Abstract

Various studies have advocated the potential for Demand Responsive Transport (DRT) services to deliver sustainable local public transport. This paper investigates the sustainability credentials of DRT services using evidence from UK-based research. More specifically, six potential DRT market niches were identified, including those which offer potential commercial opportunities (e.g. airport surface access) and those that meet social needs (e.g. non-emergency hospital trips). Mode share of these DRT services, against car or bus travel, was simulated from mixed logit models within a panel data modelling framework estimated from survey data. The survey was conducted of over 400 respondents in urban (Rochdale, Manchester) and rural (Melton Mowbray, Leicestershire) areas.Experience shows that it is particularly difficult to make DRT services financially viable. Of the DRT services investigated, those targeting airline or train passengers offer potential. However, they are in direct competition with the car, and so their success depends on the cost and availability of parking spaces. Some of the DRT schemes explored meet social needs, such as to access shopping facilities or hospitals, but they face cost challenges. In addition, institutional barriers for new DRT schemes need to be overcome in order to develop a sustainable local public transport system.

Abstract

The findings in this paper show the big potential contributions of automated cars to improvements of the"br" ecologic situation and social inclusion in the mobility market. These potential effects are however dependent on"br" the future use cases of this new technology and will only materialise if implemented as shared mobility. Based"br" on today's mobility behaviour, the number of vehicles will be reduced up to -80% if cars are shared, and up to"br" -90% if rides are shared as well. Analysing existing sharing initiatives, the implementation of shared automated"br" mobility can be seen ambivalently. On the one hand, a missing driver has some disadvantages as she/he plays an"br" important role if accompanying specific user groups such as the disabled, elderly or children. On the other hand,"br" the system would be much more efficient as cars are not sitting idle being parked at places not accessible to the"br" next client. In the absence of shared mobility models, there is a high risk of an increase of private car use as new"br" user groups are included, and as the convenience of traveling will increase in general through automated cars.

Abstract

The provision of traditional public transport services in rural areas have shown to be very inefficient and ineffective. In fact, rural areas are naturally categorized by low levels of population density leading to complex demand patterns (low levels and high spatial and temporal dispersion), which leads to low levels of service of conventional transport services (low frequencies, usage of old vehicles, etc). Demand Responsive Transport systems have been seen as an effective alternative solution already adopted in several countries. There are however some issues concerning DRT costs and benefits that still have to be addressed. In this research work an integrated analysis incorporating both internal and external costs is proposed aiming to support decision makers investigating the impacts and performance measures related to the adoption of a flexible transportation system solution. Additionally, DRT systems are highly dependent on the correct calibration of some organizational and functional parameters. In this paper, a comprehensive framework to support decision-makers in the design and planning of flexible transportation systems is proposed. The developed approach allows the simulation of different scenarios corresponding to different design alternative solutions. Accurate estimation of their global performance, in terms of both viability and sustainability, can be obtained providing effective support in the design and operational stages of a DRT system implementation in low density areas. Fundação para a Ciência e a Tecnologia (FCT) COMPETE - QREN