“Travel Time Prediction Methods for Dynamic Incident Handling”
Journal Title: International Journal of Scientific Research and Management - Year 2014, Vol 2, Issue 12
Abstract
Effective travel time prediction is of great importance for efficient real - time management of freight deliveries, especially in urban networks. This is due to the need for dynamic handling of unexpected events, which is an important factor for successful completion of a delivery schedule in a predefined time period. This chapter discusses the prediction results generated by two travel time estimation Methods that use historical and real - time data respectively. These methods are incorporated by the real - time fleet manageme nt system for the prediction of arrival time to the remaining customers. The first method follows the k - nn model, which relies on the non - parametric regr ession method that was analyzed , whereas the second one relies on an interpolation scheme which is empl oyed during the transmission of real - time data in fixed intervals. The study focuses on exploring the interaction of factors that affect prediction accuracy by modeling both prediction methods. The data employed are provided by real - life scenarios of a fre ight carrier and the experiments follow a 2 - level full factorial design approach.
Authors and Affiliations
Sanjay Singh
Keywords
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