Monthly Archives: November 2013

An opportunistic client user interface to support centralized ride share planning

Rigby, M., Kr├╝ger, A., Winter, S. (2013), An opportunistic client user interface to support centralized ride share planning, 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2013). ACM, Orlando, Florida, USA.

Existing ride sharing systems for commuting in urban environments are rigid. They rely on the communication of discrete, spatio-temporal constraints from both vehicle and client to perform ride-matching. From a client user perspective these approaches are problematic, leading to location-privacy issues and the use of additional communication channels for ad-hoc negotiation which cannot be immediately quantified. To account for these aspects, we develop a dynamic, intuitive interface technique called launch pads and a centralized system architecture, which together simplify the ride-matching process whilst preserving location-privacy. The results of two experiments reveal the latent potential existing within ride sharing systems if vehicle flexibility is quantified and incorporated into a representation of accessibility. The communication via launch pads provides a client with means to fully exploit this potential.

Please contact one of the authors for a copy.

Determining the Viability of a Demand-Responsive Transport System under Varying Demand Scenarios

Ronald, N., Thompson, R., Haasz, J., Winter, S. (2013), Determining the Viability of a Demand-Responsive Transport System under Varying Demand Scenarios, 6th ACM SIGSPATIAL International Workshop on Computational Transportation Science. ACM, Orlando, Florida, USA.

Collaborative transportation has been proposed as a potential solution to decrease congestion, reduce environmental effects of transport, and provide transportation options to those with no or restricted travel options. One such system is demand-responsive transport, in which passengers share a vehicle, usually a bus, but can be picked up or dropped off at a passenger-specified location and time. However, as these systems are expensive to implement and require long trials in order to gain traction, effective simulation is required in order to explore their viability before implementation. Although previous work has concentrated on the number of trip requests, the spatial distribution of these requests has not been considered. This paper explores four spatially-varying demand patterns — random, a many-to-one scenario, all short distance trips, all long distance trips — using a simulation of an ad-hoc demand-responsive bus system. It is shown that along with the number of trip requests and the requested trip distances, the spatial distribution of passengers does indeed have an effect on the level of service.

Please contact one of the authors for a copy.