Dec 18, 2018
Photo by anyaberkut - Thinkstock Photos
Principal Investigator: Xianfeng (Terry) Yang, University of Utah
Learn more about this research by viewing the Executive Summary and the full Final Report on the Project Overview page, or sign up for the free January 24th webinar.

It can be expected that automated vehicles and human-driven vehicles will coexist in the transportation network for quite some time. In order to support various traffic control tasks it is critical to develop a reliable model to understand the real-time traffic patterns in this mixed environment. A new report from the National Institute for Transportation and Communities (NITC) contributes three new tools to help planners model freeway traffic with both connected automated vehicles (CAVs) and human-driven vehicles (HVs). 

RESEARCH TEAM

The project was led by Xianfeng (Terry)...

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Webinar: Modeling Freeway Traffic in a Mixed Environment: Connected and Human-Driven Vehicles - Terry Yang
Nov 29, 2018

 

PRESENTATION ARCHIVE

Miss the webinar or want a look back?

OVERVIEW

Although connected vehicles (CVs) will soon go beyond testbeds, CVs and human-driven vehicles (HVs) will co-exist over a long period. Hence, it is critical to consider the interactions between these two types of vehicles in traffic flow modeling. In this study, we aim to develop a macroscopic model to understand how CVs would impact HVs in the traffic stream. Grounded on the second-order traffic flow model, we study the relationships among flow, density, and speed by two sets of formulations for the groups of CVs and HVs, respectively. A set of friction factors, which indicate CVs' impact to HVs, are introduced to the speed equation for accounting CV speed impacts. Then extended Kalman Filter is employed to update both model parameters and friction factors in real-time. By using CVs trajectory data as measurements, the difference between CV average speed and overall traffic mean speed will be fully accounted. The proposed model will serve as a basis for designing CV-based traffic...

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A red car travels along a highway
Nov 15, 2018
Photo by Felix Tchverkin on Unsplash
Principal Investigator: Liming Wang, Portland State University
Learn more about this research by viewing related publications, open-source data, and the full Final Report on the Project Overview page.

The latest report from The National Institute for Transportation & Communities (NITC) offers help to planners seeking to incorporate emerging travel modes—including car sharing, bike sharing, ride hailing, and autonomous vehicles—into regional travel demand models. More specifically, it brings these new travel modes into the Regional Strategic Planning Model (RSPM) tool. As more people start taking advantage of new...

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