Using biometric data to make urban infrastructure safer

A new study focuses on utilizing biometric data to evaluate urban infrastructure safety and prevent accidents.

The COVID-19 situation enabled people to be less depended on public transport and utilize bikes or walk for daily commuting. Unfortunately, an increase in accidents was observed. The study emphasizes the need to develop proactive techniques to make the existing urban infrastructure safer for people.

The safety of urban infrastructure has been evaluated via static data such as crashes or fatality rates. This statistical approach is the traditional manner to determine the risk of the existing infrastructure (e.g., crossing a road) and has resulted in its categorization into low or high hazard regions. However, the new research suggests that the evaluation of safety can be much more precise if individual-based metrics are incorporated. Such an endeavor would aid in making urban infrastructure safer for the all the people involved (e.g., drivers, pedestrians, bicyclists etc.).

The current approach used in transportation infrastructure in the United States (where the study focuses) suggests that an intervention at an unsafe crossing will be considered if the crossing is crowded enough accommodating 90-100 pedestrians per hour or if at least 5 accidents occur. Dr. Megan Ryerson, lead author of the study and Associate Dean for Research, Weitzman School at the University of Pennsylvania, is not willing to wait for such accidents to strike so that measures can be taken. Instead, she suggests that we should be reactive in safety planning of infrastructure. She also emphasizes that the current technological means and analytical tools have significantly developed over the past years and innovative approaches to use the data are available.

In 2018, the research team employed 39 cyclists that travelled certain routes in Philadelphia. The riders were equipped with a specially designed camera and a gyroscope that took 100 measures per second. The routes that were selected presented various safety features from protected bike lanes to completely unprotected paths. The purpose of this mixture was to enable the people involved in the tests to experience “a range of transportation-infrastructure designs which may elicit different stress and cogitative workload responses”.

The team derived a correlation between increased biometric responses and regions where high number of accidents occur. The authors suggest that, in places where cognitive workload is required, an individual is more prone to pay less attention to new information and, thus, accidents are less probable to be avoided. Moreover, scientists found out that there are inconvenient areas where people are stressed. Those areas are the same for people of low or high experience in using the routes and solely depend on the infrastructure design standards.

Conclusively, the study emphasizes the need for urban infrastructure safety design to be more proactive. Current safety measures implementation comes after accidents occur but, the existing technology enables preventive works. More biometric data collected in problematic areas will result in better understanding of where and how to apply safety measures.

Sources: Ryenson et al. (2021) UPENN