Demand Responsive Transport (DRT) is a relatively new form of public transport provision; it is an intermediate form somewhere between conventional bus and taxi services. Over the last decade, DRT services have grown in popularity mainly influenced by the development of transport telematics. The telematics-based DRT system, which forms the focus of this research, allows new generation DRT services to have greater flexibility in time and route design, and to enable immediate advance booking and response to travel requests. These DRT services have shown important advantages and benefits in several European cities and regions particularly as an alternative solution of public transport in low/dispersed demand areas and times. Moreover, DRT services have an important role to tackle social exclusion. However, several previous works reveal that many existing DRT services are still not performing to their true potential and there is still a research need to investigate DRT services from the passengers’ perspective. Therefore, this research studies DRT services from the passengers’ perspective by selecting the LinkUp DRT scheme as the case study. LinkUp is a telematics-based DRT scheme which operates as a public transport service in Tyne and Wear, UK with fully flexible routes in defined operating areas. A discrete choice model with latent variables is applied to model the passengers’ usage rate of the LinkUp DRT services. The assumption of the usage rate model developed in this research is that each passenger has an underlying utility for using the LinkUp services and the passengers who use LinkUp at different levels of frequencies have different levels of utility. The individual’s utility has an underlying latent variable and his usage rate of LinkUp in terms of number of trips per week serves as choice indicators. This study hypothesises that characteristics, and attitude and perception towards the LinkUp services of the passenger affect his utility. The passengers’ attitude and perception are constructed as latent variables (models) in the usage rate model. Therefore, the usage rate model consists of two sub-models: latent variable and discrete choice models which are specified as Multiple Indicators and MultIple Causes (MIMIC) and ordered probit models respectively. Three latent variables are proposed to quantify the passengers’ attitude and perception, which are latent Awareness, Satisfaction, and Relative Advantage. Consequently, the usage rate model is represented by the utility, which is hypothesised to be the function of the individual passenger’s characteristics and three latent variables. The results provide useful information for improving the LinkUp DRT scheme, implementing and developing telematics-based DRT services, further developing the travel behaviour model for DRT passengers, as well as for the DRT operators and policy makers.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:540461 |
Date | January 2011 |
Creators | Phonphitakchai, Thanawat |
Publisher | University of Aberdeen |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165208 |
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