UW WSU WSDOT




Intelligent Transportation Systems

Operations Performance Management Guidance, Technical Assistance, and Primer Development

The Federal Highway Administration is looking to help transportation agencies shift their focus from simply measuring transportation system performance to directly using those performance measures within their project identification, project selection, and decision-making processes. A potential tool for accomplishing that is the Capability Maturity Model (CMM). The CMM describes the degree of formality and optimization (“maturity”) of an organization’s processes, from reactive, ad hoc practices; to formally defined steps; to managed consistency through measurement; to optimization and continual performance improvement. As a subcontractor to Cambridge Systematics, Inc., TRAC researchers will help refine the CMM to examine how state agencies manage roadway performance. TRAC and Cambridge Systematics will develop a primer that will discuss the difference between simply reporting operations performance measures and actively managing the roadway system using those measures. The primer will also present how using the CMM can help agencies assess the maturity of their existing roadway operations management processes and provide actions that agencies can take to more effectively use performance measures to select and apply the best roadway operations management strategies.

Principal Investigator: Mark E. Hallenbeck, Washington State Transportation Center, UW

Sponsors:
Cambridge Systematics, Inc.
FHWA

Scheduled completion: April 2020

Characterization of Under-Served Population Perceptions and Mobility Needs in Connected-Vehicle and Smarter City Environments—Phase 2

Residents of smaller and low-density communities, as well as the elderly and disabled, have few alternatives to private car travel. While new on-demand mobility services, connected vehicle technologies, and smarter city initiatives are reshaping travel in cities, those in smaller towns and rural areas, those without smart phones and communication network access, and lower-income travelers lacking a variety of additional resources are at risk of being left behind. The goal of this outreach effort is to better understand and characterize under-served populations’ perceptions of mobility needs in urban and rural environments of the Pacific Northwest and to inform those communities about the opportunities for mobility improvement that a smart city could provide. This project will identify and work with representatives from different mobility under-served groups in Idaho, Oregon, Washington, and Alaska and will develop interactive materials to inform and educate the under-served groups about the potential improved mobility opportunities in connected-vehicle and smarter city environments. They will also collect data from the participants on their mobility challenges, perceptions, and experiences and map those data within a GIS database. They will then use the data to help identify smart city implications and potential solutions.

Principal Investigators:
Ahmed Abdel-Rahim, University of Idaho
David Hurwitz, Oregon State University
Ali Hajbabaie, Civil and Environmental Engineering, WSU
Jeff Ban, Civil and Environmental Engineering, UW
Billy Connor, University of Alaska Fairbanks

Sponsor: PacTrans
Scheduled completion: August 2020

Hierarchical, Priority-Based Control of Signalized Intersections in Semi-Connected Corridors

Connected vehicles, the internet of things, and smart infrastructure technologies facilitate the exchange of real-time, highly granular information among individual transportation network users, system operators, and the supporting infrastructure. Harnessing this emergent, ubiquitous connectivity and its resulting data stream poses unexplored possibilities to improve network mobility, specifically by optimizing the timing of signalized intersections. The main objective of this research is to develop corridor-level, priority-based coordinated signal timing algorithms that can control signalized intersections in corridors that are both connected and semi-connected. The research will enhance traffic signal optimization algorithms to allow data from connected vehicles and existing point detectors to be incorporated into the models, decisions at both the intersection and the corridor levels to be distributed to reduce computational complexity, and control decisions to be coordinated among various intersections by a distributed cloud-fog-based communication network to optimize solutions. This study will thus facilitate the transition from existing traffic signal control system technology to a connected vehicle environment.

Principal Investigators:
Ali Hajbabaie, Civil and Environmental Engineering, WSU
Sameh Sorour, University of Idaho
Ahmed Abdel-Rahim, University of Idaho

Sponsor: PacTrans
Scheduled completion: August 2020

Dynamic Metering in Connected Urban Street Networks: Improving Mobility

Connected vehicles, the internet of things, and smart infrastructure technologies will facilitate the exchange of real-time, highly granular information among individual users in transportation networks, system operators, and the supporting infrastructure. Harnessing this emergent connectivity and its resulting data stream will open unexplored possibilities to improve mobility on urban street networks. Traffic metering along urban street networks is among the effective traffic control methods that can greatly benefit from connected and autonomous vehicle technologies. A dynamic traffic metering system may use collected data to maintain network accumulation at an optimal level, thereby avoiding long queues, queue spillovers, and gridlock. The goal of this project is to improve mobility by developing a dynamic traffic metering methodology for connected urban street networks. The methodology will aim to meter an optimal portion of incoming traffic at the borders of the network or inside it to increase system-level mobility.

Principal Investigator: Ali Hajbabaie, Civil and Environmental Engineering, WSU
Sponsor: PacTrans
Scheduled completion: February 2020

Preparing for Traffic Signal Operations in a Multimodal Connected and Autonomous Vehicle Environment

Connected and autonomous vehicle (CAV) technology and information may greatly help reduce congestion, especially in urban settings. However, currently there is no real-time, reliable, and multimodal approach for controlling the timing of signalized intersections in a connected or semi-connected arterial or urban street network. In addition, research is needed to explore the ability to communicate basic traffic signal controller information such as signal phase and timing (SPaT) to connected vehicles to allow them to directly respond to and coordinate with ongoing signal operations. Because WSDOT maintains 1,000 signalized intersections throughout the state, it is important for WSDOT to plan for this emerging and revolutionary technology and to develop ways to use the additional information that CAVs will provide to improve traffic operations. This project will help WSDOT to identify technological issues and requirements of integrating CV hardware in existing traffic signal systems.

Principal Investigator: Ali Hajbabaie, Civil and Environmental Engineering, WSU
Sponsor: WSDOT
WSDOT Technical Monitor: Ted Bailey
WSDOT Project Manager: Doug Brodin
Scheduled completion: March 2020

Understanding Opportunities with Connected Vehicles in the Smart Cities Context

The goals outlined in WSDOT’s Strategic Plan include modal integration, environmental stewardship, strategic investments, and adoption of smart technologies. This project will help address aspects of all those goals. It is serving as a pilot study for the application of Connected Vehicles technologies that would be needed for establishing smart cities. Connected vehicles technologies support safe, interoperable, networked wireless communication among vehicles, roads and other infrastructure, and passengers’ personal communications devices. The study is deploying and evaluating several new technologies, primarily a Connected Vehicles device, an associated mobile app, and variety of sensors for traffic detection and data collection across all modes of travel—including pedestrians, bicyclists, and unconnected vehicles—at minor arterial test bed sites. The test beds will offer field data from infrastructure, users, and communications devices. Besides aiding smart cities studies, the newly available data may also help WSDOT to significantly improve infrastructure design and operations methods.

Principal Investigator: Yinhai Wang, Civil and Environmental Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Bill Legg
WSDOT Project Manager: Doug Brodin
Scheduled completion: December 2018

Support and Align Operational and Demand Management Strategies and Business Processes with Planning and Programming within WSDOT

WSDOT has long been a national leader in the deployment of transportation system management and operations (TSM&O) strategies.  However, currently, TSM&O tends to be adopted on an ad hoc basis within the Department.  No defined or consistent process systematically considers TSM&O strategies within the WSDOT’s programming and prioritization process, nor are TSM&O strategies routinely considered in corridor and regional plans. To address this issue, researchers are working to develop a draft business outline that describes how TSM&O should be included in WSDOT’s planning and programming process at the headquarters and regional levels, providing a framework for the development of corridor-specific operations plans. They are also developing guidance on each of the TSM&O strategies of interest to WSDOT. And they are creating a website that WSDOT staff can use to access that guidance and further information about each strategy. These products will allow WSDOT to more effectively integrate TSM&O into its business processes and fully consider and implement TSM&O benefits where appropriate. They will also help WSDOT staff select the appropriate TSM&O strategies, estimate the value of those efforts, and associate the strategies with performance metrics.

Principal Investigator: Mark E. Hallenbeck, Washington State Transportation Center, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Monica Harwood
WSDOT Project Manager: Doug Brodin
Scheduled completion: December 2017

TRAC