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Partner Universities

National Institute for Advanced Transportation Technology

Physical Address:

875 Perimeter Dr, MS 0901
Moscow, ID 83844-0901

Phone: (208) 885-0576

Fax: (208) 885-2877

Email: niatt@uidaho.edu

Transportation Research Institute

Physical Address:

Department of Civil and Environmental Engineering
College of Engineering and Technology
Norfolk, Virginia 23529-0241

Phone: (757) 683-3753

Fax: (757) 683-5354

Email: mcetin@odu.edu

Physical Address:

L.C. Smith College of Engineering & Computer Science
223 Link Hall
Syracuse, NY 13244

Phone: (315) 443.2545

Email: omsalem@syr.edu

Innovative Transportation Research Institute

Physical Address:

College of Science & Technology
Texas Southern University
3100 Cleburne Avenue
Houston, Texas 77004-9986

Phone: (713) 313-7282

Fax: (713) 313-1856

Email: yu_lx@tsu.edu

Virginia Tech Transportation Institute

Physical Address:

3500 Transportation Research Plaza
Blacksburg, VA 24061

Phone: (540) 231-1500

Fax: (540) 231-1555

Email: hrakha@vtti.vt.edu

Recent Articles

Dynamic Travel Time Prediction Using Pattern Recognition

Authors: Hao Chen, Hesham A. Rakha & Catherine C. McGhee

TranLIVE Collaborator: Virginia Polytechnic Institute and State University

Description: Travel-time information is an essential part of Advanced Traveler Information Systems (ATISs) and Advanced Traffic Management Systems (ATMSs). A key component of these systems is the prediction of travel times. From the perspective of travelers such information may assist in making better route choice and departure time decisions. For transportation agencies these data provide criteria with which to better manage and control traffic to reduce congestion. This study proposes a dynamic travel time prediction algorithm that matches current traffic patterns to historical data.

Learn About Dynamic Travel Time Prediction Using Pattern Recognition >

A Short Range Vehicle to Infrastructure System at Work Zones and Intersections

Authors: Fengxiang Qiao, Jing Jia, and Lei Yu

TranLIVE Collaborator: Texas Southern University

Description: Traditional safety countermeasures at work zones include setting up special signs, installing barriers and a lower speed limit in work zones. For stop sign areas, usually our countermeasure is to remove all the obstructions. For signalized intersections, we usually improve the safety by setting up the signal lights in an optimized layout. However, many accidents still happen despite of these traditional methods. The purpose of this research is to identify how to improve the traffic safety and achieve better air quality in these areas by using RFID.

Learn About the Short Range Vehicle to Infrastructure System >

Is Smart Growth Associated with Reductions in CO2 Emissions?

Authors: Xin Wang, Asad Khattak, Yichi Zhang

TranLIVE Collaborator: Old Dominion University

Description: The transportation sector is the second largest contributor to human-generated CO2 emissions. A key goal of the US Department of Transportation is to implement environmentally sustainable policies that can reduce carbon emissions from transportation sources. Smart growth developments are characterized by compact, mixed use, greater network connectivity and alternative mode friendly environments. These features may encourage reductions in vehicle travel and emissions. A better understanding of travel behavior in conventional and smart growth communities is needed to inform policies and make informed decisions.

Learn About the Possible Smart Growth-CO2 Emissions Corollary >

What is the Level of Volatility in Instantaneous Driving Decisions?

Authors: Asad Khattak, Xin Wang, Jun Liu, Golnush Masghati-Amoli and Sanghoon Son

TranLIVE Collaborator: Old Dominion University

Description: Instantaneous driving decisions are part of incessant human behavior during driving, strongly affecting safety outcomes, energy consumption and tailpipe emissions. To accommodate changes in surrounding environment, drivers make instantaneous decisions, such as maintaining speed, accelerating, braking, maintaining acceleration or deceleration, or increasing the rate of acceleration or deceleration (referred to as jerk, which is the decision to change the marginal rate of acceleration and deceleration). These instantaneous decisions and their combinations result in driving volatility. This paper develops a framework for understanding instantaneous decisions and explores volatility in such decisions with the aim of developing a fundamental understanding of instantaneous decisions.

Learn About the Level of Volatility in Instantaneous Driving Decisions >

Partner Universities

National Institute for Advanced Transportation Technology

Physical Address:

875 Perimeter Dr, MS 0901
Moscow, ID 83844-0901

Phone: (208) 885-0576

Fax: (208) 885-2877

Email: niatt@uidaho.edu

Transportation Research Institute

Physical Address:

Department of Civil and Environmental Engineering
College of Engineering and Technology
Norfolk, Virginia 23529-0241

Phone: (757) 683-3753

Fax: (757) 683-5354

Email: mcetin@odu.edu

Physical Address:

L.C. Smith College of Engineering & Computer Science
223 Link Hall
Syracuse, NY 13244

Phone: (315) 443.2545

Email: omsalem@syr.edu

Innovative Transportation Research Institute

Physical Address:

College of Science & Technology
Texas Southern University
3100 Cleburne Avenue
Houston, Texas 77004-9986

Phone: (713) 313-7282

Fax: (713) 313-1856

Email: yu_lx@tsu.edu

Virginia Tech Transportation Institute

Physical Address:

3500 Transportation Research Plaza
Blacksburg, VA 24061

Phone: (540) 231-1500

Fax: (540) 231-1555

Email: hrakha@vtti.vt.edu