English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

PARKAGENT is an agent based model for simulating parking search in the city. In PARKAGENT, the agents choose a parking spot based on the expected number of free parking spaces, distance to destination and length of parking space. For a true representation of underlying parking choice behaviour of agents in PARKAGENT model, a behavioural model is required. Behavioural models are considered as the core of agent based simulations, therefore a behavioural model capable to exhibit parking choice process in PARKAGENT has been proposed in this paper. This model explains that parking choice is based on the principles of utility maximization. Several research studies have used discrete choice models to describe parking choice phenomena. Discrete choice models determine the utility associated with choice of services and products. It is assumed that individual make decisions rationally, it is very difficult to measure the actual utility associated with a parking space. For a realistic calculation of the utility, factors affecting parking choice such as (parking cost, distance to destination, etc.) are required. In this research, the choice of on-street parking is considered keeping in view the factors associated with the street situation (e.g. occupancy, security). The decision of an agent to choose a street for parking is based on the factors associated to street. The necessary data is collected through stated choice questionnaire. The collected data is analysed using a discrete choice model (multinomial logit model). The results indicate show that the identified attributes of streets significantly affect the parking choice behaviour of agents.

A DISCRETE CHOICE APPROACH TO DEFINE INDIVIDUAL PARKING CHOICE BEHAVIOUR FOR THE PARKAGENT MODEL