Determining the Market Uptake of Demand Responsive Transport Enabled Public Transport Service

Abstract

Demand responsive transport (DRT) alternatives offer improved mobility to travellers through station-to-destination or door-to-transit operations. In particular, door-to-transit DRT service acts as a feeder to major public transport hubs, making public transport more accessible and attractive to travellers. This work aims to study the mode choice behaviour of travellers between their current modes and a new service, which is a combination of DRT and public transport. The study is conducted in the Northern Beaches area of Sydney, Australia where DRT is expected to serve as a feeder to the newly introduced express bus service called B-Line. A stated preference (SP) experiment is designed where multiple-choice scenarios involving two modes, status quo (SQ) and the new service (combined DRT and public transit), are presented to the participants. The survey uses trip specific information obtained from Google API to form the attributes for the new service. The collected data are analysed using a latent class choice model (LCCM), which segments the observed sample into distinct groups where each group has its own taste and preferences towards the new service option. Results from the study reveal that one of the identified user segments shows 96 percent uptake towards the new service option, while the other user segment shows an uptake of 44 percent. Results also show that individuals making work trips are more likely to opt for the new service. Findings from this study can provide information to urban planners regarding the market uptake of DRT services. Furthermore, the findings can also help planners in implementing segment specific policies aimed at further improving uptake towards DRT along with public transport.

Optimizing Centralized Dispatching of Flexible Feeder Transit considering Transfer Coordination with Regular Public Transit

“…As shown in Figures 6-9, the subobjectives of the model, such as the successful response ratio (f 1 ), the passengers' average travel time (f 1 2 ), the average advanced or delay time of transfer (f 2 2 ), and the operating costs of a single passenger (f 3 ) solved by the GA algorithm were stable. Even with more demands, owing to the robustness of the proposed model and algorithm, the final results are considered reliable.…”

“…erefore, the proposed model structures the objective function of operation benefit as maximization of the successful response ratio, expressed as formula (1). For unified optimization, the minimization of the unsuccessful response ratio is given by formula (2).…”

“…Passenger costs comprise accounting and time costs. Accounting costs depend on the fare for flexible feeder transit, as time costs are reflected in travel time (f 1 2 ) and the advanced or delay time of transfer compared with reservation (f 2 2 ). Because of the public welfare part involved in public transport, the fare is subject to several restrictions; this is beyond the scope of this study.…”

“…Literature and Background Survey. In the past, providing door-to-door services (referred to as demand-responsive transport (DRT), Dial-a-Ride Transit (DART), and flexible transport service (FTS) [1][2][3]) has been trialed in many cities around the world. e concept of a flexible bus service system was originally proposed by Flusberg in 1976 [4].…”

Mobility Nodes as an Extension of the Idea of Transfer Nodes—Solutions for Smaller Rail Stations with an Example from Poland

“…A node could be a destination object for electric vehicles [7,8], demand-responsive transport [9], or autonomous driverless shuttle buses [10]. Railway stations, as nodes, represent "urban functional areas" [11] and increase real-estate prices [12].…”