Prediction of Traffic Flow at the Boundary of a Motorway Network

• Published in: IEEE transactions on intelligent transportation systems Vol. 15; no. 1; pp. 214 - 227
• Main Authors: Yubin Wang, Van Schuppen, Jan H., Vrancken, Jos
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive algorithms; Adaptive prediction; Algorithm design and analysis; Algorithms; Boundaries; Computational modeling; Inflow; Kalman filters; Motorways; Networks; Prediction algorithms; Predictive models; Roads; short-term traffic flow forecasting; time-series model; traffic demand management; Traffic engineering; Traffic flow
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2013.2278192

For online traffic control at traffic control centers, there is a need for predictions of the traffic flow during a short horizon, for example, 30 min ahead. For this effort, predictions are needed of the traffic inflow into the network at motorways on the network boundary and at on-ramps. This paper presents an adaptive prediction algorithm for the inflows into the network in regular traffic situations based on stochastic control theory. The prediction algorithm is based on an adaptive prediction algorithm of T. Bohlin. The algorithm is designed and tested on traffic flow data of the ring road of Amsterdam. The results show that the algorithm provides robust predictions of traffic demand with relatively small errors for the next 30 min in a large-scale real-time environment.