Award Abstract # 1247456
EAGER: Interactive Reconstruction and Visualization of Metropolitan-Scale Traffic

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
Initial Amendment Date: July 25, 2012
Latest Amendment Date: July 25, 2012
Award Number: 1247456
Award Instrument: Standard Grant
Program Manager: Ephraim Glinert
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2012
End Date: September 30, 2014 (Estimated)
Total Intended Award Amount: $99,995.00
Total Awarded Amount to Date: $99,995.00
Funds Obligated to Date: FY 2012 = $99,995.00
History of Investigator:
  • Ming Lin (Principal Investigator)
    lin@cs.umd.edu
Recipient Sponsored Research Office: University of North Carolina at Chapel Hill
104 AIRPORT DR STE 2200
CHAPEL HILL
NC  US  27599-5023
(919)966-3411
Sponsor Congressional District: 04
Primary Place of Performance: University of North Carolina at Chapel Hill
201 S. Coliumbia St
NC  US  27599-3175
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): D3LHU66KBLD5
Parent UEI: D3LHU66KBLD5
NSF Program(s): GRAPHICS & VISUALIZATION
Primary Program Source: 01001213DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7453, 7916
Program Element Code(s): 745300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Traffic congestion is a global challenge. Besides the obvious energy and environmental impacts, traffic congestion imposes tangible costs on society. It is unlikely that traditional physically-centered mitigation strategies by themselves will be successful or sustainable in the current economical and environmental climate. Numerous strategies have been proposed to construct Intelligent Transportation Systems (ITS), by incorporating sensing, information, and communication technologies in transportation infrastructure and vehicles. In this EAGER proposal, we present an early-concept exploration to investigate an innovative and transformative approach for ITS. We envision that this exploratory research could advance the next generation of ITSs by introducing a tightly-integrated real-time traffic simulation, estimation, and visualization for traffic management. We are developing novel hybrid methods for real-time flow estimation, traffic reconstruction and visualization, as well as designing GPU and many-core algorithms to accelerate the overall performance.

If successful, this research could enable adaptive route planning for vehicle guidance and navigational aid to alleviate traffic congestion through an algorithmic lens. The proposed unified framework also has the potential to provide computational advances for diverse applications, including regulating traffic, improved urban planning, transportation system design, virtual tourism, education, entertainment, surveillance, and emergency response. The set of pedagogical and outreach activities complement and extend the research impact through integrated education-research programs and effective dissemination of research results.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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David Wilkie, Jason Sewall, Ming C. Lin "Flow Reconstruction for Data-Driven Traffic Animation" ACM Transactions on Graphics , v.32 , 2013
David Wilkie, Jason Sewall, Ming C. Lin "Transforming GIS Data into Functional Road Models for Large-Scale Traffic Simulation" IEEE Transactions on Visualization and Computer Graphics (TVCG) , v.18 , 2012 , p.890
D. Wilkie, J. Sewall, and M. C. Lin "Flow Reconstruction for Data-Driven Traffic Animation" ACM Transactions on Graphics , v.32 , 2013 , p.89 10.1145/2461912.2462021

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Traffic congestion management is a global challenge.  Besides the obvious energy and environmental impacts, traffic congestion imposes tangible costs on society. It is unlikely that traditional physically-centered mitigation strategies by themselves will be successful or sustainable in the current economical and environmental climate.  Numerous strategies have been proposed to construct Intelligent Transportation Systems (ITS), by incorporating sensing, information, and communication technologies in transportation infrastructure and vehicles. Many of these efforts tend to perform off-line simulation and decoupled analysis. Most existing traffic simulations focus on either microscopic (e.g. agent-based simulation) or macroscopic (e.g. flow-like) behaviors; few have examined the intriguing interplay across different physical scales in a complex transportation system. Through networks of sensors, recent cutting-edge efforts can provide real-time traffic monitoring and limited vehicle-based rerouting, but do not offer immediate, coordinated system-level relief to the traffic congestion problem.

In this EAGER project, we advance the next generation of ITS by exploratory investigation of an innovative and transformative approach that integrates simultaneous simulation, reconstruction, and route planning of the metropolitan scale traffic.

 

INTELLECTUAL MERIT

The following major scientific contributions have been achieved during this project:

(1) a fast technique to reconstruct traffic flows from in-road sensor measurements;

(2) adaptive, self-aware traffic route planning algorithms that take the planned routes adopted by the current drivers as part of the future traffic prediction; and

(3) a new concept, called “Participatory Route Planning” that coordinates the traffic management through the user adoption and participation via mobile communication.

 

BROADER IMPACT

Applications and impacts of this work include regulating highway/arterial traffic, improved urban planning, civil and traffic engineering, transportation system design, highway and freeway layout, virtual tourism, education and entertainment, surveillance, and formulating emergency response strategies.

The resulting research has been demonstrated to thousands of K-12 students and senior members in the nearby communities and in NC, helping to attract K-12 students and enhance study opportunities for under-represented groups and women students. One Ph.D. student, David Wilkie, has been partially supported by this grant and completed his Ph.D. dissertation supported by this grant; and other undergraduate student gained valuable experience from this project and plans to continue for graduate study. Resulting software systems are to be posted online.  They are also under further development for designing accessible games for children with disabilities to learn how to cross streets.  Five refereed publications resulting from this project are disseminated through websites, courses, and international conferences.


Last Modified: 09/10/2014
Modified by: Ming C Lin