CPS: Synergy: Collaborative Research: A CPS for Proactive Traffic Management to Enhance Mobility and Sustainability


The objective of the project is to demonstrate the synergistic use of a cyber-physical infrastructure consisting of smart-phone devices; cloud computing, wireless communication, and intelligent transportation systems to manage vehicles in the complex urban network – through the use of traffic controls, route advisories and road pricing – to jointly optimize drivers’ mobility and the sustainability goals of reducing energy usage and improving air quality. The system being developed, MIDAS-CPS, is to proactively manage the interacting traffic demand and the available transportation supply. A key element of MIDAS-CPS is the data collection and display device PICT that collects each participating driver’s vehicle position, forward images from the vehicle’s dashboard, and communication time stamps, and then displays visualizations of predicted queues ahead, route advisories, relevant road/lane prices, and available parking and costs.

Given the increasing congestion in most of the urban areas, and the rising costs of constructing traffic control facilities and implementing highway hardware, MIDAS-CPS could revolutionize the way traffic is managed on the urban network since all computing is done via clouds and the drivers instantly get in- vehicle advisories with graphical visualizations of predicted conditions. It is anticipated this would lead to improved road safety and lesser drive stress, besides the designed benefits on the environment, energy consumption, congestion mitigation, and driver mobility. This multidisciplinary project is at the cutting edge in several areas: real-time image processing, real-time traffic prediction and supply/demand management, and cloud computing. Its educational impacts include enhancements of curricula and laboratory experiences at participating universities, workforce development, and student diversity. Additional information on the project is available at midas-cps.mobicloud.asu.edu.

Progress so far:

1. Developed a simulation platform that generates type of data that would come from an operational PICT device, for testing algorithms and data management methods;

2. Developed MobiCloud for serving data collection, data management and computing activities, within a secure environment;

3. Developed image processing and visual computing system to identify vehicles and their lane- based position from dashboard images.

4. Developed differentiated congestion pricing schemes for congestion mitigation

5. Currently developing lane-based traffic estimation and prediction algorithms using a Lagrangian spatial coordinate system;

6. Currently developing  dynamic congestion pricing schemes to penalize or  reward drivers  to influence route choices and/or travel demand;

7. Currently developing smartphone-based parking management system

8. Currently developing variable speed limits for safety and congestion mitigation.

9. Currently developing wireless based approaches for controlling traffic signals, ramp meters and advisory signs to control traffic from cloud-based traffic management servers.

  • Arizona State University
  • Cloud Computing
  • Congestion Pricing
  • Image Processing
  • Real-Time Traffic Control
  • Traffic Prediction
  • University of Florida
  • Automotive
  • CPS Domains
  • Transportation Systems Sector
  • Control
  • Platforms
  • Critical Infrastructure
  • Real-Time Coordination
  • Wireless Sensing and Actuation
  • Simulation
  • Transportation
  • CPS Technologies
  • Education
  • Foundations
  • National CPS PI Meeting 2014
  • 2014
  • Abstract
  • Poster
  • Academia
  • CPSPI MTG 2014 Posters, Videos and Abstracts
Submitted by Pitu Michandani on