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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <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>
    <image>
      <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>Reliability-Aware Accessibility Measurement and Planning for Rural Transportation Systems</title>
      <link>https://rip.trb.org/View/2703797</link>
      <description><![CDATA[Reliable access to essential destinations is a persistent challenge in rural transportation systems, where long travel distances, limited infrastructure, and exposure to environmental disruptions can significantly affect mobility. Transportation accessibility is widely used in planning to evaluate how well transportation networks connect people to services and opportunities, yet most accessibility measures assume deterministic travel conditions and do not account for travel-time variability, weather disruptions, or infrastructure reliability. As a result, existing accessibility metrics may overestimate the practical ability of rural residents to reach essential destinations and provide limited guidance for transportation planning under uncertain conditions.
This project develops a reliability-aware accessibility measurement and planning framework for rural transportation systems. The research will extend traditional accessibility measures by incorporating transportation network uncertainty through scenario-based modeling of travel-time variability and disruption conditions. Reliability-aware accessibility metrics will be benchmarked against conventional accessibility measures and embedded within an optimization-based planning model that helps identify transportation interventions that improve reliable access under resource constraints. The framework will be demonstrated through a rural transportation case study using publicly available data and implemented as a prototype decision-support workflow for transportation planners.]]></description>
      <pubDate>Sat, 16 May 2026 11:55:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703797</guid>
    </item>
    <item>
      <title>National Accessibility Evaluation Phase II</title>
      <link>https://rip.trb.org/View/2703751</link>
      <description><![CDATA[This project implements activities for the National Accessibility Evaluation (NAE) pooled-fund study, performing accessibility evaluations describing conditions in 2020, 2021, 2022, 2023, and 2024. The National Accessibility Evaluation creates national census block-level accessibility datasets that can be used by partners in local transportation system evaluation, performance management, planning, and research efforts. The project produced a series of annual reports describing accessibility to jobs by driving, biking, walking, and by transit in metropolitan areas across America.

Accessibility calculations rely on detailed travel-time calculations for both driving and transit, using commercially available, global positioning system (GPS)-based speed measurements and published transit schedules. Each NAE partner received digital access to the accessibility datasets covering their jurisdictions. These datasets quantify access to jobs, health care, schools, grocery stores, and other essential destinations. The annual Access Across America reports provide summaries of the detailed job accessibility datasets for the 50 most populous metropolitan areas across America. These reports were released to national and local media outlets and supported by publicity and communications efforts.]]></description>
      <pubDate>Fri, 15 May 2026 15:29:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703751</guid>
    </item>
    <item>
      <title>Enabling Mobility of Emergency Medical Service through Connected and Automated Vehicle Preemption</title>
      <link>https://rip.trb.org/View/2669655</link>
      <description><![CDATA[Emergency Medical Service (EMS) vehicles, typically ambulances, have time-critical transportation roles when responding to traffic incidents by bringing first medical responders and equipment from their bases to the incident scenes, and transferring injured persons from the scenes to medical facilities. Addressing the mobility of EMS vehicles supports but public health and safety goals, as well as those related to efficient mobility.     

The traditional way for EMS vehicles to reach their destinations faster is to use audible sirens to alert drivers of their presence. Upon hearing an EMS vehicle’s siren, drivers must yield the right of way to facilitate its passage. Previous research on traffic signal preemption for EMS vehicles has demonstrated its effectiveness in reducing delays at signalized intersections. With the advent of Connected and Automated Vehicle (CAV) technology, vehicles can now communicate directly with each other. EMS vehicles equipped as CAVs could leverage vehicle-to-vehicle (V2V) communication technology to transmit warning messages to the CAVs downstream along their routes, beyond the range of audible sirens. The CAVs that have received these messages can proactively move aside to create a clear lane for the EMS vehicle to pass. This “CAV preemption” concept has the potential to significantly improve EMS mobility, resulting in faster response times, earlier on-scene medical aid, and quicker patient transfer to hospitals. Furthermore, the proposed CAV preemption will accelerate incident clearance and the restoration of highway capacity.  

This research is based on an envisioned CAV preemption system in which an EMS vehicle broadcasts its impending arrival to downstream CAVs, while simultaneously sounding its siren and emitting high-intensity strobe light to request signal preemptions. All CAVs receiving this V2V message will automatically move to the right lane, while only a portion of the non-CAV drivers will comply and respond to the siren. The efficiency of this system depends the following factors: (1) The broadcast range of the warning messages to CAVs, (2) The market penetration rate of CAVs, (3) The move-aside compliance rate of non-CAV drivers, (4) The level of traffic congestion.  

This research will simulate and quantify the efficiency of the proposed CAV preemption system under varying operating conditions. An agent-based simulation model of the El Paso highway network will be used to assess the EMS vehicle’s travel time. Mobility efficiency is defined as the percentage reduction in the average travel time. The travel times of EMS vehicles from their bases (selected fire stations that house ambulances) to multiple incident sites (selected highway locations) will be simulated, extracted, and analyzed. The analyses will assess the impacts of broadcast range, CAV market penetration, non-CAV compliance rate, and traffic volume.   ]]></description>
      <pubDate>Sun, 15 Feb 2026 16:34:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669655</guid>
    </item>
    <item>
      <title>Understanding Risks and Opportunities for Ramp Metering Control in a Mixed-autonomy Future</title>
      <link>https://rip.trb.org/View/2651988</link>
      <description><![CDATA[Vehicle automation may change traffic flow dynamics. This will also impact the control of traffic flow via infrastructure-based systems such as ramp metering control. In this work the research team investigated the impact that different levels of automation and connectivity will have on ramp metering control, and proposed modifications to existing ramp metering algorithms to improve their performance under different automation scenarios. The team finds that low-level automation such as adaptive cruise control may decrease mainline throughput by up to 58% on average and increase travel time by 61%. However, full connectivity and automation may decrease travel time by up to 40%. Based on these potential impacts, modifications to the ramp metering algorithm settings were developed for each of the seven automation scenarios. These modifications are shown to improve operations in each scenario.]]></description>
      <pubDate>Thu, 08 Jan 2026 15:26:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2651988</guid>
    </item>
    <item>
      <title>Synthesizing Microtransit and Fixed Route Transit via Rider Hand Off to Improve Transit Efficiency</title>
      <link>https://rip.trb.org/View/2640190</link>
      <description><![CDATA[Microtransit programs can improve local mobility, but they often operate separately from fixed route bus networks. This separation can create gaps in connectivity and reduce the potential efficiency of both systems. This project will study how rider hand off strategies, where microtransit vehicles bring passengers directly to fixed route transit, can strengthen system performance. Using data from CTtransit, microtransit logs, and synthetic demand models, the research will simulate multimodal operations and evaluate how pickup schedules and transfer points influence wait times, travel times, and network utilization.

The project will develop an optimization framework to identify operating strategies that improve rider transfers and increase the efficiency of both modes. Scenario testing will measure the effects of integration on cost, ridership patterns, and service quality. The results will provide agencies with practical guidance on how to coordinate microtransit and fixed route services in ways that improve reliability and expand access to transit. These findings can support broader efforts to enhance mobility in Connecticut and inform similar initiatives in other regions.]]></description>
      <pubDate>Thu, 11 Dec 2025 13:47:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640190</guid>
    </item>
    <item>
      <title>Cost-Effectiveness and Service Impacts of Bus Transit Priority Strategies


</title>
      <link>https://rip.trb.org/View/2636146</link>
      <description><![CDATA[Transit agencies across the United States are increasingly implementing transit priority strategies to improve service reliability, travel times, operating efficiency, and customer experience. Common transit priority measures include transit signal priority (TSP), bus-only lanes, queue jumps, stop consolidation, and bulb-outs.

As agencies invest in these strategies, there are increasing expectations to justify expenditures based on measurable outcomes, including travel time savings, reliability improvements, operating cost efficiencies, ridership growth, environmental benefits, safety outcomes, and return on investment. Minimal methods exist to evaluate the costs, benefits, and long-term effectiveness of transit priority treatments across varying service characteristics, roadway conditions, land use contexts, and institutional environments.

TCRP Synthesis 149: Transit Signal Priority: Current State of the Practice (2020) documents current agency practices, deployment approaches, technologies, implementation challenges, and lessons learned associated with TSP. TCRP Research Report 262: Transit Capacity and Quality of Service Manual, 4th edition (2026) advances methods for evaluating bus speed, reliability, and capacity. Research is needed to give transit agencies guidance on evaluating, comparing, prioritizing, and implementing bus transit priority investments.

OBJECTIVE: The objective of this research is to develop a guide, with supporting evaluation frameworks and decision-making tools, to enable transit agencies to assess, compare, prioritize, and communicate the costs, benefits, and effectiveness of bus transit priority strategies.]]></description>
      <pubDate>Mon, 08 Dec 2025 19:58:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2636146</guid>
    </item>
    <item>
      <title>Comparing Pricing Mechanisms of Managed Lanes: Performance Assessment of PR-22 Dynamic Toll Lanes</title>
      <link>https://rip.trb.org/View/2589111</link>
      <description><![CDATA[A performance assessment and willingness-to-pay (WTP) analysis were conducted of the reversible dynamic toll lanes (DTL) of freeway PR-22 in Puerto Rico. This is the first managed lane facility of its kind in a toll freeway in Puerto Rico. Toll transactions from the year 2019 were used to calculate seven performance measures to assess the impact of the managed lanes on travel times and vehicle speeds on the 12 km-long (7.7 mi) segment. The results demonstrate that the dynamic pricing algorithm behaves as expected, increasing the price for the DTL as traffic increases and vehicle speeds decrease on the facility, and provided satisfactory performance for the conditions at PR-22. The DTL provided an average travel time savings of 7 minutes and enhanced travel time reliability when compared with the general toll lanes (GTL) during the morning peak period. Compared to six other managed lane facilities in the U.S., the results from the PR-22 DTL show higher travel time savings and reliability. A survey of PR-22 users was conducted to estimate their willingness-to-pay (WTP) and their attitudes and perceptions associated with the quality and usage of the DTL. The aggregate analysis of PR-22 users using the Van Westerndorp Price Sensitivity Meter resulted in a WTP range for the DTL of $1.00 to $2.79, which is less than the $4.95 maximum toll charged for the managed lane facility. Even though the maximum price exceeds their WTP, the level of congestion in the GTL during peak periods still motivates users to pay the extra fee for the DTL outside of their preference. A regression analysis found that the factors that significantly reduce the WTP of the freeway users include subjects from higher income levels, higher ages, and females. As stated by freeway users, the congestion in the GTL is the main factor that influence them to use the DTL. Therefore, a recommendation to increase the usage of the PR-22 DTL is to provide commuters with relevant information about the real-time benefits of the DTL. The implementation of a high-occupancy vehicle (HOV) policy for the freeway corridor should also be studied. A HOV policy could promote ridesharing on the corridor while providing economic relief and reducing or eliminating the premium toll fee of the managed lanes to some commuters.]]></description>
      <pubDate>Sat, 16 Aug 2025 23:49:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/2589111</guid>
    </item>
    <item>
      <title>Express Lanes Benefitting Freight Mobility: Can Express Lane Systems and its Benefits to General-purpose Lanes Improve Freight Mobility?</title>
      <link>https://rip.trb.org/View/2553996</link>
      <description><![CDATA[The objectives of the research project include the following: (1) assess the impact of Express Lanes on freight movement efficiency; (2) evaluate changed in travel time and improve safety; (3) analyze the impact on freight delivery reliability and efficiency, examine the economic impacts of Express Lanes associated with freight movements; (4) quantify cost changes for truck drivers and truck companies; (5) assess potential economic benefits to the region, evaluate the environmental impacts of Express Lanes associated with freight movements; (6) estimate reductions in greenhouse gas emissions; and (7) estimate savings in fuel consumption.]]></description>
      <pubDate>Fri, 16 May 2025 07:20:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/2553996</guid>
    </item>
    <item>
      <title>Improving Travel Time Data Integration and Estimations for Strategic Prioritization</title>
      <link>https://rip.trb.org/View/2452921</link>
      <description><![CDATA[Travel time and travel time savings are key to measuring the performance of many of the projects submitted through the Strategic Prioritization process to determine which projects will be programmed in the State Transportation Improvement Program (STIP). The process includes travel time values from two sources: data from the statewide travel demand model at the corridor and 24-hour level, and data from microsimulation at the intersection and peak hour level. These two sources produce results that are not immediately comparable and involve different levels of specificity, which limits the application of travel times within the Strategic Prioritization process. 

The primary goal of this research is to identify options for improving travel time savings values produced by North Carolina Department of Transportation (NCDOT) for highway projects in the STIP context. The feasibility of increasing the accuracy and consistency of travel time savings will be explored. By leveraging the strengths of microsimulation and aligning it with statewide models, the accuracy and application of travel time data for highway projects in the STIP can potentially be improved, leading to more informed project prioritization and resource allocation decisions. 

In order to develop the most informed options for NCDOT, the current related practices at NCDOT and other modern approaches for producing and integrating travel time data sources used by other DOTs will be reviewed. This information will guide analyses conducted to identify options for improving travel time savings. This iterative process will involve experimentation with different alternatives, testing these alternatives using project data submitted through the prioritization process, and presenting results to key stakeholders whose feedback will be incorporated into each iteration of analysis. By understanding the differences in data granularity, accuracy, and applicability, the research team can work toward aligning the two data sources to enhance the accuracy and consistency of travel time savings values within the STIP context.

Documentation will be delivered at every phase of this project to provide NCDOT with resources that can be used immediately and into the future. Key results of this work will be documented in a white paper NCDOT can use to communicate the current state of the practice related to travel time data and analysis at NCDOT and nationally. Presentations that outline incremental project progress and are suitable for sharing with the Prioritization Workgroup, a white paper outlining options for improving travel time savings, a technical guide detailing any recommended methodological changes, and a final report will be developed. Every research activity will be conducted with a focus on helping NCDOT achieve the goal of improving travel time savings estimations in an evidence-based way.]]></description>
      <pubDate>Fri, 15 Nov 2024 16:26:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2452921</guid>
    </item>
    <item>
      <title>Impact of All-Way Stop Control Intersections Along Rural and Suburban Corridors</title>
      <link>https://rip.trb.org/View/2452869</link>
      <description><![CDATA[All-way stop control (AWSC) is a superb intersection treatment, producing large crash savings and even mobility at a low cost. In North Carolina, previous research efforts sponsored by the NC Department of Transportation (NCDOT) revealed that AWSC works well under circumstances that previously thought to be questionable including but not limited to large truck percentages, unbalanced demands, and on high-speed roads. Hence, AWSC has been considered by NCDOT as the leading safety treatments. To date, there are more than a hundred AWSC intersections across the state, with more to be installed in the near future.

However, the precondition for AWSC to keep users safe is that drivers are compliant with stop signs, which is not always possible, particularly if drivers see no reason for a stop sign or if drivers are frustrated by the overuse of stop signs. In summary, the effectiveness of an AWSC will be achieved when used at the right place and under the right conditions, while overuse of AWSCs may reduce their effectiveness. While in current practice, there lacks a clear and scientific understanding of the effects of high concentrated AWSCs on the mobility of corridors and drivers’ compliance to stop signs. In this regard, there is an urgent need to investigate if there are factors or thresholds that provide reduced safety benefits when AWSC installations are installed in succession along a corridor. If increases in risk are proven to be related to one or more factors, it is necessary to understand when those safety risks are most likely to be present and why.

The proposed research aims to collect measurable data on the mobility and safety performance of corridors with successive AWSCs and investigate driver behavior when driving through concentrated AWSCs. Specifically, the objective of this research is to (1) investigate safety performance of concentrated AWSCs in terms of crash rate and driver compliance to successional AWSC intersections; based on which, figure out factors that affect drivers compliance to AWSC and assess the potential crash risk caused by violation of stop signs; (2) assess the mobility impacts of AWSC intersection along corridors in terms of travel time and delay, compared to other intersection designs such as two-way stop-control and signal control, etc. The outcome of this research will be practice-ready guidance on the applicability of AWSC intersection along corridors such as the maximum or optimal number of AWSC intersections per unit distance to be deployed along a corridor, which will provide NCDOT planners and engineers with a clear understanding of the density limit on AWSC during the preliminary planning stage of capital improvement projects.]]></description>
      <pubDate>Fri, 15 Nov 2024 15:23:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2452869</guid>
    </item>
    <item>
      <title>Investigating the Impacts of Smart Charging on Electric Vehicle
Charging Choices Within an Activity-based Framework
</title>
      <link>https://rip.trb.org/View/2420065</link>
      <description><![CDATA[The objective of this project is to forecast the impacts of spatio-temporal electricity pricing
on electric vehicle (EV) charging behavior, drawing on established EV charging models and
incorporating considerations such as smart charging acceptance and joint charging-activity
time planning decisions. The research team aims to elucidate how current and future electricity rates may
influence EV driver behavior, while accounting for heterogeneity in charging preferences and
value of travel time. Using the Los Angeles metropolitan area as a case study, the team develops future
year scenarios for EV adoption and charging infrastructure access to evaluate the effects of pricing
strategies on the demand for public infrastructure and EV-related trips. The analysis encompasses
a range of smart charging policies, including spatially and temporally-varying electricity prices linked
to factors such as charging speeds, utility control, location, and enrollment in bill assistance
programs. Results, segmented by travel characteristics such as household income, home charger
access, and EV range will quantify the impact of EV charging prices on both aggregate and
disaggregate network metrics (e.g., vehicle miles traveled and charging cost savings, respectively.)
The results provide insights into the broader implications of electricity pricing strategies for EV
integration within the transportation network. The findings of this project are expected to contribute
to a deeper understanding of EV charging behavior and access and inform the development of
effective demand management strategies within the evolving landscape of transportation
electrification.]]></description>
      <pubDate>Thu, 22 Aug 2024 16:10:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/2420065</guid>
    </item>
    <item>
      <title>Analyzing and Predicting Truck Travel Time Reliability</title>
      <link>https://rip.trb.org/View/2394459</link>
      <description><![CDATA[Truck travel time reliability (TTTR) is one of the most important performance measures for assessing freight movement on the interstates. The Virginia Department of Transportation (VDOT) and the Office of Intermodal Planning and Investment (OIPI) have been reporting TTTR as required by the FHWA and using TTTR in various project planning and performance measurement processes. They are interested in data-driven approaches to identify the locations and causes of unreliable truck travel times and to predict TTTR metrics. This study will address the research needs by developing a systematic method to identify the location, time period, and causes of unreliable truck travel times, and develop models to predict TTTR.   ]]></description>
      <pubDate>Tue, 18 Jun 2024 09:51:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2394459</guid>
    </item>
    <item>
      <title>Impacts of Shared Autonomous Vehicles on Traffic Operations (4.17)</title>
      <link>https://rip.trb.org/View/2378075</link>
      <description><![CDATA[As global demand for ride-hailing services rises, there is an increased urgency to study shared autonomous vehicles (SAV) fleets and their impacts on regional travel. According to Schaller (2018), the number of ride-sourcing vehicles and trips in New York City from 2013 to 2017 increased by 59% and 15%, respectively. In the same period, the number of idle vehicles increased by 81% and ride-sourcing drivers spent more than 40% of their time empty and cruising for passengers, which increased vehicle-miles travelled (VMT) by 36%. The same trends are expected to happen for ridesharing using SAVs if appropriate policies are not used to manage the empty VMT. For this reason, this proposed project aims to understand the impacts of ride-sharing, especially through shared autonomous vehicles on traffic operations and infrastructure durability (including the wear and tear of these vehicles on asphalt) in Connecticut. Investigating this impact requires the simulation of traffic for the entire population in the state under different ride-sharing scenarios. Traffic simulation tools require multiple datasets and calibrated models, which are different for each region. The research team plans to use a traffic
simulator, such as POLARIS, which is an agent-based traffic simulation tool developed by Argonne National Laboratory, for SAV simulations. These tools allow for simulating multimodal traffic over large-scale transportation networks and requires multiple inputs and models calibrated for each specific region. Therefore, the research team will collect the required data and estimate models, including but not limited to activity generation, mode choice, and destination choice models, specific to Connecticut. The expected findings of this study could provide valuable insights into the impacts of autonomous vehicles and ride-sharing options provided by these vehicles on traffic operations including but not limited to VMT, empty VMT, and total travel time, as well as travel patterns in the state of Connecticut. These traffic operations and travel patterns will impact the deterioration of asphalt, which will be investigated in this study through the surface damage index.]]></description>
      <pubDate>Thu, 09 May 2024 15:15:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2378075</guid>
    </item>
    <item>
      <title>The 15-Minute City Quantified Using Mobility Data</title>
      <link>https://rip.trb.org/View/2350712</link>
      <description><![CDATA[In response to social and environmental challenges faced by cities worldwide, policymakers are embracing the "15-minute city" planning model, positing that most human needs should be met within a short walk from home. The 15-minute city's popularity stems from rising congestion, air pollution, climate change, energy consumption, sprawl, and a loss of social interactions, motivating cities to aim for more livable, people-oriented spaces. This popular vision of urban living has taken many names and shapes, such as Paris's 15-Minute City, Portland's Complete 20-Minute, Charlotte's 10-Minute neighborhoods, and Melbourne's 20-Minute neighborhoods. Despite its rising popularity, there is currently no large-scale empirical evidence that can be used to measure exactly how aligned cities and neighborhoods are with the 15-minute vision and assess the distributional implications of advancing that vision. Moreover, there are rising concerns that the decentralization of economic activity and fostering of more inward-focused communities, especially in the context of sprawling and highly segregated North American cities, could exacerbate existing social divides and limit economic efficiency by disrupting the inter-neighborhood flows of people and ideas. In this project, PIs introduce a new measure to quantify local trip behavior using Global Positioning System (GPS) data from 40 million mobile devices across the US. This study defines local usage as the share of trips made within 15 minutes of walking from home. Finally, PIs will test the hypothesis that fomenting 15-minute access and usage could increase the level of segregation in the city.]]></description>
      <pubDate>Mon, 11 Mar 2024 21:32:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2350712</guid>
    </item>
    <item>
      <title>Ecological Driving System for Connected Automated Vehicles: A New Model Predictive Control Framework</title>
      <link>https://rip.trb.org/View/2343737</link>
      <description><![CDATA[The growing importance of sustainable and eco-friendly transportation has spurred the need for effective solutions to optimize the operational efficiency of connected automated vehicles (CAVs) in such complex environments. The trajectory planning problem (TTP) for CAVs is complicated by non-linear constraints, especially when dealing with the Eco-trajectory Planning Problem (EPP), characterized by its nonlinear, high-order, and non convex objective function. To tackle this challenge, the research team proposes a novel heuristic explicit predictive model control (heMPC) framework and aim to develop an innovative multi-objective ecological driving system that optimizes CAVs' trajectories along signalized arterial roads. Three key objectives are targeted: minimizing travel time, reducing fuel consumption, and improving traffic safety. The proposed framework comprises two interlinked modules: an offline module and an online module. In the offline module, the team will construct an optimal eco-trajectory batch by optimizing a series of simplified EPPs, considering diverse system initial states and terminal states. This process can be
likened to a lookup table in the general eMPC framework, with the intention of precomputing all necessary optimizations and calculations to eliminate online optimization in the subsequent stage. In the online module, the team will employ both static and dynamic trajectory planning algorithms to efficiently handle trajectory planning for CAVs. After proving the effectiveness of the proposed algorithms in the simulation environment, the team will test the entire system with field studies, leveraging the in-house CAV in the lab.]]></description>
      <pubDate>Thu, 22 Feb 2024 15:57:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2343737</guid>
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