Short-term Travel-time Prediction on Highway: A Review on Model-based Approach

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Emerging technologies provide a venue on which on-line traffic controls and management systems can be implemented. For such applications, having access to accurate predictions on travel-times are mandatory for their successful operations. Transportation engineers have developed numerous approaches including model-based approaches. The model-based approaches consider underlying traffic mechanisms and behaviors in developing the prediction procedures and they are logically intuitive unlike datadriven approaches. Because of this explanation power, the model-based approaches have been developed for the on-line control purposes. For departments of transportation (DOTs), it is still a challenge to choose a specific approach that meets their requirements. In efforts to develop a unique guideline for transportation engineers and decision makers when considering for implementing modelbased approaches for highways, this paper reviews model-based travel-time prediction approaches by classifying them into four categories according to the level of details involved in the model: Macroscopic, Mesoscopic, CA-based, and Microscopic. Then each method is evaluated from five main perspectives: Prediction range, Accuracy, Efficiency, Applicability, and Robustness. Finally, this paper concludes with evaluations of model-based approaches in general and discusses them in relation to data-driven approaches along with future research directions.
Publisher
KOREAN SOCIETY OF CIVIL ENGINEERS-KSCE
Issue Date
2018-01
Language
English
Article Type
Review
Keywords

CELL TRANSMISSION MODEL; TRAFFIC FLOW; NEURAL-NETWORKS; MISSING DATA; SIMULATION; FRAMEWORK; AUTOMATA; METANET; SYSTEM; WAVES

Citation

KSCE JOURNAL OF CIVIL ENGINEERING, v.22, no.1, pp.298 - 310

ISSN
1226-7988
DOI
10.1007/s12205-017-0535-8
URI
http://hdl.handle.net/10203/238758
Appears in Collection
GT-Journal Papers(저널논문)CE-Journal Papers(저널논문)
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