Smart Parking Framework: Automatic Slot Allocation and In-Parking Guidance over DSRC-Based VANET Communication Infrastructure

Smart mobility is a core component of the smart city; it comprises various intelligent systems that make the city more safe, livable, efficient and sustainable. One of these system is the smart parking system (SPS). A smart parking system is known as the application of advanced information and communication technologies to the traditional parking system. It is a technology-driven approach that plays a crucial role in smart cities, particularly in improving traffic management. The smart parking system is a multi-faceted concept that integrates parking reservation, automatic payment, parking space detection, outside/inside guidance, data analytics, and user interaction interfaces. While various advanced technologies, such as Wireless Sensors Networks (WSNs), Internet of Things (IoT), Cloud Computing (CC), FoG computing, and Artificial Intelligence (AI), are involved in engineering and implementing these functional facets, Vehicular Ad Hoc Network (VANET) and its derivatives have received relatively limited interest in the literature of smart parking systems. Moreover, much of the literature primarily focuses on reducing parking search time outside parking facilities. However, drivers in practice often waste a significant amount of time inside the parking facility navigating for a free parking spot. In this work, we address two main functions in smart parking: a parking spot allocation mechanism and on-site parking real-time guidance. We developed an automatic parking spot allocation and in-parking guidance approach where the communication layer is modelled using IEEE 802.11p DRSC as the reference infrastructure. The simulation assumes a reliable channel and excludes lower-layer performance evaluation such as packet loss, congestion, latency, interferences, or coverage sensitivity. The reported improvements therefore characterize the application-layer benefit of pre-assignment reservation and spatial guidance, independent of the specific communication technology employed. The designed system, called in this paper VANET-guided, aims to significantly decrease the parking spot search time inside the parking facility. This paper presents a comparative evaluation study of a VANET-guided smart parking framework against a fully unguided baseline using NS-3.36.1, evaluating their performance across four key operational dimensions: lot occupancy, number of vehicles within facility, inter-arrival gap, and driver decision delay, with R = 30 statistically validated replications per experimental cell, using a series of Monte Carlo simulations under diverse traffic and mobility conditions. The guided system combines atomic server-side spot reservation, spatial allocation strategies, and a Kalman-filtered RSSI-based in-lot positioning pipeline, while the unguided baseline models realistic driver behavior, including cognitive decision delays, spot rejection, and concurrent spot competition. To address the structural asymmetry between the two systems, two intermediate baselines are evaluated: (i) an information-only configuration and (ii) a reservation-only configuration, providing an exploratory comparison of the respective roles of availability information, reservation, and spatial targeting. The findings indicate that the fully guided system (called in this paper VANET or VANET-guided) reduces mean parking search time by 28% to 71% relative to the fully unguided baseline across all tested occupancy levels, with statistical validation through 95% confidence interval analysis, paired t-test and Wilcoxon signed-rank test, practical effect sizes reported through Cohen’s d, and distributional statistics including standard deviation, coefficient of variation, and 90th–95th percentile search times.