Congratulations to Prof. Dimitris Metaxas and Prof. Desheng Zhang for their NSF research grant under the Smart and Connected Communities program.
This project titled “Making Micromobility Smarter and Safer” with a $1.5 million budget is led by Rutgers Bloustein School of Planning and Public Policy in collaboration with Rutgers faculty members from Transportation Planning, Civil Engineering, and Computer Science.
“Making Micromobility Smarter and Safer” will focus on the effects that increased use of e-scooters, sit-down scooters, e-bikes, and other options have on the safety of pedestrians and micromobility users. Road design favors automobiles resulting in 6,000 pedestrian deaths in 2018. This is a 14% increase from 2015 and a 27% increase from 2014. Contributing factors to pedestrian deaths include human behavior, road design, environmental conditions, and technology.
The objectives of this project are to (a) use new sensing methods to gather better data on what determines pedestrian and micro-mobility risk, (b) create tools that deliver more integrated solutions in collaboration with industry micro-mobility partner Veo, and (c) test the tools in the service of the needs of New Jersey communities including the Rutgers campuses, Highland Park, Asbury Park, Hoboken, and others. These tools will explicitly integrate both social and technology solutions to improve safety.
Project tasks include: (a) create an enhanced near-miss detection capability using multiple visual sensors and advanced computer vision techniques; (b) perform behavioral experiments using both traditional tools (signage, temporary road reconfigurations) and smart-city tools (sensor-equipped and networked mobile users and intersections); (c) conduct technological experiments integrated into a prototype mobile-phone-based app for pedestrians, e-scooters, e-bikes, and drivers; and (d) convene a community deliberation process that informs development of local smart transportation plans.
The research will utilize computer vision algorithms to accurately detect pedestrians, e-scooters, e-bikes, vehicles; measure trajectories (direction, velocity); measure near misses (deceleration, proximity, avoidance behavior); and distinguish key user attributes (clothing brightness, gender, race, size). It will use digital models of the built environment to improve the performance of the computer vision algorithms and allow spatially explicit tracking of different walkers, riders, and drivers. The second major contribution will develop an integrated risk reduction portfolio. Vulnerable elderly, children and under-represented minority pedestrians and cyclists will benefit because they are currently at disproportionate risk. The project will involve undergraduate and graduate students in the research activities through urban planning studio classes, multidisciplinary capstone design classes, the summer Rutgers’ Aresty Undergraduate Research Program, and the summer RISE (Research in Science and Engineering) program which introduces outstanding minority students to graduate-level research through summer jobs with research groups.
