OPAS wirelessly receives the user information upon arrival at the entrance and determines the best‐suited spot by solving an adaptive optimisation problem considering the travel and parking behaviour in terms of the number of passengers in the car, their walking and driving distances, the priority level of users, in addition to trends of the occupation ratio. The proposed OPAS dynamically tunes its objective parameters to align with overarching system goals, yielding successive, situation‐adaptive decisions. The performance of the proposed scheme is evaluated using data from an indoor parking model of a shopping centre in Gunma City, Japan. The results demonstrate that OPAS achieves a significant reduction in both individual walking distance and vehicular travel distance within the parking facility. Consequently, this efficiency directly translates to a decrease in total fuel consumption and associated emissions. Specifically, the proposed strategy achieves a daily reduction of 23 kg in emissions and 10 L in fuel consumption, highlighting the practical significance of the proposed approach.