The urban transportation infrastructure that we have inherited from previous generations is centered largely around the needs of vehicular traffic, with little or no regard to accommodating the needs of a growing pedestrian population. One of the key challenges in enabling smart urban communities lies in integrating pedestrians’ needs into the design of the urban infrastructure. For example, lack of timely support to cross the streets at intersections, particularly in inclement weather conditions, frustrates many pedestrians and is conducive to jaywalking, a well-documented source of pedestrian fatalities in big cities. It is, therefore, of a fundamental importance to provide pedestrian-centric services, particularly for vulnerable pedestrians such as children, the elderly, and the disabled. This proposal aims to develop and build CrossGuard, a system which will make crossing at intersections safer and, in the process, elevate pedestrians' quality of experience. CrossGuard will explore new opportunities available at the nexus of intelligent infrastructure, data analytics, intelligent sensing, and engaged pedestrians towards Vision Zero, a world-wide initiative that aims for zero traffic fatalities. The design of CrossGuard is inspired by human crossing guards, often stationed at busy intersections, most notably near schools. Just like a vigilant crossing guard, CrossGuard will anticipate pedestrian needs and accommodate them promptly and effectively. We expect this project to have a profound and lasting societal impact.
The objectives of CrossGuard will be realized via the exploration of four research questions: (1) Investigating and developing an understanding of the challenges facing the pedestrian community; (2) Designing algorithms to identify vulnerable pedestrians and developing stochastic models for ensuring that they can cross safely; (3) Developing sensing modalities and resource allocation strategies for the successful provisioning of CrossGuard’s services; and (4) Expanding CrossGuard to non-signalized intersections.
The team will actively engage citizens and officials from the cities of Norfolk and Virginia Beach in a meaningful dialogue via focus groups and workshops. They will also make efforts to ensure participation from a representative cross-section of the citizens, particularly parents of school-age children, the elderly, and people with disabilities. The team envisions that the wealth of real-time traffic data collected in conjunction with perceived traffic trends will make the seamless integration of pedestrian and vehicular traffic possible. In turn, this will offer new opportunity for connected urban spaces, and will drastically reduce traffic accidents involving pedestrians, especially children.
Abstract
Shubham Jain
I am an Assistant Professor in the Computer Science Department at Stony Brook University.
My research interests lie at the intersection of smart environments and cyber-physical systems (CPS), particularly in building software and architectural support for enabling large-scale analytics on pervasive sensing devices. My research has enabled ubiquitous devices to expand their role and innovate new services, ranging from large-scale video analytics to pedestrian safety. I am also interested in using wearable sensors for enabling low-cost scalable monitoring of health parameters.
Prior to this (Fall 2017 - Summer 2020), I was an Assistant professor in the Department of Computer Science at Old Dominion University. I received my PhD in Electrical and Computer Engineering at Winlab, Rutgers University, in June 2017.
Performance Period: 10/01/2020 - 02/28/2021
Institution: Old Dominion University Research Foundation
Award Number: 1951789
Core Areas:
Transportation and Personal Mobility