An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach

Abstract

Real-time parking occupancy information is critical for a parking management system to facilitate drivers to park more efficiently. Recent advances in connected and automated vehicle technologies enable sensor-equipped cars (probe cars) to detect and broadcast available parking spaces when driving through parking lots. In this paper, we evaluate the impact of market penetration of probe cars on the system performance, and investigate different parking guidance policies to improve the data acquisition process. We adopt a simulation-based approach to impose four policies on an offstreet parking lot influencing the behavior of probe cars to park in assigned parking spaces. This in turn effects the scanning route and the parking space occupancy estimations. The last policy we propose is a near-optimal guidance strategy that maximizes the information gain of posteriors. The results suggest that an efficient information gathering policy can compensate for low penetration of connected and automated vehicles. We also highlight the policy trade-off that occur while attempting to maximize information gain through explorations and improve assignment accuracy through exploitations. Our results can assist urban policy makers in designing and managing smart parking systems.Wu, Balkumar and Luo et al. 2 INTRODUCTIONThe ever-increasing number of cars on roads today has led to a burden on the management of transportation infrastructure. A prime example we observe today is vehicle owners finding it difficult to search for parking spaces. This is more evident in large cities and in prime locations where it is not uncommon to find vehicles moving around inside a parking lot anticipating a parking space to free up. In addition to the driver discomfort and frustration, searching for a parking space leads to a significant loss of personal time and an increase in fuel consumption.Searching for a parking space in an optimized manner is thus a problem that demands the attention of researchers. The availability of real-time parking information has the potential for immense time and economic savings as drivers know in advance the presence of empty parking spots at the end of their trips. A highly desirable feature in such a system is that the source of real-time information must be independent of infrastructure. Parking solutions that depend on infrastructure, for example the use of on-site cameras, often incur significant costs. More importantly the implementation of such a solution is not generic with respect to the layout of the parking lot. Modern vehicle advancements have led to cars that are today equipped with vision and range-based navigation sensors and offer a source of real-time parking space information which is independent of surrounding infrastructure. The focus of researchers has thus shifted towards modifying the navigating sensors and algorithms to tap real-time information on the occupancy of parking spaces, and subsequently relaying the useful information to a wide audience (1).Even though exploiting data from ve...