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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
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      <title>SPR-5022: Development of Diagnostic Analytics Tool for Causal Effect Analysis from 511 Database</title>
      <link>https://rip.trb.org/View/2576661</link>
      <description><![CDATA[By leveraging the results of the platform and tool developed from the SPR-4937 project, we propose to develop and implement a Diagnostic Analytics tool with intelligent web-based user interfaces for highway traffic management and operations based on 511IN traffic data and other related data sources. This tool will be capable of displaying various spatial-temporal traffic patterns and events and enabling users to draw connections between traffic patterns and identify correlations to causes. The tool can be used to develop an analytic or machine learning model for generating and predicting the traffic patterns for future occurrence of the event.]]></description>
      <pubDate>Tue, 15 Jul 2025 15:44:37 GMT</pubDate>
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      <title>SPR-4937:  Enhanced Traffic Pattern Knowledge Abstraction and Presentation from 511 Database</title>
      <link>https://rip.trb.org/View/2399821</link>
      <description><![CDATA[This project will develop a system with a user-friendly intelligent interface that will enhance the existing 511 features by developing new features for INDOT and potential users. These new features may include: (1) providing user-adjustable spatial-temporal traffic flow information over a specified period in the display; (2) allowing users to overlay additional parameters of their choice by integrating 511 traffic data and another related database, such as weather and event data; and (3) supporting pattern analysis for the historical data already stored in 511.]]></description>
      <pubDate>Tue, 02 Jul 2024 13:46:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/2399821</guid>
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      <title>Automatic Detection and Understanding of Roadworks</title>
      <link>https://rip.trb.org/View/2087440</link>
      <description><![CDATA[Roadwork zones present a serious impediment to vehicular mobility. Whether new construction or maintenance is taking place, work in road environments cause lower vehicle speeds, congestion, increased risk of rear-end collisions, and more difficult maneuvering. Crowd-sourced navigation systems like Waze warn drivers of roadworks, but those data must be manually entered causing a distraction for the driver. Google maps now automatically shows roadworks, but those data are often slow to update and do not distinguish between active/inactive work zones or specify lane restrictions/changes. In the proposed work, the study team seeks to address these issues by developing computer vision and machine learning methods that will automatically identify and understand (e.g., lane closed and two lanes merge into one lane) road work zones. The calculated information can be shared with other drives and also enable dynamic route planning for navigation systems, driver assist systems, and self-driving cars for efficiently and safely maneuvering through or around road work zones. Moreover, a comprehensive view of road work activity in a region can be constructed from information shared by users. Such a view may prove to be a useful tool for optimizing traffic flow along detour routes (e.g., traffic lights stay green for longer to accommodate the additional volume).]]></description>
      <pubDate>Wed, 21 Dec 2022 11:40:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2087440</guid>
    </item>
    <item>
      <title>SPR-4440: An Integrated Critical Information Delivery Platform for Smart Segment Dissemination to Road Users</title>
      <link>https://rip.trb.org/View/1637986</link>
      <description><![CDATA[This proposed INDOT/JTRP FY-2020 research is a collaborative work between TASI from IUPUI and Purdue University, which has the following major deliverables: (1) An integrated database including the baseline mile post database scheme and other data sources. (2) Algorithms that can generate targeted and prioritized alert messages for augmenting the INDOT ITS system. (3) Intelligent and novel traffic information delivery interfaces.
]]></description>
      <pubDate>Mon, 15 Jul 2019 11:20:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/1637986</guid>
    </item>
    <item>
      <title>Northwest Passage Phase #4</title>
      <link>https://rip.trb.org/View/1505787</link>
      <description><![CDATA[Interstates 90 and 94 between Wisconsin and Washington function as major corridors for commercial and recreational travel. Extreme winter weather conditions, prevalent in the northern states within this corridor, pose significant operational and travel-related challenges. Idaho, Minnesota, Montana, North Dakota, South Dakota, Washington, and Wyoming are predominantly rural and face similar transportation issues related to traffic management, traveler information, and commercial vehicle operations. Recognizing the value of coordinated, cross-border collaboration for intelligent transportation systems (ITS) deployment to address these issues, Minnesota initiated a meeting in 2002 with representatives from each of the states within the corridor. The group established itself as a Transportation Pooled Fund in 2003. North/West Passage members contribute $25,000 or more annually to the pooled fund and are reimbursed for program travel. A work plan is developed and approved annually by the Steering Committee. Work Plan 1 and Work Plan 2 were funded through TFP-5(093). That project number was closed out and Work Plan 3 - Work Plan 11 were funded through the FHWA number TPF-5(190). To view each work plan and project results, visit the program website at: http://www.nwpassage.info/about/workplan.php. This new TPF number will fund Work Plan 13 as well as a the next few annual work plans. OBJECTIVES: The vision of the North/West Passage (NWP) Corridor is to focus on developing effective methods for sharing, coordinating, and integrating traveler information and operational activities across state and provincial borders. The vision provides a framework to guide the states’ future projects in the corridor.
]]></description>
      <pubDate>Thu, 22 Mar 2018 08:46:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1505787</guid>
    </item>
    <item>
      <title>Green Navigation: A Big Data Approach Towards Sustainable Transportation</title>
      <link>https://rip.trb.org/View/1489861</link>
      <description><![CDATA[This project addresses the need for big data solutions that reduce the carbon emissions and energy footprint of the transportation sector by providing computational tools for informing driver decisions. These cyber-tools take physical models of vehicles, roads and traffic into account to produce advice that enhances transportation sustainability, and thus will have significant contributions to cyber-physical transportation systems. According to the US Energy Information Administration, the transportation sector currently accounts for one of the largest shares of energy consumption in the nation, among all sectors. A research investment is needed to offer computationally-enabled solutions for drivers to reduce their energy cost, emissions, delay, and carbon footprint. Towards this end, this proposal develops a system that gives individualized navigation advice to drivers. Currently, vehicular traffic is managed largely in bulk. Traffic lights, route advisories, and other traffic regulators operate in the spirit of broadcast, offering the same feedback to all. In contrast, with increasing proliferation of computational devices and global positioning system (GPS) navigation systems in vehicles with their own networking, storage, and processing capabilities, it becomes possible to customize real-time information that flows back to drivers, thereby allowing individuals to make more informed energy-saving and cost-saving decisions. Such individualization will result in significant total energy and emissions savings.]]></description>
      <pubDate>Tue, 28 Nov 2017 09:38:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/1489861</guid>
    </item>
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      <title>Field Operational Tests of Vehicle-Assist and Automation (VAA) System Using Full-size Public Transit Buses</title>
      <link>https://rip.trb.org/View/1441790</link>
      <description><![CDATA[The magnetic guidance technology developed in the past years has been successful and has displayed its maturity through various demonstrations throughout the world. Vehicle-assist and Automation (VAA) technologies have shown significant promise to provide benefits to transit agencies in terms of more efficient operations, cost savings (such as reduced right-of-way cost and travel times, smoother rider, reduce bus maintenance and repairs, and rail-like services) and safety. However, the United States Department of Transportation (US DOT) Federal Transit Administration (FTA) felt that in most cases, full technical feasibility and the benefits have not been quantified. Therefore, they decided that it is necessary to initiate a pilot program to demonstrate the benefits of VAA applications for full-size public transit buses in revenue service.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:52:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441790</guid>
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    <item>
      <title>Research Program Design---Administration of Highway and Transportation Agencies. Evaluation Guidance for Automated Vehicle Pilot and Demonstration Projects</title>
      <link>https://rip.trb.org/View/1357353</link>
      <description><![CDATA[No summary provided.]]></description>
      <pubDate>Fri, 12 Jun 2015 01:00:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1357353</guid>
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    <item>
      <title>Prototype Development of the Open Mode Integrated Transit System</title>
      <link>https://rip.trb.org/View/1236154</link>
      <description><![CDATA[The open mode integrated transit system (OMITS) is proposed to use state of the art technologies in wireless communication, global positioning system (GPS), data exchange and management system to combine availability of public transit system, taxi system, a carpool system, and emergency service system to provide dynamic, efficient, economic, and reliable transportation service in metropolitan areas. A novel device, namely cPhone, will communicate between riders, drivers, and the database server so as to exchange realtime and accurate transit information while serving as a GPS to give routing direction for a driver. A routing and dispatching system will match a driver and riders timely to enable dynamic carpooling, trace and confirm the success or failure of a carpooling match, and provide a consistent algorithm for GPS and the database servers to define the best/shortest route for drivers. A well designed membership management system and user operation system will ensure the security, credibility, and operational reliability of the whole system. The advantages of the OMITS are clear when compared with static transit systems (such as traditional car-pools and scheduled buses and trains) because it allows for dynamic matching of riders with transit options that best suit their needs and incorporates routing information that is adaptable to existing traffic conditions. Furthermore, the OMITS provides benefits over even dynamic ride-share programs because it incorporates multiple modes of transportation thus allowing users to transfer between transit modes when advantageous. In total, the OMITS will integrate a dynamic car-pooling system with public transportation systems and private transportation systems to provide a robust, stable, reliable, and economical solution for the current overloaded and inefficient urban metropolitan transportation system. It will result in new understanding of the critical urban transportation system currently and unsustainably over congested. The success of this system will greatly increase ridership in public and private vehicles, significantly reduce the number of cars in traffic peak time, and thus help to alleviate traffic and parking problems in metropolitan areas. Broad impacts will be produced on gas saving, greenhouse gas emission and transit cost reduction. For demonstration, this proposed project would develop a small prototype system for about 100 residents in northern Bergen County, New Jersey, who are working in New York City. Once the concept of this system is proved, the technology will be immediately transferred to industry partners and transit agencies and be extended to the other parts of New York metropolitan area and other cities.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:42:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1236154</guid>
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