Dynamic Updating of Inter-Urban Traffic Network Models Using Conditional Independence Relationships
Traffic counts from conductance loops embedded in the road surface of motorway networks are now being wired to local and distant processors. The loops generate a stream of volumes and velocities, classified by vehicle type and lane, at a large number of monitoring stations on the network. Ways of exploiting this stochastic information, in particular for estimating current and predicting future travel times, are discussed.
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- Dempster, A.P. (1990). In Oliver, R.M. and Smith, J.Q. (eds) Influence diagrams, belief nets and decision analysis. Wiley: Chichester.Google Scholar
- Harvey, A.C. (1989). Forecasting, structural time series models and the Kalman filter. C.U.P.: Cambridge.Google Scholar
- Papageorgiou, M. (1991). Concise Encyclopedia of Traffic and Transportation Systems. Pergamon Press: Oxford.Google Scholar
- Whittaker, J. (1990). Graphical Models in Applied Multivariate Statistics. Wiley: Chichester.Google Scholar
- Whittaker, J. and Garside, S. (1993). State space models for dynamic traffic networks. in Gunn, H. DYNA-DRIVE II project V2036 Annual Project Review Report-Part A Section 2. Submitted to EC RandD Program Telematic Systems in the Area of Transport.Google Scholar