Aerial view of urban city road with cars on the road and crosswalk. Text reads: Webinar: Land Use and Transportation Policies for a Sustainable Future.
Aug 14, 2020
 

OVERVIEW

Even though there are tremendous uncertainties in the timing and evolution path of the Autonomous Vehicles (AV) technology, it may become a likely reality within most MPOs' long-range regional transportation plan horizon of twenty years. Yet a recent survey of the largest MPOs in the US indicates only one of them "even mentions driverless, automated, or autonomous vehicles in its most recent RTP". One of the uncertainties in assessing the impacts of AV is their direction: on one hand, self-driving cars could increase VMT by increasing roadway capacity, lowering costs of travel; on the other, they may reduce VMT by enabling more car-sharing, improving access to transit, eliminating the fixed costs of car ownership, and reclaiming parking space. To date, there is no suitable conceptual framework or modeling tools available to MPOs for quantitatively assessing the likely long-term effects of AV or potential policy scenarios.

This project studies the possible impacts on travel and land use of the emerging AV technology and focuses on advancing this innovative mobility option by making sure it serves the greater good of building sustainable and equitable communities in its adoption. It also contributes to smart cities research by examining the likely social, economic, and environmental outcomes of integrating AV in our cities and by...

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Red restaurant tables and chairs stand in the place of former curbside parking on a Seattle street
Aug 04, 2020
Photo by Dongho Chang, Seattle Traffic Engineer
Benjamin Clark and Anne Brown, University of Oregon

Autonomous vehicles (AVs) will challenge cities in ways that are difficult to fully predict, and yet critical...

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Bicyclists ride in a protected bike lane, buffered by planters
Jun 04, 2020
Photo by Cait McCusker
Marc Schlossberg and Heather Brinton, University of Oregon

Advances in transportation technology — e-scooters and bike share, Lyft & Uber, and autonomous vehicles — are beginning to have profound impacts on cities. New mobility is changing not only how we travel, but also urban form and development itself. In the near future, we can expect differences in what public transit looks like, the layout of cities, and the places we spend our time. In turn,...

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Connected Vehicles Illustration showing icons of wifi over a road
Apr 01, 2020
Image by metamorworks/iStock
Xianfeng Yang, University of Utah; Mingyue Ji, University of Utah

Now that we are decades into the Age of Information, it's increasingly important to minimize the age of information: that is, to make sure the information we have is the very latest.

In the world of connected vehicle technology, Age of Information (AoI) is a concept that was introduced in 2012 to quantify the “freshness” of knowledge about the status of remote systems. The latest NITC...

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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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