A team of Rutgers researchers led by VTC’s Hannah Younes analyzed the effect of a bicycle lane on traffic speeds using computer vision techniques.

A team of Rutgers researchers led by VTC’s Hannah Younes analyzed the effect of a bicycle lane on traffic speeds using computer vision techniques.
In this study, researchers Hannah Younes, Robert B. Noland, and Clinton J. Andrews used traffic camera footage to observe the behavior of over 700 shared e-scooters and privately owned bicycles in Asbury Park, New Jersey. The authors discuss policy implications with regard to safety and gender differences between the two modes of transit.
The results of this pilot data collection effort provide insights on the potential use of the latest sensor technology and computer vision algorithms to understand travel behavior for new and emerging transportation modes.
Objective While fatal crashes are available through the Fatality Analysis Reporting System (FARS) and are readily available to the public, many states do not make their crash data easily accessible for the public and the research community. The public has an interest...
Through this research, NJ TRANSIT sought to understand how women and members of the lesbian, gay, bisexual, transgender, queer plus community, sometimes referred to as sexual and gender minorities (SGMs) travel on NJ TRANSIT so the agency can provide better...
Recent advances in biometric sensing technologies, such as eye tracking, heart rate trackers, and galvanic skin response (GSR) sensors, offer new opportunities to measure pedestrian stress level and their travel experiences in real-time. Uncertainty remains about...
Background Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic...