Herd Routes: A Preventative IoT-Based System for Improving Female Pedestrian Safety on City Streets

Woodburn, Madeleine, Griggs, Wynita M., Marecek, Jakub, Shorten, Robert N.

arXiv.org Artificial Intelligence 

--Over two thirds of women of all ages in the UK have experienced some form of sexual harassment in a public space. Recent tragic incidents involving female pedestrians have highlighted some of the personal safety issues that women still face in cities today. There exist many popular location-based safety applications as a result of this; however, these applications tend to take a reactive approach where action is taken only after an incident has occurred. This paper proposes a preventative approach to the problem by creating safer public environments through societal incentivisation. The proposed system, called "Herd Routes ", improves the safety of female pedestrians by generating busier pedestrian routes as a result of route incen-tivisation. A novel application of distributed ledgers is proposed to provide security and trust, a record of system users' locations and IDs, and a platform for token exchange. A proof-of-concept was developed using the simulation package SUMO (Simulation of Urban Mobility), and a smartphone app. With positive results from the initial testing of the proof-of-concept, further development could significantly contribute towards creating safer pedestrian routes through cities, and tackle the societal change that is required to improve female pedestrian safety in the long term. Emales of all ages face gender-inequities in every day life, and the associated feelings of compromised safety and fearfulness that can arise. Of course, in these situations, women do as much as they can to prioritise their personal safety. Notably, women approach walking through cities with extreme caution, especially at night. In London, for example, there are ongoing initiatives such as the UN Women's Global initiative of "Safe Cities and Safe Public Spaces for Women and Girls", which commits to identifying gender-responsive, locally relevant and owned interventions [1].

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found