Multimodal Public Transit Trip Planner with Real-time Transit Data

Abstract

Trip planner is a smart travel assistance tool which provides pre-trip travel plan information to the commuter for the given origin and destination stops. It is built-up with information such as road network and vehicles’ schedule from various transport agencies. The schedules are static and deviates much in actual due to delays caused by dwell time, traffic congestion and accidents etc. Therefore, many real-time trip planners were developed to produce more accurate plans in terms of time and transit vehicles which use data from Global Positioning System (GPS) enabled vehicles. However, the methodologies for vehicle positioning in real-time, dealing with interrupted GPS signals and just-in-time update of transit network is still not crystallized. Mostly the vehicle positioning is handled by a third party. In addition, most of the real-time planners do not consider arterial routes. In this paper we present development of a multimodal intracity transit trip planner using public transport. It incorporates the delays into the transit network at real-time to minimize the gap of our prediction model. K- shortest path algorithm is being used to compute multi-criterion optimal plans. Here we consider both delays in all routes including arterial ones and frequently missing GPS signals. Our system handles all these with some heuristics and simulation. Besides the web interface, trip planning can also be done by sending Short Messaging Service (SMS) from any mobile phone to the server. The results have shown that the system produces plans which are acceptable in terms of response time, feasibility and accuracy.