Governments worldwide are planning car-free policies to increase the livability of cities. However, car-free policies often face opposition from local stakeholders, and policy-makers often lack relevant model indicators to represent all stakeholder interests in their ex-ante car-free policy evaluations. Well-being (Dutch: Brede Welvaart) indicators can be more relevant for the various stakeholder interests in car-free policies by covering aspects in the domains of living environment, accessibility, safety and health. This thesis investigates how relevant well-being indicators can be selected and operationalised for the ex-ante evaluation of car-free policies. A well-being indicator selection process was developed and applied to a case study in the Oude Westen neighbourhood in Rotterdam. This process involved conducting thirteen semi-structured stakeholder interviews. The resulting stakeholder interests were analysed to determine the relevant aspects of well-being and the relevant indicators for these aspects. From the shortlist of relevant indicators, three indicators were selected and operationalised in this thesis. At last, two validation interviews were conducted to validate the results of this case study and the developed indicator selection process. The most relevant stakeholders - municipality, local residents, and local business owners - were selected to be involved in the well-being indicator selection process in the case study. Based on their interests, the most relevant aspects of well-being were found to be the use of space, accessibility of mobility options, accessibility of activities, traffic safety, and noise pollution. This resulted in the operationalisation of three indicators: the use of space for car parking, the number of mobility options, and the traffic mix safety warning. While the small sample size does not allow for generalisation of the case study results, the results of this thesis do show that the well-being indicator selection process can yield relevant indicators of well-being and that this process can be applied in practice. The operationalised indicators can be relevant to represent stakeholder interests in car-free policy evaluation and can be applied to other cases as well. However, the relevance of the indicators does depend on the type of policy and the stage of the planning process. Using well-being indicators in policy evaluation can enhance the relatability of the evaluation results for stakeholders and potentially increase stakeholder support for policies.

Many municipalities try to encourage cycling in their cities to increase the use of sustainable modes of transport and decrease congestion. They therefore implement innovative traffic solutions such as `green wave'-apps for cyclists. These `green wave'-apps influence the green phase of traffic lights by requesting a green light earlier than conventional detectors would. These apps have already been implemented in several municipalities in the Netherlands and Germany, but not much research has been done into this kind of apps. The goal of this thesis was to determine how these apps can contribute to the cycling experience and benefit both cyclists and municipalities. This thesis involved a literature review, theoretical case studies into the potential effects of the apps, interviews with municipal employees and app developers, and a small survey among app users. This research showed that when the request of a green light can be granted immediately, the use of a `green wave'-app can decrease the travel time of an average cyclist with up to 4.4 seconds per intersection. When an intersection already has more than one detection loop for cyclists, the advantages of using a `green wave'-app are more noticeable for the faster cyclists. Interviews with municipalities showed that the few reactions they got from users of the apps were mainly positive, but for most cities, specific results of the apps are not yet known due to a low number of users and a lack of research. Only in Enschede and in Marburg (Germany), a decrease in average waiting times for cyclists seemed to be found in research. The respondents to the survey showed mixed experiences, which was in line with the results of a survey conducted in Enschede. Some respondents did not experience benefits from using the app and stopped using it. More frequent users more often seemed to experience an increase in the number of times they got an early green light while using the app. Suggestions from respondents for possible improvements of the apps mainly focused on the implementation at more intersections. Municipalities saw possible improvements in the feedback to the users in the app. More information about where and when a cyclist got an early green light while using the `green wave'-app could increase the transparency of the app and show users the benefits from using it. The results indicate that the existing `green wave'-apps for cyclists can contribute positively to the experience of cycling and already seem to decrease waiting times for cyclists in some cities. This more positive cycling experience could theoretically contribute to the popularity of cycling and help municipalities encouraging bike usage. However, experiences of cyclists are not all positive. The suggested improvements of the apps could help to improve user experiences and further increase the number of users. Further research could simulate the impact of the use of these apps on traffic flows at intersections or look at the importance of the route prediction compared to only GPS-tracking.