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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>Car Drivers’ Willingness to Pay for Design Related Attributes of Parking Garages: Hierarchical Information Integration Approach</title>
      <link>https://trid.trb.org/View/1641883</link>
      <description><![CDATA[This paper focuses on car drivers’ willingness to pay for design related attributes of parking garages. Car drivers’ willingness is retrieved from a stated choice experiment including three basic attributes (capacity of parking, parking tariff, and walking distance between parking and final destination) and 25 design related attributes. The design related attributes are included in the choice experiment following the principles of Hierarchical Information Integration that grouped the 25 attributes into five constructs: attributes related to the parking area, pedestrian environment, accessibility, service, and safety. Per construct, respondents were invited to choose two times between two parking facilities. The experiment was included in an online questionnaire that was completed by 315 respondents who evaluated in total 3,150 choice tasks. The respondents’ choices are evaluated using a standard multinomial logit model. The results show that the following design related attributes significantly contribute to the total utility of parking garages: the width of parking spaces, the width of road lanes, the type of pedestrians’ routes, the width of staircases, the types of elevator points, the presence of parking guidance systems, the available payment options, the presence of toilets, the level of lighting, the presence of ramps, and the level of cleanliness and maintenance. The respondents are willing to pay most for the available payment options (range €2.91) and the level of cleanliness and maintenance (range €2.69).]]></description>
      <pubDate>Fri, 09 Aug 2019 09:19:23 GMT</pubDate>
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      <title>Functional split brain in a driving/listening paradigm</title>
      <link>https://trid.trb.org/View/1446861</link>
      <description><![CDATA[People often engage in two concurrent but unrelated activities, such as driving on a quiet road while listening to the radio. When they do so, does their brain split into functionally distinct entities? To address this question, the authors imaged brain activity with fMRI in experienced drivers engaged in a driving simulator while listening either to global positioning system instructions (integrated task) or to a radio show (split task). The authors found that, compared with the integrated task, the split task was characterized by reduced multivariate functional connectivity between the driving and listening networks. Furthermore, the integrated information content of the two networks, predicting their joint dynamics above and beyond their independent dynamics, was high in the integrated task and zero in the split task. Finally, individual subjects’ ability to switch between high and low information integration predicted their driving performance across integrated and split tasks. This study raises the possibility that under certain conditions of daily life, a single brain may support two independent functional streams, a “functional split brain” similar to what is observed in patients with an anatomical split.]]></description>
      <pubDate>Tue, 28 Mar 2017 11:38:43 GMT</pubDate>
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      <title>Weather Information Integration in Transportation Management Center (TMC) Operations</title>
      <link>https://trid.trb.org/View/1105683</link>
      <description><![CDATA[This report presents the results of the third phase of an on-going FHWA study on weather integration in Transportation Management Center (TMC) operations. The report briefly describes the earlier phases of the integration study, summarizes the findings from the implementation and evaluation of an automated weather alert notification system in the Sacramento Regional TMC, and discusses the efforts of four TMCs (Cheyenne, Colorado Springs, Kansas City, Louisiana, and Redding) that used the FHWA self-evaluation guide to identify their weather integration needs and strategies that could be implemented to meet those needs. Four of those TMCs prepared weather integration plans with implementation tasks and schedules. The report tracks their progress toward implementing those strategies and identifies the outcomes and benefits they have achieved to date. Efforts to refine, market and promote the self-evaluation guide are also discussed. Finally, lessons learned and recommendations based on the experiences working with a variety of TMCs are offered to encourage and facilitate greater weather information integration in the future.]]></description>
      <pubDate>Wed, 20 Jul 2011 07:25:04 GMT</pubDate>
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      <title>Integrating Information About Complex Systems: Role of Metadata in the Acceptability of Results from Models</title>
      <link>https://trid.trb.org/View/777207</link>
      <description><![CDATA[Opus is a project funded by the European Union Statistical Agency (Eurostat). The project is developing a methodology for the coherent and consistent integration of information from multiple sources about complex systems (based on Bayesian statistical models) and a series demonstration of this approach. Most, but not all, of these are transport applications. Alongside the modeling frameworks being developed, the project has developed a framework for storing a complete audit trail, covering the specification and fitting of statistical models, and making use of a formal metadata specification to represent statistical models. This framework builds on ideas about metadata for processes that have been developed in other statistical projects. Practitioners are often skeptical about results derived from models. In practice, all analysis of survey or sample data involves some form of model, even if it is hidden in implicit assumptions. The approach to this skepticism is to open up the model to scrutiny and to present information about the reliability of results, under the title of provenance and reliability. All this comes from the metadata about the statistical model. The approach is generic, but the presentation needs to be domain specific and tailored to the level of expertise and understanding of the user of the results. This paper presents the motivation behind this approach and outlines the metadata structures and functionality being built to deliver this support to users of results from the Opus methodology.]]></description>
      <pubDate>Thu, 25 May 2006 07:57:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/777207</guid>
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      <title>BENEFITS OF INFORMATION INTEGRATION IN BUDGET PLANNING FOR PAVEMENT MANAGEMENT</title>
      <link>https://trid.trb.org/View/746588</link>
      <description><![CDATA[The budget-allocation process in pavement management occurs at several levels of decision making.  In normal practice, the central level is concerned with the allocation of the budget to regional agencies to improve the health of the overall road network, while the regions are responsible for the programming and scheduling of road maintenance in their respective networks. The information processed at different management levels differs, and information at one level may not be readily available to the other.  As a result, the maintenance funds allocated by central management to regional highway agencies may not be best used.  A budget-allocation procedure based on artificial-intelligence agents is presented; it takes into account information integration between the central and regional management levels by using multiagent systems.  Agents are used to facilitate the interaction between decision makers at the two management levels and thus provide a means for vertical information integration.  A hypothetical problem containing a two-level funds-allocation structure consisting of a central-level management and three regional highway agencies is investigated.  Each regional agency has different road network profiles with different local-level objectives.  A genetic algorithm is used as the optimization tool in the decision-making process carried out by each agent.  The results are compared with conventional allocation approaches and a two-stage optimization approach.  It is shown that, with better integration of information at the different management levels, the resulting budget-allocation strategy produces greater maintenance-cost savings for a given target level of pavement performance.]]></description>
      <pubDate>Mon, 27 Dec 2004 00:00:00 GMT</pubDate>
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