Gender and Mobility: Utilising Smart City Technologies to Improve the Feeling of Safety in Pedestrian Women

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Women are disproportionately affected by feelings of unsafety when walking alone on the streets at night. Yet, current navigation systems such as Google Maps and Waze do not account for feelings of unsafety and only suggest the fastest route. Within the framework of Value-Sensitive Design - an approach that aims to include societal values in the design of technologies - this poses a value-infringement in the technology as it is not free of a certain gender bias. Current advancements within smart cities may alleviate the issue by creating a dynamic navigation system that utilises the data collected by smart city technologies to determine the “Safest Perceived Path” (SPP). This thesis proposes a pipeline for the calculation of an SPP so that it can be implemented in path-finding problems. The pipeline is realised in three steps; 1) a set of relevant factors that improve feelings of safety i.e. safety factors are determined and contextualised in research, namely “lighting”, “density”, “security”, “entrapment”, and “maintenance”; 2) proof-of concept (smart) technologies are presented that can measure the safety factors; 3) by means of an online survey, the weighting of each safety factor is obtained in order to determine to what extent the identified factors need to be considered when proposing the SPP . To retrieve the weights from the survey, Bayesian Multivariate Models were applied. The results showed that “lighting”, “density”, and “maintenance” were the most important safety factors in determining an SPP for both men and women. Possible limitations include the generalisability of the results. Furthermore, by accounting for an existing value-infringement in navigation systems, new value trade-offs may arise. Keywords: Smart City, Smart Technologies, Value-Sensitive Design, Gender Inequality, Freedom of (Gender) Bias, Navigation Systems, Graph Search, Artificial Intelligence, Fear of Crime, Pedestrian Mobility
Faculteit der Sociale Wetenschappen