TY - GEN
T1 - A discrete choice approach to define individual parking choice behaviour for the Parkagent model
AU - Khaliq, A.
AU - van der Waerden, P.J.H.J.
AU - Janssens, D.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Agent based parking simulation model PARKAGENT
KW - Discrete choice model
KW - Factors affecting on-street parking choice
UR - http://www.scopus.com/inward/record.url?scp=85039733271&partnerID=8YFLogxK
U2 - 10.2495/UT170421
DO - 10.2495/UT170421
M3 - Conference contribution
AN - SCOPUS:85039733271
SN - 9781784662097
T3 - WIT Transactions on The Built Environment
SP - 493
EP - 502
BT - Urban Transport XXIII, 5-7 September 2017, Rome, Italy
PB - WIT Press
CY - s.l.
T2 - 23rd International Conference on Urban Transport and the Environment, 2017
Y2 - 5 September 2017 through 7 September 2017
ER -