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Static traffic Assignment with Junction Modelling

Muijlwijk, Heleen (2012) Static traffic Assignment with Junction Modelling.

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Abstract:Modelling traffic consists roughly of four steps, this is known as the ‘four-step model’. The first step is ‘trip generation’. It determines the frequency of trips that are going in and out of zones as a function of socio-economic data. For example, a zone containing a lot of shops will generate many trips going into that zone. The second step is ‘trip distribution’. It matches origins and destinations, in such a way that it determines how much travellers will be travelling from a specific origin to a specific destination. Thus a trip matrix is obtained. Often a gravity model is used in this step, based on the fact that masses attract each other: the bigger the mass (higher frequency of trips) and the smaller the distance between the masses (smaller distance between origins and destinations), the bigger the attraction (more trips are made). The third step is ‘modal split’, where the trips are assigned to different modes, for example cars, bicycles or public transport. The fourth and final step is the traffic assignment. It determines which routes will be chosen by travellers, given their origins and destinations. In this step the travellers are ‘placed’ on the network, and a resulting load on every road is obtained. This last step, known as the Traffic Assignment Problem (TAP), is the subject of this study. The assignment is based on some assumptions on the network. Firstly, we can assume congestion in the network, meaning that the travel time increases when it gets busier. If we ignore congestion, the travel time is the same, regardless how busy it is. Secondly, we can assume that travellers have perfect knowledge about the network and the travel times, so everyone knows what the shortest routes are and agrees about that. In this case we deal with a deterministic model. Or we can assume that travellers may have different perceptions about the network and their travel times, this is a stochastic model.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:81 education, teaching
Programme:Science Education and Communication MSc (60708)
Link to this item:http://purl.utwente.nl/essays/64399
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