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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Connected Vehicle System Design for Signalized Arterials
Mar 05, 2020
 

PRESENTATION ARCHIVE

OVERVIEW

It can be expected that connected vehicles (CVs) systems will soon go beyond testbed and appear in real-world applications. To accommodate a large number of connected vehicles on the roads, traffic signal control systems on signalized arterials would require supports of various components such as roadside infrastructure, vehicle on-board devices, an effective communication network, and optimal control algorithms. In this project, we aim to establish a real-time and adaptive system for supporting the operations of CV-based traffic signal control functions. The proposed system will prioritize the communication needs of different types of CVs and best utilize the capacity of the communication channels. The CV data sensing and acquisition protocol, built on a newly developed concept of Age of Information (AoI), will support the feedback control loop to adjust signal timing plans.

Our multidisciplinary research team, including researchers from transportation engineering and electrical engineering, will carry out the project tasks along four directions that capitalized on the PIs’ expertise:

  1. Data collection and communication, in which the proposed system will...
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A worker measures the distance from a bike light to the ground
Oct 09, 2019
Stephen Fickas and Marc Schlossberg, University of Oregon

NITC researchers Stephen Fickas and Marc Schlossberg of the University of Oregon are on a mission: bring the benefits of V2I (vehicle-to-infrastructure communication) to bicycling. Earlier this year they published their proof-of-concept of a DIY vehicle-to-infrastructure "bike box" in Oregon for communicating with traffic signal controllers. In the most recent round of NITC grants awarded...

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Oct 07, 2019

PRESENTATION ARCHIVE

Miss the webinar or want a look back?

OVERVIEW

The "Fast Track" project at the University of Oregon focuses on a mode of transportation that is sometimes left out of vehicle-to-infrastructure, or V2I, conversations: Bicycling. NITC researchers developed an app based on a new technology being integrated into modern cars: GLOSA, or Green Light Optimized Speed Advisory. GLOSA allows motorists to set their speed along corridors to maximize their chances of catching a "green wave" so they won't have to stop at red lights.

This project demonstrates how GLOSA can be used by bicyclists in the same way it is used by motorists, with a test site on a busy car and bike corridor feeding the University of Oregon campus: 13th Avenue in Eugene, Oregon. Researchers developed a smartphone app that tells a cyclist whether they should adjust their speed to stay in tune with the signals and catch the next green. The project demonstrates how university researchers, city traffic engineers, and signal-controller manufacturers can come together to help bicyclists be active participants in a smart transportation system.

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Bicyclists cross an intersection with a bike signal, near a red car
Sep 26, 2019
John MacArthur, Portland State University

What if your bicycle could warn you that a car is coming from a side street you can't see? Or let you know that your front tire is getting a little low, or that you're approaching a pothole that wasn't there yesterday? A NITC research project led by John MacArthur of Portland State University explores how connected vehicle (CV) technologies could encourage an increase in bicycling. As CV technology moves forward in the rest of the transportation system—with buses and connected streetcars requesting early green lights from the traffic signals, and cars chatting with each other about their locations and trajectories—there may be...

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Cars waiting at a traffic signal
Apr 04, 2019
Photo by Canetti
Principal Investigator: Gerardo Lafferriere, Portland State University
Learn more about this research by viewing the Executive Summary and the full Final Report on the Project Overview page.

Automobile traffic congestion in urban areas comes with significant economic and social costs for everyone. According to the 2015 Urban Mobility Report, the total additional cost of congestion was $160 billion. As more people move to metropolitan areas, the problems only intensify. The latest NITC report offers a new approach to urban traffic signal control based on network consensus control theory which is computationally efficient, responsive to local congestion, and at the same time has the potential for congestion management at the network level.

Traffic signals represent a significant bottleneck. As cars queue up at a stoplight, then gradually move again once the...

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Cyclists cross the road at a bike signal
Feb 28, 2019
Investigators: Stephen Fickas, University of Oregon; Marc Schlossberg, University of Oregon
Learn more about this research by viewing the Executive Summary and the full Final Report on the Project Overview page.

Most people who bike for transportation can probably think of "that one intersection:" The light where it's impossible to get a green without waiting. Even when there are no cars, pedestrians or other bikes in sight, you still know you'll have to stop and wait a while, sacrifice all your momentum, and wish you could have given the signal advance notice that you were coming.

Researchers at the University of Oregon have created an app for that.

Lead investigator Stephen Fickas, a computer and information science professor at the UO, developed the app, along with a specially-designed Bike Connect ‘box' (watch the 3-minute video) that attaches to a traffic signal controller. With the box installed, the app allows a cyclist to alert the signal that they're...

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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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