Modelling parking choice behaviour using Possibility Theory

Proceedings of the 82nd …, 2003

The development of such models commonly includes administration of surveys to collect data on individual travel preferences. The data collected are then used to identify the influential variables that will be incorporated into the model. Different parking choice models have been proposed in the literature. They can be classified with respect to the modeling approach, decision type, number of decisions modeled, and the data collection method [i.e., stated preference (SP) versus revealed preference (RP)]. Most parking models address mode-of-travel choices and parking characteristics (6-8) rather than the choice between parking alternatives. In addition, most research has considered parking choice as a stand-alone decision rather than as a component in a broader behavioral framework. The following paragraphs summarize selected parking type choice models that have been studied.

Transportation, 1991

Over recent years, parking policy has become a key element of transport policy in many countries. Parking policy measures can affect many different dimensions of travel behaviour but are likely to be most significant in terms of travellers' choice of parking type and location. This dimension of travel choice has, to date, received comparatively little attention, yet is of vital importance if we are to properly understand and predict the effects of parking policy measures.

Yugoslav Journal of Operations Research, 2004

Modeling of human choice mechanism has been a topic of intense discussion in the transportation community for many years. The framework of modeling has been rooted in probability theory in which the analyst's uncertainty about the integrity of the model is expressed in probability. In most choice situations, the decision-maker (traveler) also experiences uncertainty because of the lack of complete information on the choices. In the traditional modeling framework, the uncertainty of the analyst and that of the decision-maker are both embedded in the same random term and not clearly separated. While the analyst's uncertainty may be represented by probability due to the statistical nature of events, that of the decision maker, however, is not always subjected to randomness; rather, it is the perceptive uncertainty. This paper proposes a modeling framework that attempts to account for the decision maker's uncertainty by possibility theory and then the analyst's uncertainty by probability theory. The possibility to probability transformation is performed using the principle of uncertainty invariance. The proposed approach accounts for the quality of information on the changes in choice probability. The paper discusses the thought process, mathematics of possibility theory and probability transformation, and examples.

South African Journal of Industrial Engineering

Trying to find a parking space in a parking lot is a routine activity for most people in our society. However, in managing the sustained growth rate in the number of vehicle users, the demand on such parking facilities is likely to remain under constant pressure. Both the users and the management of parking lots use various strategies in dealing with the requirement for suitable parking facilities. This paper presents a computational model using an agent-based modelling technique to simulate two commonly used strategies applied to choosing a parking spot under various demand and supply conditions. The model is unique in the current literature, as it is specifically designed to evaluate the effectiveness of the strategies. The analysis of the experimental results shows that, in most conditions, accepting the first available parking spot and then walking to the destination performed better than driving as close as possible to the destination and then searching for an available parking spot.

Sustainability, 2023

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Transportation Research Record: Journal of the Transportation Research Board, 2012

Parking choice is an essential part of individual transportation; however, many travel demand and traffic simulations do not include parking. This paper reports on a proposal for a simple parking model and describes how this model was implemented into an existing, agent-based traffic simulation. The parking model provides feedback to the traffic simulation so that the overall simulation can react to spatial differences in parking demand and supply. Simulation results of a scenario in the city of Zürich, Switzerland, demonstrated that the model could capture key elements of parking, including capacity and pricing, and could assist with designing parking-focused transport policies. The paper also discusses possible work, such as microsimulation of the search for large-scale parking.

Transportation Research Part A: Policy and Practice, 2014

We examine car driver's behaviour when choosing a parking place; the alternatives available are free on-street parking, paid on-street parking and parking in an underground multi-storey car park. A mixed logit model, allowing for correlation between random taste parameters and estimated using stated choice data, is used to infer values of time, both when looking for a parking space and for accessing the final destination. Apart from the cost of parking, we found that vehicle age was a key variable when choosing where to park in Spain. We also found that the perception of the parking charge was fairly heterogeneous, depending both on the drivers' income levels and whether or not they were local residents. Our results can be generalised for personalised policy making related with parking demand management.

Conference: Transportation Planning and Implementation Methodologies for Developing CountriesAt: indian institute of technology, BombayVolume: 12th, 2016

Major cities of India are facing on-street parking problem specifically in CBD area. Lack of data for on-street parking demand and absence of concrete parking policy leads to business as usual condition on major streets of CBD area. Therefore, a 12 hour parking inventory using license plate method was carried out for the two busy urban streets of the CBD area of Vadodara. Survey witnessed demand spilling over the supply with poor turnover for major duration of the inventory. This study was an attempt to model the response of the vehicle parkers using on-street parking for a policy measure framed under guideline of National urban transport policy (NUTP 2014). The survey data was analysed using fuzzy technique revealed that house hold income, frequency of trip and duration of parking influenced the parking choice behaviour of driver.

This paper presents a modelling approach based on the Possibility Theory to reproduce drivers' choice behaviour under Advanced Traveller Information Systems (ATIS). The Possibility Theory is introduced to model uncertainty embedded in human perception of information through a fuzzy data fusion technique. Drivers' choice models are often developed and calibrated by using, among other, Stated Preferences (SP) surveys. An experiment is presented, aimed at setting up an SP-tool based on driving simulator developed at the Technical University of Bari. The obtained results are analysed in order to compare the outcomes of the proposed model with preferences stated in the experiment.