Open AccessBuilt environment and parking pricing: Probability on changing mode choice in Bandung urban area
Author(s) -
D N Afalia,
S Y Rachmat
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/592/1/012003
Subject(s) - metropolitan area , trips architecture , transport engineering , binary logit model , business , public transport , mode (computer interface) , park and ride , trip generation , city centre , traffic congestion , geography , computer science , engineering , mathematics , statistics , archaeology , operating system
Bandung as an urban area in the centre of Metropolitan Bandung Raya and the centre of various activities generate high movement of trips, especially the movement from commuters. The more trips use motorized vehicles, the more people need parking lots. In consequences, the massive movement using private vehicle and the use of on-street parking causes congestion in Bandung Urban Area because of the increasing of road capacity. Previous research proved that one factor to reduce private vehicle user mode choice behaviour is by having a strong strategy in parking. Hence the parking pricing is one of the most effective parking strategies in influencing driver behaviour. The binary logit regression model is used to identify the behaviours of private vehicle users and to investigate the probability of private vehicle drivers shifting to mass transportation particularly for commuter’s trip. This paper surveyed 200 commuters through revealed and stated preference in Bandung Centre Area. The best model is the model with the highest significance number shown from the Neglekerke R square number. The response keeps using private vehicle and parking in the existing area has the highest significance number which is 0,59. The model from the response is Ln P/1-P = 4.356 -1,550 (X1.1)- 1,279 (X1.2) – 0,01 (X2). The variables in this model are a medium compact area (X1.1), a compact area (X1.2) and parking pricing strategy (X.2). The result can assist decision-makers on all levels to wisely allocate resources to public transportation improvement, and optimization of parking pricing strategy, especially in Bandung Urban Area.