When such variables are identified for both customers and facilities, choices can be made on the basis of economic advantage.
In this section, we analyse the congestion of the Loading Bay (LB) and its effect on drivers' parking facility choice.
Further analysis of the effect of LB congestion on parking facility choice is carried out in Section 4.3.3.
Owing to the considerable development of bike facilities, the investigation of facility preference, particularly focusing on facility choice forecast, has become increasingly important.
This study developed a model for predicting the facility choice of cyclists between on-street facilities (curb, traffic lane, and bike lane (BL)) and off-street facilities (sidewalks).
The future direction of the research is to use the disaggregate data to train mathematical models of drivers' parking behaviour, examining parking facility choice and parking duration.
The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage).
However, we have acknowledged such limitation focusing on two main decisions which we consider determined in most part by the drivers' alone, and which still have an important impact on the parking congestion and road traffic: the parking facility choice and parking duration.
A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion.
Apart from the aforementioned factors, several other exogenous variables were also found to be significant predictors of bike facility choice, including the width of traffic lanes, existence of real-time stopping vehicle, type of bike, bus stop existence, and in-group cycling.
