R.C.P. Wong

Modelling multi-period customer-searching behaviour of taxi drivers

Various taxi network models have been developed to investigate the consequences of implementing taxi regulation policies. These models rely on logit-based taxi customer-search models to depict the customer-searching behaviour of drivers. However, very few studies have sought to validate the hypotheses on which the logit models are based, or to determine the factors that affect drivers’ customer-searching choices at different times of day. In this study, global positioning system (GPS) data from 460 urban taxis were used to validate the logit model and determine the factors underlying drivers’ searching behaviour. The analysis reveals that cross-zonal travel distance, intra-zonal circulating distance, relative passenger demand and rate of return affect the customer-searching decisions of the drivers of vacant taxis and that their searching behaviour varies with the time of day. The data also reveal that the cross-district search behaviour of vacant taxi drivers is strongly related to passenger demand over time and space. The drivers of vacant taxis tend to travel to high-demand districts during the mid-night period when overall demand is low, but they avoid crossing districts during high-demand peak hours.

A Time-dependent Logit-based Taxi Customer-search Model

In this study, global positioning system data from 460 urban taxis are used to develop a time-dependent logit model. The rate of return (ROR, also known as profit per unit time) is used as a factor underlying taxi drivers’ searching behaviour for customers. The data also reveal that the search behaviour across districts as well as the decisions towards a particular district in customer-search is strongly related to the daily profile of passenger demand, and that when the overall passenger demand is high, vacant taxi drivers tend to circulate within or wait at the area where their preceding customers got off to find their next customer. The results also show that the ROR is a significant factor that affects the customer-searching strategies of vacant taxi drivers over a day, and is inversely related to the percentage of taxi idling time. More importantly, this paper illustrates that there is a change in searching behaviour over time of day.

Public transport policy measures for improving elderly mobility

Abstract Population aging is happening in most of the worlds metropolitan cities, and the proportion of elderly adults is predicted to increase significantly in the coming decades. This rapid growth of elderly populations may lead to serious transport issues when their mobility is compromised by the unavailability of public transport services. Public transport concession fare schemes are commonly implemented in many cities to encourage the elderlys participation in social activities. However, these policies emphasize the role of money (i.e., travel fares) in determining willingness to travel. Other possible factors, such as walking distance to and from stops and stations, wait times for public transport services, and seat availability, have not been considered by transport operators and policy makers. In this study, we interviewed 613 elderly Hong Kong residents aged 60 or above regarding their travel decisions using designated modes of public transport to attend social activities in four hypothetical games. A total of 2452 observations were collected for model development. Binary logistic regression models were calibrated to determine which factors significantly influenced the elderlys travel decisions. Based on the model results, this paper suggests policy measures to strengthen public transport planning in Hong Kong with the goal of improving elderly mobility. The findings provide policy insights that can also be applied to other metropolitan cities with similar traffic conditions.

Mixed logit approach to modelling arrival time choice behaviour of cemetery and columbarium visitors during grave-sweeping festivals

Special events attract extraordinarily high travel demands over a relatively short time. Managing the travel demand for special events is more difficult than for normal commuting trips. Grave-sweeping is a special event that is popular in Asia, especially in Chinese societies. In Hong Kong, many people visit cemeteries and columbaria around the two traditional festivals, causing overcrowding at the sites and congestion on the access roads. To mitigate the adverse traffic effects, the police usually implement temporary traffic management measures to control the number of visitors accessing the sites. However, these measures often ignore visitors’ arrival time preferences and hence their effectiveness is questionable. This study models and analyses the arrival time preferences of cemetery and columbarium visitors under various transport mode scenarios. The model development is based on 3128 choice decisions collected from 782 respondents. A mixed logit model is calibrated to investigate the potential taste heterogeneity of the respondents, and a likelihood ratio test demonstrates that the model is superior to a standard multinomial logit model and provides a better fit to the survey data. The model results indicate that in-vehicle travel time, total waiting and walking time, and the provision and travel fare of feeder services are significant factors influencing cemetery and columbarium visitors’ arrival time choices. The effects of socio-economic factors are also examined and discussed. Based on the model results, recommendations are provided for managing the travel demand to cemeteries and columbaria at peak and off-peak hours on or around festival days.