Print Email Facebook Twitter The influence of adverse weather conditions on the probability of congestion on Dutch highways Title The influence of adverse weather conditions on the probability of congestion on Dutch highways Author Van Stralen, W.J.H. Contributor Van Wee, G.P. (mentor) Molin, E.J.E. (mentor) Bots, P.W.G. (mentor) Calvert, S.C. (mentor) Faculty Technology, Policy and Management Department Transport and Logistics Programme SEPAM Date 2013-06-27 Abstract This study incorporates both the highway traffic demand change and the highway capacity reduction in the estimation of the congestion probability at Dutch highways as a result of adverse weather conditions. Congestion effects at the Dutch highways account for serious economic damage. Between May 2010 and April 2011 there were 68 million vehicle loss hours as a result of congestion (TNO, 2011). The external factor weather is widely acknowledged to contribute to the occurrence of congestion in two different ways. Firstly, weather conditions can influence traffic supply through a temporal reduction of capacity due to changes in driving behaviour. Secondly, weather conditions can influence highway traffic demand. A stated adaptation experiment has been conducted and a Panel Mixed Logit model is estimated to arrive at a highway traffic demand as a result of adverse weather. To examine the influence of precipitation on highway capacity it was chosen to estimate capacity distribution functions for dry weather, light rain and heavy rain based on the Product Limit Method. With the development of a generic model based on a cumulative normal distribution, breakdown probabilities can be calculated for any given traffic demand and capacity. Rainfall leads to a significant increase in probability of breakdown at bottleneck locations. A breakdown probability of 50% in dry weather will lead to an average breakdown probability of 86.7% in light rain and 77.4% in heavy rain conditions. The higher breakdown probability with light rainfall is the result of the increased traffic demand. The conclusion that can be drawn is that both traffic demand and highway capacity should always be incorporated in the analysis to come to accurate predictions regarding breakdown probabilities. Subject highway traffic demandhighway capacityadverse weather conditionsbreakdown probability Dutch highways To reference this document use: http://resolver.tudelft.nl/uuid:701f24a7-d9e9-48ef-bb65-973cc6c20efc Part of collection Student theses Document type master thesis Rights (c) 2013 Van Stralen, W.J.H. Files PDF Master_thesis_Wouter_van_ ... 511041.pdf 2.41 MB Close viewer /islandora/object/uuid:701f24a7-d9e9-48ef-bb65-973cc6c20efc/datastream/OBJ/view