Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/33192
Title: STIMF: a smart traffic incident management framework
Authors: FARRAG, Siham 
Sahli, Nabil
EL HANSALI, Youssef 
Shakshuki, Elhadi M.
YASAR, Ansar 
Malik, Haroon
Advisors: Ansar
Issue Date: 2021
Publisher: 
Source: Journal of Ambient Intelligence and Humanized Computing, 12(1), p. 85-101
Abstract: Non-recurrent congestion, which is mainly due to traffic incidents, may seriously impact the performance and operation of a traffic system. Reacting quickly and in a uniform and structured way is vital. In particular, choosing the appropriate response strategy with only a short delay may mitigate the impact of incidents, improve traffic efficiency, and increase safety in the transportation system. This paper proposes STIMF: a smart traffic incident management framework to reduce the burden on traffic incident operators by assisting them in selecting the most appropriate response strategy when an incident occurs. STIMF includes two software systems: (a) a simulation environment used to evaluate traffic incident management strategies and (b) a fuzzy-logic inference system that allows the traffic operator to get prompt recommendations on the best response strategies based on the current context and conditions. Moreover, the STIMF framework also describes the process of preparing and building the simulation environment. To evaluate the proposed framework, we tested it on a section of the Muscat expressway in Oman.
Keywords: Traffic decision support system;Traffic incidents;Expert system;Fuzzy logic;Simulation
Document URI: http://hdl.handle.net/1942/33192
ISSN: 1868-5137
e-ISSN: 1868-5145
DOI: 10.1007/s12652-020-02853-8
ISI #: 000608685400002
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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