Print Email Facebook Twitter Improving vehicle routing using traffic predictions Title Improving vehicle routing using traffic predictions Author Loof, P.C. Contributor Spaan, M.T.J. (mentor) Faculty Electrical Engineering, Mathematics and Computer Science Department Software and Computer Technology Programme Algorithmics Date 2014-08-14 Abstract Vehicle routing through road networks is an important topic of research: time and money can be saved by reducing traffic jams, which would also reduce the burden on the environment. The problem of minimizing the travel time for a vehicle trip is easy to grasp but hard to solve, it is a highly complex shortest path problem. Our goal is to show that routing advice can be improved by using historical traffic data to predict the traffic conditions in the nearby future. We introduce several algorithms that combine historical data with live data in a smart way, our algorithm set contains fixed path algorithms, adaptive path algorithms and policy algorithms. In order to test their performance we create historical scenarios and test scenarios using micro-simulations because they can produce network-wide traffic data. We evaluate the realism of the simulations and highlight the problems that are encountered when trying to mimic reality. The results of the routing algorithms are compared to obtain a good insight in the advantages and drawbacks of the different algorithm types. We show that the best algorithms clearly outperform an algorithm based on the concept of modern in-car routing devices, even when only a limited amount of live data is available, which clearly shows that routing advice can be significantly improved using traffic predictions. Subject traffic routingshortest path problemtraffic forecastingmicro-simulation To reference this document use: http://resolver.tudelft.nl/uuid:df10f760-6b11-4fea-aa99-309a3f10b4a4 Embargo date 2015-08-14 Part of collection Student theses Document type master thesis Rights (c) 2014 Loof, P.C. Files PDF thesis.pdf 716.13 KB Close viewer /islandora/object/uuid:df10f760-6b11-4fea-aa99-309a3f10b4a4/datastream/OBJ/view