Workshop On Intelligent Transportation: Technology, Trends and Practices in Next-Gen Traffic Management

Workshop Goals

The goal of the workshop is to identify existing issues and challenges, and disseminate research ideas for next generation, intelligent traffic monitoring and management systems. The workshop will feature keynote addresses, short presentations and panel discussion by eminent researchers, federal agency program officers, and industry stakeholders focusing on intelligent transportation technology, best practices, and future trends. The workshop is intended for faculty, researchers, students and practitioners interested in smart and autonomous systems, cyber physical systems and related areas including artificial intelligence, wireless communication, and energy-aware computing - focusing around the theme of intelligent transportation and traffic management.

Workshop Organizers

  • Prithviraj (Raj) Dasgupta Professor, Computer Science Department, University of Nebraska, Omaha
  • Hamid Sharif Professor, Electrical and Computer Engineering Department, University of Nebraska-Lincoln
  • Aemal Khattak Professor, Civil Engineering Department, University of Nebraska-Lincoln

Workshop Timeline and Agenda

The workshop will be held in Omaha, Nebraska in the first or second week of April 2018. Exact dates and agenda will be announced on this Website.

Vision

Our vision is to develop novel techniques and algorithms that will enable multiple, mobile air-borne sensors (e.g., camera, LIDAR) integrated on unmanned aerial vehicles (UAVs), and ground sensors located at strategic locations (e.g., busy traffic intersections, inside traffic tunnels) to autonomously and intelligently coordinate with each other and with central command and control centers via wireless communication, towards collecting real-time traffic information and using that information to pro-actively improve traffic congestion.

Our team's objective is to focus on three inter-disciplinary research areas towards achieving our vision:

  • Artificial intelligence(AI)-based real-time coordination techniques between aerial and ground sensor nodes for dynamic asset (mobile sensor) allocation to achieve improved coverage and surveillance of traffic movement within a region of interest.
  • Energy-aware, wireless communication strategies and protocols to enable robust, reliable and secure information exchange between aerial-ground sensor nodes for seamless operation of system in zero to low communication zones.
  • Urban traffic data collection using the aforementioned techniques and analysis to proactively mitigate traffic congestion situations.

Acknowledgement

The organizers are grateful to Nebraska Research Initiative - NU Collaboration Initiative Planning grant for sponsoring the workshop.