Data management and applications in a world-leading bus fleet
technology - automatic vehicle monitoring, place - europe, mode - bus, technology - passenger information, technology - geographic information systems
AVL system, Public transport applications, AVL data management, iBus, Bus performance monitoring
Automatic Vehicle Location (AVL) Systems are being introduced increasingly in many major cities around the world to improve the efficiency of our road-based passenger transport systems. Satellite-based location and communication systems, particularly the Global Positioning System (GPS) have been the platform for AVL systems which are now supporting real-time passenger information (RTPI), fleet management and operations (FMOs) and public transport priorities (PTPs), to name three key applications. The process of real-time on-board bus location can result in a substantial database where the progress of the bus is stored typically on a second-by-second basis. This is necessary for the primary real-time applications such as those listed above (e.g. RTPI, FMO and PTP). In addition, it is clear that such data could have an array of ‘secondary’ purposes, including use off-line for improving scheduling efficiency and for automatic performance monitoring, thus reducing or removing the need for manual on-street surveys. This paper looks at these and other innovative uses of AVL data for public transport, taking the recent iBus system in London as a current example of a modern AVL/GPS application in a capital city. It describes the data architecture and management in iBus and then illustrates two further examples of secondary data use – dwell time estimation and bus performance analysis. The paper concludes with a discussion of some key data management issues, including data quantity and quality, before drawing conclusions.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Hounsell, N.B., Shrestha, B.P., & Wong, A. (2012). Data management and applications in a world-leading bus fleet. Transportation Research Part C: Emerging Technologies, Vol. 22, pp. 76-87.