Ad hoc shared‐ride trip planning by mobile geosensor networks

Abstract

Abstract Recent developments in miniaturization of computing devices, in location‐sensing technology and in ubiquitous short‐range wireless networks enable new types of social behaviour. This paper investigates one novel application of these technologies, ad hoc inner‐urban shared‐ride trip planning: Transportation clients such as pedestrians are seeking ad hoc shared rides from transportation hosts such as private automobiles, buses, taxi cabs or trains. While centralized trip planners are challenged by assigning clients and hosts in an ad hoc manner, in particular for non‐scheduled hosts, we consider the transportation network as a mobile geosensor network of agents that interact locally by short‐range communication and heuristic wayfinding strategies. This approach is not only fully scalable; we can also demonstrate that with short‐range communication, and hence, incomplete transportation network knowledge a system still can deliver near‐to‐optimal trips. Keywords: Route planningIncomplete knowledgeMobile geosensor networksNegotiation strategiesHeuristic wayfinding strategies Acknowledgements Many thanks are due to Trang Cao and Lin Jie Guan, University of Melbourne, who have implemented the simulation and computed the results. The idea of local trip planning was born in a discussion with Monika Sester, University of Hannover. This work has been supported by the Australian Academy of Science with a travel grant for the first named author. The work of the second named author was partially supported by the National Science Foundation under NSF Grant Number EPS‐9983432. Notes 1. MitfahrzentraleTM: http://www.mitfahrzentrale.de 2. RideNowTM: http://www.ridenow.com 3. SuperShuttleTM: http://www.supershuttle.com