University of Twente Student Theses


Traffic modelling aimed at assessing well-being

Vink, J. (2024) Traffic modelling aimed at assessing well-being.

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Abstract:Background: Traffic micro-simulation models are an important tool for assessing (future) traffic scenarios. A trend has emerged in which there is more attention towards well-being (Dutch: ‘brede welvaart’) in policy-making. Including well-being in mobility-related policies is likely to become a requirement for future policies. Many analyses regarding mobility are executed using traffic micro-simulation software. Therefore, there will be a need for a possibility to assess well-being using this type of software. At the moment there is no such method available, which is why a framework is set up to allow for an assessment of well-being using traffic simulation models. Method: As well-being is a very broad term first it is investigated what the mobility aspect of it actually entails. This mobility aspect consists of four dimensions, which are living environment, accessibility, safety and health. For the assessment of well-being, seven indicators are defined and a relation between the indicators and the simulation software is defined. These seven indicators represent three of the four dimensions directly, with the missing dimension of health indirectly involved in multiple indicators. These seven indicators are emissions – gases, emissions – noise, paved surface area, travel time loss per person, the attractiveness of public transport, the attractiveness of active modes, and traffic safety. Using a survey among traffic engineers it is investigated whether the seven indicators are regarded as equally important. Due to the great variance between responses and the fact that different situations require different rankings of indicators, it is necessary to establish a dedicated ranking of indicators for every study area. There is no general relative importance between indicators available that can be applied universally. Framework: The framework that is created consists of three separate parts, although for each part a distinction is made whether results for an indicator can be obtained using traffic simulation software or not. For the simulation indicators, different variants for the same study area need to be compared. The first part for simulation is gathering results for the seven indicators by making use of traffic simulation software. These results need to be normalized so they can be compared to each other. The second part is the establishment of the relative importance of indicators. This should be achieved by communicating with local authorities, local residents and the input of an experienced traffic engineer. The third and final part is combining the results of the first two parts to obtain a well-being score for the simulation part. For the non-simulation indicators, the three parts are very similar. For the first part data needs to be gathered instead of obtaining results. The second part is a priority list of indicators, rather than a list of factors per indicator. The third part also combines the outcomes of the first two parts to obtain the well-being score for the non-simulation indicators. The overall score resulting from the framework for well-being is the combination of both the simulation and non-simulation indicators. Discussion and conclusion: Well-being is a very broad term which makes it difficult to assess, even though only the mobility aspect of it is investigated. Seven indicators are a low amount to make a proper assessment. However, the seven indicators are well spread across the different dimensions of the mobility aspect. This makes the outcomes of the simulation part of the framework useful to gain insight into the impact of different variants on well-being. For the case study that is performed as an example of how the framework can be applied several assumptions are made that need closer inspection before the actual implementation of the framework. The impact of heavy traffic and the effect of variants on the modal split are not taken into account properly for the case study.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:55 traffic technology, transport technology, 56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
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