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Study on demand forecasting and allocation of expressway emergency vehicle resource
KTH, School of Electrical Engineering (EES).
2014 (English)In: Journal of Computational Information Systems, ISSN 1553-9105, Vol. 10, no 10, 4205-4215 p.Article in journal (Refereed) Published
Abstract [en]

Emergency vehicles are the key resources of expressway for the rescue mission to traffic accidents. For optimal emergency vehicle resources allocation, an improved Case-Based Reasoning (CBR) and an allocation model are established. First, the effecting factors of traffic safety on expressway are analyzed to establish an accident hazard indicator system. A difference coefficient is introduced to improve Case-Based Reasoning for predicting the demand of emergency vehicle resources. Then, the resource allocation model is established based on the objective constrained optimization method, which tries to find the minimum rescue time with constraints such as road hazard, rescue time, resource demand, and the configuration result is obtained by adopting Particle Swarm Optimization (PSO). Finally, according to the study of a bridge case, it shows that the prediction error of resource demands becomes smaller by using the improved case-based reasoning method and the resource allocation results are reasonable through the calculation of objective constrained optimization model.

Place, publisher, year, edition, pages
2014. Vol. 10, no 10, 4205-4215 p.
Keyword [en]
Demand forecasting, Emergency vehicle resource, Expressway, Resource allocation
National Category
Other Engineering and Technologies
URN: urn:nbn:se:kth:diva-161771DOI: 10.12733/jcis10246ScopusID: 2-s2.0-84901829255OAI: diva2:795677

QC 20150317

Available from: 2015-03-17 Created: 2015-03-17 Last updated: 2015-03-17Bibliographically approved

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Shen, Tong
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