Loading Events
  • This event has passed.

Developing the CAV Living Lab at CAIT’s DataCity Smart Mobility Testing Ground

  • February 23, 2023
  • 2:00 pm–3:00 pm

Course Description: 

The DataCity Smart Mobility Testing Ground is a 2.4-mile multi-modal corridor “living laboratory” in downtown New Brunswick, NJ, for collecting multi-modal smart-mobility data that will help the region improve safety, congestion, and equity in its transportation systems, while also establishing NJ as a hub for R&D in the growing Connected and Autonomous Vehicle industry.

DataCity is equipped with Self-Driving-Grade, high-resolution roadside sensors and computing devices to enable smart mobility services to all travelers on the corridor without the need for expensive on-board units or high-end vehicles. This provides researchers at Rutgers CAIT, and project partners at Middlesex County and NJDOT, with operational, real-time smart mobility data to analyze and develop tools, while also providing high-resolution datasets for private sector R&D.

In this webinar, Project Manager Dr. Peter Jin will discuss the status of DataCity and its implementation throughout the test corridor, analyze data collected from the project so far, and layout next steps in the DataCity program.

Learning Objectives:

  1. Learn about the DataCity project and its installation throughout the New Brunswick test corridor.
  2. Analyze CAV and smart mobility data collected so far through the DataCity project.
  3. Learn about opportunities for both private industry and local agency engagement in the DataCity program.

Intended Audience:

Administrators, engineers, planners.






Dr. Peter Jin, Associate Professor in the Department of Civil and Environmental Engineering at Rutgers, and a CAIT researcher.






Register Now

Withdrawal Policy: If you find yourself unable to attend a class for any reason, please submit a withdrawal request by emailing caitregistrar@soe.rutgers.edu. To be eligible for a refund for fee-based classes, you must email a withdrawal request at least 72 hours before class begins. If no withdrawal request is made, the nonrefundable and nontransferable program fee will be charged to your account.

Privacy Policy: The personal information we collect when you register for a program will not be disclosed to any outside parties. We use personal information for purposes of administering our business activities and providing customer service. We may also use the information we collect to notify you about important services and offerings we think you will find valuable. We are not responsible for the practices employed by websites linked to or from our website or the information or content contained therein.

nighttime work zone with police and traffic