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    <title>Research in Progress (RIP)</title>
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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>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Health and Activity Impacts of Student Commute Modes</title>
      <link>https://rip.trb.org/View/2652176</link>
      <description><![CDATA[Active school transportation can profoundly influence children’s health, safety, and wellbeing. This project will investigate how different school commute modes – walking, bicycling, school bus, or private car – affect student physical activity and health, exposure to traffic-related air pollutants, safety, and travel disparity. Focusing on Texas school districts that currently or historically participate in Safe Routes to School (SRTS) programs, we will combine new data collection with existing evidence to evaluate the benefits and challenges of various commute modes. The study will also examine how shifting school trips to active modes may reduce vehicle emissions near schools and improve air quality. We will conduct surveys to quantify students’ physical activity during commutes, assess their exposure to emissions, and gauge perceptions of safety. Recent literature (2015–2025) will be synthesized to identify how school transportation choices affect student health (e.g. obesity, respiratory health, mental wellbeing) and safety outcomes, including disparities by socioeconomic status and geography. By evaluating SRTS interventions’ effectiveness in Texas communities, the project will fill critical gaps in understanding the multi-faceted impacts of commute mode on student wellbeing. Expected outcomes include practical recommendations for school districts and transportation agencies to design safer, healthier school travel environments. ]]></description>
      <pubDate>Tue, 13 Jan 2026 15:25:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652176</guid>
    </item>
    <item>
      <title>Evaluating isolated areas, alternative routing, and economic impact for resilient transportation in North Carolina</title>
      <link>https://rip.trb.org/View/2604572</link>
      <description><![CDATA[Natural disasters, such as flooding, landslides, storm surge, and wildfire can cause severe impacts to the social, environmental, economic, and transportation systems of North Carolina. At the same time, transportation infrastructure plays a critical role in natural disaster response and recovery efforts during these natural disaster events. Unfortunately, extreme hazard events such as these are occurring with greater frequency and intensity. These events can negatively impact road functionality and lead to the loss of essential services. According to the National Oceanic and Atmospheric Administration (NOAA), weather-related disasters have cost over $1.875 trillion since 1980. The built environment isn’t designed to handle many of the impacts that are happening due to extreme hazard events. For example, stormwater systems, culverts, and tidal pumps were all designed for past events— not current and future conditions. The failure of these systems will impact  communities to a level where they may not be able to return to normal for months or years.

Transportation planners and engineers from North Carolina Department of Transportation (NCDOT), as well as other federal, state, and local agencies across the state, and in close collaboration with emergency managers, are increasingly looking for better ways to address these issues and become more resilient, while simultaneously planning for a more reliable transportation network. Planning for extreme events is about finding ways for systems to bounce back to normal as quickly as possible after the negative impacts of an event. One particular issue that NCDOT faces is the rerouting of traffic during and immediately after natural disaster events. Typical considerations include traffic volumes, current conditions, roadway capacities, and overall safety. However, there are other considerations such as the overall economic impact, including issues like commerce, commute times for individuals traveling between work and home, access to essential services, and disruption to local businesses, that should also be taken into account. These impacts can be further compounded in areas where entire networks of roads, such as a neighborhood or community, become cut-off due and thus isolated. This isolation can be due to such factors as a damaged bridge or road washout. Worse yet, these impacts can often last for days or even months. By identifying these areas ahead of time, and better understanding the potential economic impacts, NCDOT and other agencies can be better equipped when planning for a more resilient and sustainable transportation infrastructure system.

The joint proposal team, consisting of researchers from the University of North Carolina at Asheville’s National Environmental Mapping and Applications Center (NEMAC) and the University of North Carolina at Charlotte, proposes a comprehensive and innovative approach to helping NCDOT better understand the forces behind transportation route and commute pattern disruptions, and their effects on local economies, in the face of an increase in extreme hazard events. Through comprehensive user research and discovery, data analysis, and the development of decision-making workflows, the project team seeks to provide NCDOT with actionable insights to better plan and respond to disruptions related to extreme hazard events, ultimately improving infrastructure reliability and community access.]]></description>
      <pubDate>Tue, 30 Sep 2025 11:13:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2604572</guid>
    </item>
    <item>
      <title>Financial Incentives to Promote Multi-passenger Commuting</title>
      <link>https://rip.trb.org/View/2499289</link>
      <description><![CDATA[In California in 2022, according to CARB, passenger car vehicle miles of travel (VMT) produced 27.6% of overall human-caused greenhouse gas (GHG) emissions. USDOT Bureau of Transportation Statistics (BTS) has California commuting to work in 2017 at about 17% of automobile travel, and single occupant travel is predominant in cars at 65% of commuting trips as of 2022. An important, feasible alternative mode for reducing transportation’s impact on climate change is high occupancy vehicle (HOV) commuting in private vehicles, that is, carpooling and vanpooling. According to USDOT BTS, this mode already has a 2022 work travel market share in California of 9.8% (including drivers) notably exceeding the 2.7% share for public transit. Pooling is a point of attack on carbon. It is an available mode where there is no public transit service in operation. Ten single occupant vehicle (SOV) commuters to a suburban office park deciding to cooperatively travel pairwise in five cars would represent a 50% reduction in commuting VMT for them. The policy challenge is how to motivate cooperative commuting that generates HOV travel and reduces VMT. This proposal is about motivating more pooling. However, it’s also important to note that if ten regular bus passengers decided because of a new incentive scheme to switch to carpooling in five personal ICE automobiles, more carbon would be the result, and the revenue stream of the bus agency would take a hit as well. The project team will take this scenario seriously.

There is growing interest in using financial incentives (generally, cash payments but sometimes gift payments), to reward a shift from SOV driving to passenger travel, by carpool, vanpool, or transit. A 2018 project, Congestion-Clearing Payments for Passengers, (CCPTP) tested for the first time the idea of using incentives at a congestion-clearing level. The CCPTP project established a methodology for defining and evaluating a “build nothing – pay passengers” option as a potential alternative to highway expansion.

In the CCPTP project report, a reward curve was estimated showing the amount of reward needed per day per passenger to encourage a given proportion of commuters to shift to passenger travel on the case study route. The basis for the reward curve estimation was a survey of residents of Half Moon Bay and nearby communities that make up the catchment of travelers that might use Highway 92 to travel to work or play in Silicon Valley. This was the first time such a reward curve had been estimated in this way. The survey showed significant potential for financial incentives to reduce congestion. The estimated benefit-to-cost ratio was 4.5, and estimated value creation of half a billion dollars over a 20-year period. 

The CCPTP researchers cautioned that the reward curve might not be generalizable to other catchments or congested routes, work should be done to improve the quality of the estimation, and survey results (stated preference) should be calibrated to actual results (revealed preference). The CCPTP survey was completed prior to the COVID-19 pandemic, and the impact of the pandemic on the estimated reward curve should also be investigated. However, the team will make an assessment of this impact based on published research in the 2020s.

The reward curve has subsequently been used to support proposals for the use of incentives to reduce traffic. The Minett, Niles, et al. CCPTP project reached worldwide visibility in a peer-reviewed article that has been cited subsequently by several researchers. Since 2020, Patrick DeCorla Souza, outside of his professional duties in the U.S. DOT Federal Highway Administration, has been designing an innovative plan to incorporate carpooling incentives into new configurations of managed lanes on urban expressways, as documented in several publications. Minett, Niles, et al. (2020) has also been cited by researchers in China exploring the effectiveness of different types of non-cash gift incentives, by Greek researchers seeking linkages of carpooling to “smart city” projects, and by Florida researchers exploring randomized controlled trial methodologies for validating a particular MaaS smartphone app.

The CCPTP reward curve has been used in an evaluation of a concept referred to as HOTTER (High Occupancy, Transit, or Toll in Existing lanes for Rewards) lanes, in which a subset of existing lanes on a major highway would be converted to High Occupancy or Toll (HOT) lanes, and the toll revenues would be used to pay incentives to those who shifted to passenger travel.

The HOTTER lanes evaluation found that there would be a significant surplus of toll revenue after paying incentives and other operating costs and that HOTTER lanes would improve person throughput while reducing vehicle throughput. HOTTER lanes have been discussed as a potential solution for application in California. This present proposal for improving the reward curves is supported by the previously mentioned HOTTER researcher, by Caltrans managers, and by transportation thought leader Michael Replogle.]]></description>
      <pubDate>Fri, 31 Jan 2025 19:03:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2499289</guid>
    </item>
    <item>
      <title>The Effects of Changing Commutes on Home Delivery Activity</title>
      <link>https://rip.trb.org/View/2440043</link>
      <description><![CDATA[Since the COVID-19 pandemic, New York, like most US and global cities, has seen rapid evolution of (1) work location and time flexibility and (2) adoption of online shopping alternatives for diverse commodities by varying shopper populations.  It is expected that changes in work location – particularly the increased opportunity for some individuals to work from home at least a few days per week – could have profound impacts on the choice of location for shopping activities and on the likelihood of receiving home deliveries. 

Relying on the New York City Department of Transportation’s forthcoming 2022 Citywide Mobility Survey (CMS) and publicly-available land-use and employment data, this project will explicitly investigate the relationship between work-related travel activity (or lack thereof) and propensity for home delivery.  This study will distinguish individuals based on demographic characteristics, home and work built environments (e.g. land uses and building types) and commute characteristics (e.g. frequencies, modes, times of day), and will evaluate shopping frequencies for several specific categories of goods - including groceries, prepared food, and parcels. Results are expected to provide insights on the expected impacts of changing work on local delivery activity, to inform the design of future urban freight infrastructure and city logistics strategies in work- and residence-oriented communities, and to provide insights for potential implications for local travel and retail activity.
]]></description>
      <pubDate>Sun, 13 Oct 2024 16:13:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440043</guid>
    </item>
    <item>
      <title>Promoting Commute Equity in Maryland: A Machine Learning-Based Model Development Proposal</title>
      <link>https://rip.trb.org/View/2343827</link>
      <description><![CDATA[Unequal mobility and accessibility have been a key constraint in accessing jobs, education and healthcare and other opportunities across the nation. This is aggravated by differences in income, transport infrastructure, transit and indeed all modes, vehicle availability, class of workers and other variables which individually or collectively contribute to the commute inequity. Evaluating these can be challenging because there are types of equity and impacts to consider including horizontal and vertical commute equities and various ways to measure them. Horizontal equity assumes that people with similar needs and abilities should be treated equally; vertical equity assumes that disadvantaged groups should receive a greater share of resources. Through the utilization of cutting-edge machine learning techniques and conducting a comprehensive analysis of the factors influencing commute equity, this project aims to empower Maryland policymakers with an effective decision-making framework.]]></description>
      <pubDate>Thu, 22 Feb 2024 16:07:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2343827</guid>
    </item>
    <item>
      <title>Evolution of Mode Use Due to COVID-19 Pandemic in the United States: Implications for the Future of Transit</title>
      <link>https://rip.trb.org/View/2137504</link>
      <description><![CDATA[The COVID-19 pandemic has brought about transformative changes in human activity-travel patterns. These lifestyle changes were naturally accompanied by and associated with changes in transportation mode use and work modalities. In the United States, most transit agencies are still grappling with lower ridership levels, thus signifying the onset of a new normal for the future of transit. This report addresses this challenge using a novel panel survey data set collected for a representative sample of individuals from across the United States. The study involved the estimation of a panel multinomial probit model of mode choice to capture both socio-economic effects and period (pre-, during-, and post-COVID) effects that contribute to changes in mode choice. This work provides rich insights into the evolution of commute mode use as a result of the pandemic, with a particular focus on public transit. Through a rigorous modeling approach, this study provides a deep understanding of how transit use has evolved, how it is likely to evolve into the future, and the socio-economic and demographic characteristics that affect the evolution of (and expected future use of) public transit. Results suggest that transit patronage is likely to remain depressed by about 30 percent for the foreseeable future, in the absence of substantial changes in service configurations. This study also shows that minority groups and those living in higher density regions are more likely to exhibit transit use recovery in the post-pandemic period.]]></description>
      <pubDate>Tue, 14 Mar 2023 12:39:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2137504</guid>
    </item>
    <item>
      <title>What Is the New Normal? An Analysis of Post-COVID-19 Commute and Work Patterns</title>
      <link>https://rip.trb.org/View/2087424</link>
      <description><![CDATA[The study is addressing the following questions: (1a) What are the adoption rates and frequencies of working from home in Spring 2022 (representing at least the “back side” of the COVID-19 pandemic, if not yet completely post-COVID), and what are the intentions to continue to work remotely in the future? (1b) What demographic, geographic, and attitudinal characteristics are associated with adoption/non-adoption, higher or lower frequencies? (2a) What is the distribution of one-way commute lengths, and how has that distribution changed since before COVID-19? (2b) Putting one-way commute lengths together with commute frequencies, what is the distribution of total weekly commute distance traveled, and how has that distribution changed since before the pandemic? (2c) What socio-economic and other characteristics are associated with one-way commute lengths and total weekly commute distances? (3) How have the shares of commute modes changed since before the pandemic, and what characteristics are associated with those changes? To address these questions, we have designed, and are in the process of fielding, an online survey of employed Georgia residents. The study team is recruiting approximately 2000 respondents through an online opinion panel vendor (Qualtrics). Ultimately, the team will also develop models of key behavioral indicators, to enable them to control for multiple behavioral influences simultaneously.]]></description>
      <pubDate>Wed, 21 Dec 2022 10:56:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/2087424</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S06-08. Exploring Airport Employee Commuting and Transportation Needs</title>
      <link>https://rip.trb.org/View/2077889</link>
      <description><![CDATA[ACRP Synthesis 136: Exploring Airport Commuting and Transportation Needs, from TRB's Airport Cooperative Research Program, describes how airport employees commute to and from work and how airports are seeking to influence employee transportation decisions.]]></description>
      <pubDate>Mon, 05 Dec 2022 18:17:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2077889</guid>
    </item>
    <item>
      <title>Distribution of Potential Benefits across Stakeholder Groups for Shared Electric Vehicles Serving Multi-University Commute Travel</title>
      <link>https://rip.trb.org/View/2008007</link>
      <description><![CDATA[Transit, shared mobility, and vehicle electrification serve as major enablers of transportation decarbonization. Several shared mobility have been offered in the US and abroad, with a major focus on implementation on university campuses and at airports. However, combined offerings of shared and electric vehicles providing on-demand service rather than route-based service are still 
forthcoming. In this proposed project, we will assess the greenhouse gas (GHG) reduction potential and potential equity impacts of the deployment of shared electric vehicles servicing student, faculty, and staff commute travel to and from three university campuses), REDACTED assess the distribution of accessibility benefits across these cohorts and across demographic groups within these cohorts, and characterize the policy implications of widespread implementation of such university transportation systems. This research project will (1) identify the potential users and use cases of shared electric vehicles serving university commute travel; (2) estimate the potential for GHG reduction and other benefits for different technology deployment and policy scenarios; (3) assess the distributional differences of the estimated benefits across stakeholder groups; and (4) recommend measures to remove barriers to adoption of shared electric vehicles and increase equitable shared electric fleet programs. In this project, the three teams will conduct a survey of potential users of shared and electric fleet. To this end, all three campuses will utilize the large scale transportation survey data to obtain sociodemographic and travel behavior characteristics of the students, staff, and faculty. To characterize energy use and emissions from the existing transportation system and the system after the anticipated shift in commute activity to shared-use vehicles will be conducted using MOVES-Matrix and the Georgia Tech Fuel and Emissions Calculator (FEC). The team will assess how these costs and benefits are distributed across the student, faculty, and staff user groups by income, race, and other demographic factors. The results of this project can be used in long-range planning for shared electric programs in complex, multi-stakeholder institutional environments.
]]></description>
      <pubDate>Tue, 16 Aug 2022 18:26:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/2008007</guid>
    </item>
    <item>
      <title>Estimating the Impact of COVID-19 on Travel Behavior and Perceptions: An Investigation of Commuting Travel and Intercity Travel in the Northeast Megaregion</title>
      <link>https://rip.trb.org/View/1767651</link>
      <description><![CDATA[The impact of COVID-19 on transportation– both for routine commuting and for less routine intercity transportation trips – has been significant and uneven across modes. As traveler concerns, beliefs, behaviors, and actual travel needs have changed, there are concerns related to the use of pre-COVID-19 travel data to predict travel demand going forward. The extent to which the COVID-19 pandemic will shift the propensity to travel and the mode of travel – both because of changing norms and changing needs – is an open and highly consequential question. The goal of this project is to understand future travel demands (both in trip generation and mode choice) for trips generated from a major anchor institution for both routine commuting and intercity transportation. Through a survey of more than 400 members of the faculty and staff at the University of Pennsylvania – the largest trip generator in the Delaware Valley Region in the Northeast Megaregion – and other sites about travel behaviors prior to the COVID-19 pandemic and their perceptions and plans for travel in the future – the research team will build models that provide new understanding into how changing perspectives and travel needs will shape the future of commuting and intercity travel. The analysis will provide planners, from those looking to incentivize sustainable behavior and control congestion to those planning scheduled transportation modes, with a spatial scenario analysis tool to evaluate future local, regional, and megaregional travel patterns.]]></description>
      <pubDate>Thu, 04 Feb 2021 17:44:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/1767651</guid>
    </item>
    <item>
      <title>Understand the Diverted and Induced Demand of UAM</title>
      <link>https://rip.trb.org/View/1763977</link>
      <description><![CDATA[Traffic congestion and consequent excessive air pollutant emissions are leading sustainability issue in the United States. Urban Air Mobility (UAM) is an emerging concept proposed in recent years that uses electric vertical take-off and landing vehicles (eVTOLs), which is expected to offer an alternative way of transporting passengers and goods in urban areas with significantly improved mobility by making use of low-altitude airspace. Also, eVTOLs generate zero air pollutant emissions during operations. If the electricity (or partial of the electricity) comes from clean and renewable resources and eVTOLs are used efficiently, then UAM is also expected to be an environmentally friendly transportation mode. 
In current limited references, authors assumed simplified mode choice decisions for estimating diverted demand from existing ground transportation modes, and also did not estimate induced demand that could be caused by the system performance improvement due to the introduction of UAM. Such induced demand includes induced ground traffic demand due to mitigated traffic congestion and induced demand of UAM service due to improved mobility. 
In this study, the research team will design a stated preference survey questionnaire to investigate the potential of UAM in context of relieving ground congestion, willingness to pay, and mode shift. First, the current research aims to design an exploratory framework that will contribute to understanding how to approach the analysis of diverted and induced demand in case of UAM. Second, it will provide more insights on the factors (both psychological attitudes and socio-demographic characteristics) that will play a role in the adoption of UAM. Third, the study will explore how daily commute times and congestion status in respondents’ current locations relate to the willingness to pay for UAM and willingness to use UAM.
To answer the abovementioned research questions, both qualitative and quantitate analysis will be performed. The qualitative approach will allow to capture, analyze, and explain the behavioral component of study while the quantitative methods such as advanced statistical and econometric models will provide additional insights into the relationship between dependent variable of interest and independent variables.
Lastly, utility functions with expanded transportation mode choices will be explored to estimate diverted demand and induced demand. 
]]></description>
      <pubDate>Fri, 15 Jan 2021 14:48:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/1763977</guid>
    </item>
    <item>
      <title>Modeling and Optimizing Ride-sourcing Services in Connected and Automated Cities</title>
      <link>https://rip.trb.org/View/1697988</link>
      <description><![CDATA[This project proposes a modeling framework to integrate ride-sourcing services and connected/automated vehicles with transit to serve different users in an urban area. Multiple travel modes are considered for morning commute:  single ride and shared ride in ride-sourcing, and integrated ride-sourcing (either single ride or shared ride) and transit. Simulation testing and validation will be conducted on a multi-modal network in the Seattle area.]]></description>
      <pubDate>Thu, 16 Apr 2020 09:07:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/1697988</guid>
    </item>
    <item>
      <title>Institutions and Information Technology to Support Service Integration in Multimodal Employment Transportation </title>
      <link>https://rip.trb.org/View/1635489</link>
      <description><![CDATA[​The Madison, WI region is adding more jobs than workers and currently faces a labor shortage. To address this challenge, in 2018, the Wisconsin Department of Workforce Development launched the Commute to Careers program (CtC) to reduce transportation barriers for unemployed, low and moderate-income workers.  

In October 2018, Union Cab Cooperative of Madison—the largest taxi company in Madison—was awarded a CtC grant to develop an affordable shared ride taxi service. The objectives of the rideshare intervention were twofold: (1) economic development through more efficient, cost-effective use of the existing transportation system, and (2) better access to jobs and opportunities. Union Cab CtC began serving riders in December 2018. Preliminary data from a survey of riders shows that the program is reaching a population of low-income workers, but it needs to be scaled up to accomplish its goal of providing shared rides to a larger target population in a sustainable model.   

In response, Union Cab has proposed to coordinate its service with JobRide, a vanpool program operated by YWCA Madison. JobRide has a waitlist of riders who want to join the vanpool. By working together, Union Cab and JobRide could serve these riders on the waitlist and combine their models into a feeder and trunk route system that could prove more efficient and attract employer investment. However, this calls for an even greater need for robust program evaluation in order to assess the effectiveness of the individual and combined interventions at meeting their objectives.  

Thus, the research team proposes to conduct process and outcomes evaluations of the integrated demonstration project carried out by Union Cab and JobRide, which will advance CTEDD’s mission through an industry-community-university partnership that combines applied research, technology transfer, evaluation, outreach, and education. Through a rigorous investigation, the team will learn whether the integrated demonstration results in economic development through more efficient, cost-effective use of the existing transportation system, and better access to jobs and opportunities. This project represents a Level 7 Technology Readiness Level 1 approaching Level 8 because it is a prototype being demonstrated in an operational environment. ​ ]]></description>
      <pubDate>Thu, 04 Jul 2019 11:15:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/1635489</guid>
    </item>
    <item>
      <title>Environmental Attributes of Electric Vehicle Ownership and Commuting Behavior in Maryland: Public Policy and Equity Considerations</title>
      <link>https://rip.trb.org/View/1604405</link>
      <description><![CDATA[This research investigated the socio-demographic attributes that contribute to electric vehicle (EV) ownership and EV owners’ commuting behavior based on different types of developed human settlements such as city, suburb, and rural area. EVs still are pricier than comparable internal combustion engine vehicles (ICEVs). The objective of this study was to suggest public policies and recommendations to decision makers to prompt EV ownership equitably by identifying socio-demographic factors that influence the purchasing/leasing decision. The State of Maryland promotes EV ownership by subsidizing EV purchases and deploying charging facilities at transit rail stations. The other objective was to determine mode choice by EV owner commuters. An online survey of EV (non-fleets) owners registered in Maryland was conducted from July 1, 2016, to August 19, 2016. In total, 1,257 EV owners completed the survey. After assessing data quality, the survey data were tabulated and visualized to observe general trends that helped construct appropriate hypotheses and statistical models. Multinomial logistic regression models (MNL) were constructed to examine the associations between EV owner characteristics and their reasons for purchasing/leasing the EV. The findings revealed five key points. First, socioeconomic attributes such as age, education, income, household size, marital status, number of vehicles in a household, and political affiliation significantly affected EV owners’ preference when making purchasing/leasing decisions. Second, environmental concerns were the main reason for purchasing and driving an EV; vehicle price was the third most important factor. Third, very few EV owners used rail transit for the commute to work prior to EV purchase, and even fewer after purchase. Fourth, EV owners who had longer commuting trips were more concerned about price and operating costs and efficiency and performance of the EV than those with shorter commuting trips. Fifth, some significant similarities and differences are found in the travel patterns of both EV and ICEV owners]]></description>
      <pubDate>Mon, 06 May 2019 16:41:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/1604405</guid>
    </item>
    <item>
      <title>Assessing Potential of Bike Share Networks and Active Transportation to Improve Urban Mobility, Physical Activity and Public Health Outcomes in South Carolina</title>
      <link>https://rip.trb.org/View/1578216</link>
      <description><![CDATA[Description: There is need for evidence-based research about how, when, where, and why people undertake active travel, like bicycling and walking, and about how the built environment and infrastructure may or may not accommodate active travel. As stated in the National Physical Activity Plan, transportation and public health entities should collaborate to “improve and expand existing data collection sources to assess active transportation patterns and trends that include local-area data.” Charleston, South Carolina has the conditions necessary to promote active travel, such as supportive stakeholders and a walkable built environment, as well as the tools to study the conditions under which active travel may thrive. This research will conduct a case study on active travel in Charleston, focusing on issues such as route conditions and the use of bike share programs to better understand how Charleston’s built environment is meeting the health, physical activity, and transportation needs of the community. 

Intellectual Merit: Qualitative, quantitative, and geospatial methods will be used to evaluate active transportation, physical activity, and health outcomes in Charleston, South Carolina.
Broader Impacts: Research results will be beneficial to communities which are undertaking active transportation and bike share initiatives to improve mobility, reduce congestion, promote sustainability, increase levels of physical activity, and bring about desirable public health outcomes.
Technology Transfer: The research team will engage local officials, decision makers, and community stakeholders by communicating its data analysis and results, for example through infographics, formal meetings, and a guidebook. Findings will also be published and presented in national engineering and city planning forums, and will be disseminated to municipalities and other stakeholders via strategic technology transfer channels.]]></description>
      <pubDate>Fri, 11 Jan 2019 14:32:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/1578216</guid>
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