Towards more train paths through early passenger intention inference

Abstract

© 2015 ATRF, Commonwealth of Australia. All rights reserved. In public train stations, the designed way finding tends to induce individuals to conform to specific egress patterns. Whilst this is desirable for a number of reasons, it can cumulate into congestion at specific points in the station. Which, in turn, can increase dwell time; for example, loading and unloading time increases with concentrations of people trying to load/unload onto the same carriage. Clearly, an influencing strategy that is more responsive to the current station situation could have advantages. Our prior research studies in Perth Station demonstrated the feasibility of reliably and predictably influencing passengers egress patterns in real time during operations. This capability suggests the possibility of active counterbalancing of the egress-alternatives while maintaining way finding. However, the prerequisite for such capability is the availability of knowledge of passenger's intention at a point in their journey where viable egress-alternatives to their destination exist. This work details an approach towards an early (in the passenger journey) passenger intention inference system necessary to enable active egress-alternative influencing. Our contextually grounded approach infers intention through reasoning upon observed system and passenger cues in conjunction with a-priori knowledge of how train stations are used. The empirical validation of our intention inference system, which was conducted with data acquired during operations on a platform in Brisbane’s Central train station in Queensland, is presented and discussed. The findings are then employed to argue the feasibility of an influencing system to reduce passenger congestion and the potential service impacts