Advanced public transport and intelligent transport systems: new modelling challenges
technology - intelligent transport systems, technology - passenger information, technology - geographic information systems, ridership - behaviour, ridership - demand, ridership - modelling, planning - travel demand management, planning - signage/information
Advanced traveller information systems, transit trip planners, transit operations control, transit system short-term forecasting, simulation-based transit assignment, individual path choice modelling, real-time transit reverse assignment
Transit system ‘big data’ collecting and processing, and bidirectional communication between transit travellers and information centres are emerging as two factors that enhance the tools supporting short-term forecasting of network status for transit operations control and for traveller information. However, the current methodologies applied in these tools do not seem to have reached the level of research in the field of transit network modelling. Therefore, several methodological issues connected to the development of such tools are analysed in this paper. These issues concern application and development of real-time on-board load short-term forecasting methods, real-time best path advice, real-time transit assignment modelling, individual path choice modelling, and real-time updating and upgrading of demand and supply model parameters.
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Nuzzolo, A., & Comi, A. (2016). Advanced public transport and intelligent transport systems: new modelling challenges. Transportmetrica A: Transport Science, Vol. 12(8), pp. 674-699.