Vacant Parking Space Research Articles

Pricing of parking games with atomic players

This paper considers a parking competition game where a finite number of vehicles from different origins compete for the same number of parking spaces located at various places in a downtown area to minimize their own parking costs. If one vehicle reaches a desired vacant parking space before another vehicle, it will occupy the space and the other vehicle would have to search elsewhere. We first present a system of nonlinear equations to describe the equilibrium assignment of parking spaces to vehicles, and then discuss optimal pricing schemes that steer such parking competition to a system optimum assignment of parking spaces. These schemes are characterized by a union of polyhedrons. Given that the equilibrium state of parking competition is not unique, we further introduce a valid price vector to ensure that the parking competition outcome will always be system optimum. A sufficient condition is provided for the existence of such a valid price vector. Lastly, we seek for a robust price vector that yields the best worst-case outcome of the parking competition.

Vacant Parking Space Detection Based on Plane-Based Bayesian Hierarchical Framework

In this paper, we propose a vacant parking space detection system that operates day and night. In the daytime, the major challenges of the system include dramatic lighting variations, shadow effect, inter-object occlusion, and perspective distortion. In the nighttime, the major challenges include insufficient illumination and complicated lighting conditions. To overcome these problems, we propose a plane-based method which adopts a structural 3-D parking lot model consisting of plentiful planar surfaces. The plane-based 3-D scene model plays a key part in handling inter-object occlusion and perspective distortion. On the other hand, to alleviate the interference of unpredictable lighting changes and shadows, we propose a plane-based classification process. Moreover, by introducing a Bayesian hierarchical framework to integrate the 3-D model with the plane-based classification process, we systematically infer the parking status. Last, to overcome the insufficient illumination in the nighttime, we also introduce a preprocessing step to enhance image quality. The experimental results show that the proposed framework can achieve robust detection of vacant parking spaces in both daytime and nighttime.

Smart Parking System Based on Wireless Sensor Network for Large Parking Lots

In China, finding a vacant parking space in a congested area or a large parking lot is always time consuming and frustrating. To minimize hassle and inconvenience to the automatic drivers, this paper proposed a novel smart parking system which consists of many parking sensor nodes and one parking gateway in one large parking lot. Parking sensor node is used as vehicle occupancy detector and parking gateway is used as parking lot manager. All parking sensor nodes compose wireless sensor networks with Zigbee transmission protocol. With the GPRS/3G transmission function of parking gateway, large parking lot can provide friendly parking information to the running vehicles and subscribed users. In a word, the proposed novel smart parking system is provided with innovative and practicability.

A Hierarchical Bayesian Generation Framework for Vacant Parking Space Detection

In this paper, from the viewpoint of scene under standing, a three-layer Bayesian hierarchical framework (BHF) is proposed for robust vacant parking space detection. In practice, the challenges of vacant parking space inference come from dramatic luminance variations, shadow effect, perspective distortion, and the inter-occlusion among vehicles. By using a hidden labeling layer between an observation layer and a scene layer, the BHF provides a systematic generative structure to model these variations. In the proposed BHF, the problem of luminance variations is treated as a color classification problem and is tack led via a classification process from the observation layer to the labeling layer, while the occlusion pattern, perspective distortion, and shadow effect are well modeled by the relationships between the scene layer and the labeling layer. With the BHF scheme, the detection of vacant parking spaces and the labeling of scene status are regarded as a unified Bayesian optimization problem subject to a shadow generation model, an occlusion generation model, and an object classification model. The system accuracy was evaluated by using outdoor parking lot videos captured from morning to evening. Experimental results showed that the proposed framework can systematically determine the vacant space number, efficiently label ground and car regions, precisely locate the shadowed regions, and effectively tackle the problem of luminance variations.

INTELLIGENT TRANSPORTATION SYSTEMS IN IMPROVING TRAFFIC FLOW IN TOURISM DESTINATIONS∗

The rapid growth and development of motorisation combined with relatively small investments made to improving transportation infrastructure in cities, as well as in tourism destinations, has led to serious problems in the unobstructed movement of vehicles in public traffic areas. Traffic congestion on roadways, in ferryboat ports and at state borders during the summer months and year-round lines of cars going to or returning from work are a regular presence in traffic in most urban and tourism destinations in Croatia, as well as in the rest of Europe. Intelligent transportation systems (ITS) can be implemented in urban and tourism centres, which, for example, have no opportunity for increasing the capacity of their traffic networks by constructing new, or expanding existing, transportation infrastructure, and no opportunity for increasing parking capacities. The only solution would be to optimise traffic networking by introducing intelligent technologies. Intelligent transportation systems and services represent a coupling of information and telecommunication technologies with transportation means and infrastructure to ensure greater efficiency in the mobility of people and goods. ITS implementation helps to provide better information to motorists and travellers (tourists); improve traffic and tourist flows, cargo transportation, public passenger-transportation; facilitate the work of emergency services; enable electronic traffic-related payments; enhance the security of people in road traffic; and monitor weather conditions and the environment. To motorists the system provides guidance to roads on which traffic is less intense, guidance to available parking spaces, and guidance, for example, to a good restaurant or interesting tourist attraction. his paper focuses, in particular, on ITS application in city and tourism destinations in connection with parking problems. Guiding vehicles to the closest vacant parking space helps to reduce traffic congestion, reduce the amount of time lost in searching and increase the occupancy rate of car-parks

Modeling Parking

This paper presents a simple model of parking congestion focusing on drivers' search for a vacant parking space in a spatially homogeneous metropolis. The mean density of vacant parking spaces is endogenous. A parking externality arises because individuals neglect the effect of their parking on this mean density. We examine stochastic stationary-state equilibria and optima in the model. Due to the model's nonlinearity, multiple equilibria may exist and the effects of parking fees are complex. Several extensions are discussed, including determining the social value of a particular parking information system.