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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <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>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Which Way Forward? Learning from Global Informal Transport Networks to Inform Microtransit Services in California</title>
      <link>https://rip.trb.org/View/2695811</link>
      <description><![CDATA[This proposed 12-month study seeks to draw upon lessons learned from informal transit systems, particularly from the developing world, to inform the development and implementation of demand-responsive transit (often referred to microtransit) strategies in California. Through a comprehensive review of existing literature, case studies (n= up to 5), and expert interviews (n=15-20), this study aims to identify lessons learned, challenges, and opportunities associated with informal transit operations. Leveraging this understanding, the research will assess how such lessons can be applied to the design, deployment, and evaluation of microtransit and other demand-responsive services in California communities, including transportation network companies (TNC) and taxi models. Key areas of focus include business and operational models, fare affordability and financial sustainability (including operational costs), and potential policy frameworks. By synthesizing insights from informal transit experiences internationally, this proposed study seeks to contribute to the development of efficient and sustainable microtransit and demand-responsive strategies tailored to the diverse needs of all travelers.]]></description>
      <pubDate>Thu, 23 Apr 2026 18:05:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2695811</guid>
    </item>
    <item>
      <title>Using Artificial Intelligence to Uncover How Safety Perception Influences Travel Behavior Shifts: Comparative &amp; Longitudinal Analysis for the Future of Autonomous Vehicle, Transit and Ride-hailing Services</title>
      <link>https://rip.trb.org/View/2655700</link>
      <description><![CDATA[Transit agencies and cities are increasingly overwhelmed by large volumes of unstructured data; yet they lack methodical, validated tools to turn safety narratives into operational indicators. This project addresses that gap by measuring and comparing public safety perception for autonomous-vehicle services (robotaxis), public transit, and ride-hailing services. It will assess how these perceptions relate to traveler profiles and mode choice in San Francisco and San Jose over a six-month period. San Francisco as a mature setting where robotaxis may compete with ride-hailing and transit, and San Jose as a newer coming deployment that provides a baseline for comparison and forward-looking extrapolation.
The research team will use artificial intelligence with human-audited classification to analyze public discourse drawn from news-comment threads and social-media posts, for example, discussions of disengagements, curb conflicts, yielding behavior, and interpersonal harm such as unwanted contact, theft, or assault. Validation will include human audit with inter-rater reliability (aiming for Cohen’s kappa of at least 0.60), time- and city-based cross-validation, and an error taxonomy with documented adjustments. The project will deliver (1) a transparent safety-perception taxonomy, (2) traveler-persona profiles linked to safety perceptions, (3) a lightweight dashboard for agencies and cities to explore time, place, and topic trends, and (4) operational and policy frameworks for improvements across all modes, organized into vehicle-level safety measures, station and hub operating practices, reporting and response mechanisms, and rider communication standards. The approach and workflow are replicable and can be extended to additional cities. The innovation lies in a reusable tool bridging research and practice providing concrete, methodical steps to turn qualitative narratives into consistent indicators they can trust. Agencies can adopt it to sort and prioritize incoming signals, rerun it with new data, and compare results across time and places to support day-to-day decisions and longer-term planning.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:09:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655700</guid>
    </item>
    <item>
      <title>Towards an Efficient Robotaxi Deployment
</title>
      <link>https://rip.trb.org/View/2625316</link>
      <description><![CDATA[The commercial deployment of automated vehicles (AVs) for on-demand mobility services, referred to as robotaxis, has advanced significantly in recent years. Given the drastic changes that robotaxis might set in motion in the near future, there is a crucial need to prepare guidelines for their efficient deployment. This collaborative project aims to facilitate this effort by developing modeling tools to understand the complex interactions between the various stakeholders involved in the robotaxi’s deployment phase, including regulators, transit agencies, robotaxi operators, TNC drivers, private AV owners, and regular travelers.]]></description>
      <pubDate>Thu, 13 Nov 2025 16:03:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625316</guid>
    </item>
    <item>
      <title>Compliance of Alternate Transit Options with State and Federal Requirements</title>
      <link>https://rip.trb.org/View/2487297</link>
      <description><![CDATA[The public transit landscape has expanded beyond traditional systems, with various agencies and private companies now providing transportation options to the public. These include transportation network companies (TNCs), taxis, and paratransit service providers. When these service providers establish contractual partnerships with federally funded transit agencies, they become subject to federal requirements.
In June 2018, TCRP LRD 53: Legal Considerations in Evaluating Relationships Between Transit Agencies and Ridesourcing Service Providers was published. This digest examined whether such providers were eligible for federal financial assistance and analyzed the legal implications of their partnerships with transit agencies. At the time, ride-sourcing services were relatively new to the transit industry. TCRP LRD 53 identified significant challenges these providers faced in meeting state and federal requirements.
Updating TCRP LRD 53 is now essential due to the significant changes that have occurred in this field. Since 2018, the number of companies entering the market has grown considerably. Additionally, federal and state governments have introduced new regulations and prioritized the enforcement of existing requirements, such as those under the Americans with Disabilities Act (ADA). The legal landscape has also evolved, with increased litigation addressing key issues related to these partnerships. An updated report should reflect these changes and provide transit agencies with up-to-date legal guidance.
OBJECTIVE:
The objective of this research is to develop practical guidance and summarize relevant laws, litigation, and policy developments to support public transportation agencies, their legal counsel, and policymakers in decision-making related to contracting with service providers and ensuring compliance.]]></description>
      <pubDate>Tue, 07 Jan 2025 18:56:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2487297</guid>
    </item>
    <item>
      <title>Tompkins Mobility-as-a-Service (MaaS) Phase 1</title>
      <link>https://rip.trb.org/View/2077906</link>
      <description><![CDATA[Tompkins County will receive funding to develop a multi-modal trip planning platform that integrates information on bus services, demand-response service, taxis, volunteer transportation, car-share and bike-share services. The platform will enable riders in rural upstate New York to plan multi-modal trips through a mobile app and web platform.]]></description>
      <pubDate>Tue, 06 Dec 2022 09:48:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2077906</guid>
    </item>
    <item>
      <title>Quantifying the Effect on Congestion of Converting Metropolitan Taxi Services into Ridesharing Mode</title>
      <link>https://rip.trb.org/View/2004407</link>
      <description><![CDATA[Large and growing urban areas are dealing with an escalation of traffic congestion and all its consequences in terms of overall delay experienced by travelers. Ridesharing is intuitively a practical solution to improve the congestion issues in our modern cities. The largely unused capacity of the private vehicles would be utilized in place of other vehicles to satisfy the mobility needs of individual passengers. This project analyzes and quantifies the effect on congestion reduction of a large-scale application of ridesharing mode to serve metropolitan transportation demand of taxi services, which have been shown to be often unproductive and wasting car seating capacity. Specifically, the authors are evaluating the macroscopic effect of converting a sizeable portion of the taxi rides from conventional direct point-to-point service to a ridesharing modality. This will incur in a potentially significant reduction of vehicles on the network and consequently ease out congestion at the expense of the service level experienced by willing ridesharers, which would need to be incentivized by fare reductions.
The project will make use of an available large set of taxi data from the City of Chicago to perform simulation analyses under a variety of scenarios. Different ridesharing modalities, scheduling algorithms and participation levels will be utilized and assumed to infer traffic network usages. The effect on congestion will be estimated with a before and after analysis evaluating an integrated index that considers total miles traveled, total travel time and Level of Service.
The project aims to provide tools and detailed information for planners and policy makers to intervene by incentivizing a conversion, even if partial, of the taxi services into ridesharing service, presenting an opportunity to improve the congestion conditions, along with other clear environmental advantages. Impact is expected to be significant with a potential nationwide deployment of these policies, driven by the largescale findings.]]></description>
      <pubDate>Sun, 07 Aug 2022 16:11:56 GMT</pubDate>
      <guid>https://rip.trb.org/View/2004407</guid>
    </item>
    <item>
      <title>The Provision of Alternative Services by Transit Agencies: The Intersection of Regulation and Program Objectives</title>
      <link>https://rip.trb.org/View/1713373</link>
      <description><![CDATA[The objective of this research is to understand how taxis, ride-sourcing services, and other non-dedicated service providers are being used for alternative services for individuals with disabilities. This research should address: (1) The interpretation and application of pertinent federal regulations, statutes, and guidelines; (2) The mobility benefits and challenges that alternative services produce for the individuals; (3) The impacts that these services have on customer travel patterns; (4) The costs of both on-demand and traditional paratransit services to the transit agencies and the individuals; (5) Data transit agencies collect from providers and uses for these data services, as well as any unmet data needs and purposes; and (6) Best-practice design models for alternative services that have resulted in transit agencies achieving their goals as well as service equivalency and reduction in cost while also increasing mobility.]]></description>
      <pubDate>Tue, 09 Jun 2020 10:21:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/1713373</guid>
    </item>
    <item>
      <title>Optimizing ADA Paratransit Operations with Taxi and Ride Share Programs</title>
      <link>https://rip.trb.org/View/1574983</link>
      <description><![CDATA[Rising ridership on Americans with Disabilities Act (ADA) paratransit services, such as MBTA’s The Ride, pose a challenge due to the high costs of operating this required service.  The objective of this project is to optimize programs to serve some paratransit trips by taxi or other mobility service in order to minimize system cost.  The benefits to MBTA will be to lower the cost of providing service in order to be better positioned for expected continued increases in ridership. The challenge of managing a system of demand-responsive transportation services for people with disabilities is that the operation of the system depends on the demand-side considerations related to traveler behavior and supply-side considerations related to the system structure and costs.  Starting with limited participation in September 2016 and expanded to all eligible ADA paratransit service “The Ride” customers on March 1, 2017, a pilot program now allows eligible customers to use taxicabs, Uber, or Lyft for a subsidized trip in addition to conventional ADA paratransit service from The Ride.  This research project will seek to evaluate the effects on demand, supply and optimal service provision of this new service.  The goal is to provide insights about how the operation and use of the system is changing under the pilot program and then to provide guidance about how to manage a multimodal ADA program that provides users with a greater range of choices than they have had in the past.  Although the scope is tied closely to analysis of the MBTA system, the insights are likely to have implications for the ADA paratransit systems elsewhere in Massachusetts.

]]></description>
      <pubDate>Mon, 17 Dec 2018 15:56:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/1574983</guid>
    </item>
    <item>
      <title>The Environmental Effects of New Mobility Services</title>
      <link>https://rip.trb.org/View/1441929</link>
      <description><![CDATA[The proposed white paper will summarize the expected environmental effects of new mobility services, and critically evaluate the empirical and modeling evidence that test these effects. The review will focus on carsharing and on-demand ride services. Carsharing services will encompass roundtrip, one-way, and peer-to-peer services. On-demand services will include e-hail taxi (e.g., Uber and Lyft), shared taxi (e.g., UberPool and Lyft Line), peer-to-peer ridesharing (e.g., Carma), and microtransit (e.g., Bridj). The review will focus on these services because they have complicated, both positive and negative, effects on the environment. These services are also likely to be early adopters of automated vehicle technologies. This review will help untangle the magnitude and balance of these complex effects and provide a structured lens through which to evaluate current and emerging evidence.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:57:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441929</guid>
    </item>
    <item>
      <title>Smartphone Information and Transportation Demand Modeling: An Analysis of Transportation Network Companies</title>
      <link>https://rip.trb.org/View/1441922</link>
      <description><![CDATA[In this task the performing organization plans to develop a comprehensive understanding about the operations and technological capabilities of transportation network companies (TNCs) and to explore ways in which this knowledge/data can be used to improve transportation system modeling, namely the demand-side. Three firms will be examined in this report: Uber, Lyft, and Side-Car through publicly available documents from TNCs and other sources (e.g. newspapers, legal documents, etc) although the performing organization will also direct efforts to communicate directly with TNC managers. The selection is largely based on firm size, however, each firm also possess sufficient operational diversity to warrant the investigation of all three.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:56:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441922</guid>
    </item>
    <item>
      <title>Urban Travel Time Variability: Spatio-Temporal Analysis for New York City</title>
      <link>https://rip.trb.org/View/1425397</link>
      <description><![CDATA[Traffic congestion is an important aspect of quality of life, mobility and accessibility in urban areas. The economic cost of congestion is in the order of billions of dollars especially for dense urban cities. Besides the congestion which relates to the magnitude of travel time, travel time variability is also studied extensively by researchers as an additional measure for transportation network efficiency. In order to enhance the efficiency of urban traffic flow in New York City (NYC), numerous policies have been discussed, including different transportation pricing schemes. Pricing schemes – particularly variable pricing – should incorporate the severity of congestion and levels of travel time variability at different times of day and areas throughout the City. However, most of the existing discussions are based on number of trips and bridge/tunnel crossings in the City, mainly because the necessary data to calculate travel time related measures have not been extensively available. Meanwhile, wider deployment of new intelligent transportation systems (ITS) tools and the emergence of GPS devices in vehicles have been helping to create comprehensive and reliable data resources to extract the travel time patterns. For instance, NYC Taxi and Limousine Commission (TLC) mandates all registered taxis to install Global Positioning System (GPS) devices and record all trips, including pickup and drop off location as well as travel distance and time information. Using this data, taxis can be utilized as probe vehicles in the network, collecting travel time information in the city 24/7. Until very recently, TLC’s taxi trip dataset were originated by yellow taxis which can legally serve anywhere in the city, but largely serve in Manhattan due to taxi drivers’ higher potential hourly income in relatively more business oriented Manhattan. Consequently, the existing studies could not provide comprehensive spatial travel time patterns for the whole City including Brooklyn, Queens, Bronx and Staten Island. In order to increase the taxi service in the City, TLC introduced boro taxis which are restricted to serve at Brooklyn, Queens (except LGA and JFK airports), Bronx, Staten Island and upper Manhattan (north of north of West 110th street and East 96th street). In this respect, the recently available boro taxi data fill the crucial gap to provide travel time data for unsufficiently covered areas in the City. This proposed study utilizes both yellow and boro taxi datasets to provide the necessary spatio-temporal congestion and travel time variability patterns, in order to aid relevant policy discussions in New York City. Main objectives of the proposed research direction is to identify spatiotemporal congestion and travel time variability, and provide powerful visual maps in order to convey facts to wider audience as well as policy makers. The proposed research direction ultimately pursues to provide classification and clustering models to extract travel time relationships between space and time. These models along with strong descriptive data visualization will help facilitate better understanding of congestion and travel time variability patterns for both public and academic scholars.]]></description>
      <pubDate>Tue, 04 Oct 2016 15:59:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/1425397</guid>
    </item>
    <item>
      <title>Why TNCs Will Be Regulated Like Taxis–Historically Speaking</title>
      <link>https://rip.trb.org/View/1350301</link>
      <description><![CDATA[With the advent of transportation network companies, or TNCs, as they are labeled by the state of California, there has been considerable discussion, legislative action, and lawsuits regarding their attempts to operate without being subject to local taxi, sedan, limousine, or private-for-hire regulations. Indeed, across almost every continent, Uber has attempted to simply disregard local city and airport rules and regulations established for all commercial ground passenger transportation carriers. Uber argues that it is not a transportation company but rather a technology company, and so by definition it is not subject to commercial vehicle regulations. As a result, fierce and expensive legal and legislative battles have been bitterly fought. However, these legal proceedings rarely address just why there are regulations for commercial vehicles and their drivers.

It is therefore incumbent upon public officials to learn from this phenomenon and design a taxi system that provides drivers a fair income opportunity and maximum utilization from vehicles, to offer and maintain a high level of service at reasonable rates to residents and visitors alike. A best guess is that the industry will experience a form of hybrid taxi/TNC type transportation firm that offers both services in competition with national TNC brands for a while, but that ultimately there will be re-regulation and TNCs will be included within the local regulatory framework. There may be an opportunity for statewide or even national taxi/TNC regulations, but as in the past, drivers will be vetted, entry will be restricted, and public safety in the form of commercial liability insurance for all drivers will be standard requirements.]]></description>
      <pubDate>Tue, 14 Apr 2015 01:00:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/1350301</guid>
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