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"Abstract: The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a "bundle" of dynamic mobility applications (DMA) that leverage existing and new connected vehicle data sets to optimize traffic signal timing for safety, emergency response, and improved mobility. The analysis is based on the policy team's review of a wide range of materials that include: - The MMITSS program's Concept of Operations (ConOps), Stakeholder Input Report, and System Design and Requirements documents. - The Connected Vehicle Reference Implementation Architecture (CVRIA) diagrams for MMITSS. - Discussions with the technical team overseeing development of the prototype applications within the MMITSS bundle and a review of the prototype documents. - Industry best practices and standards in information technology, security and privacy, and data exchange. As policy or institutional issues emerged during the review, they were categorized into one of four categories (not every DMA bundle had issues in all four categories) and were further paired with recommended actions for resolution, if options were available. Where they were not available, additional research is recommended. The four issue categories are: 1. High priority issues need immediate attention and resolution as they may challenge deployment, adoption, and use. 2. Medium priority issues have potentially serious consequences but clear, if challenging, paths to resolution; which should be accomplished prior to technology transfer. 3. Low priority issues have policy implications but also have solutions underway or represent current best practices that can be implemented before MMITSS applications are introduced to the marketplace. 4. Emerging issues have some probability of challenging deployment over time, as MMITSS implementations grow in complexity or geographic coverage. In summary: - One high-priority issue common to other DMA applications was identified and documented. The one issue is concerns of privacy of Personally Identifable Information (PII). Future MITSS deployments will need to ensure careful attention to PII concerns. - Four medium-priority issues were identified and documented. One issue is common to the other DMA applications. The four issues are: certification of Connected Vehicle (CV) technologies; data governance with regard to collecitng, archiving, and accessing CV data; safety of pedestrians and disabled users; and allocating signal priority among multiple agencies and private entities. All of these issues are challenging but have potential technical and policy options that can be applied to resolve them. Further research is recommended to analyze the options for their impacts and to determine the optimal recommendations. - Nine low priority issues were identified and have been documented in this report. They include: governance (legitimacy) of "handicapped" nomadic devices; ensuring functionality throughout the product lifecycle; digital certification for data exchange with nomadic devices; credentialing for technicians; interoperability of New MMITSS components with existing systems; availability to DSRC for real-time data exchange; regional integration and optimization of signal priorities; coordination and participation; concerns of existing signal priority patent owners. - Bicycle safety with MMITSS enabled signal systems may emerge as more important as MMITSS implementations expand to involve multiple agencies or jurisdictions which must work together effectively. Based on the results of this analysis, the policy team does not foresee a need for any new policies to be enacted or any major issues that will stand in the way of successful market adoption and use by industry. All policy and institutional issues identified can be resolved satisfactorily, some with recommended additional research into the following topics: - Existing guidance for collecting and storing Personal Identification Information (PII); identify whether existing policies adequately address MMITSS needs - Legal analysis of liability for pedestrian safety, in the event of an app failure - Case studies of bicycles and alternative technology - Literature review of current coordinated signal timing practices - Inventory Geographic Intersection Data management practices and identify any needed institutional changes - Best practices in inter-jurisdictional agreements for traffic management - Alignment with existing FHWA guidance on bicycles, coordinated signal timing."--Technical report documentation page.
"Abstract: This report documents policy considerations for Enabling Advanced Traveler Information Services, or EnableATIS. EnableATIS is the traveler information element of the Dynamic Mobility Applications program, and it provides a framework to develop multi-source, multimodal data into new advanced traveler information applications and strategies. The policy team has documented four policy issues for EnableATIS, none of them high-priority. In conclusion, the policy team finds that additional policy research, outreach, and other steps may be needed, including investigation of public-private partnerships to broaden the reach and improve the effectiveness of ATIS implementation. In summary, the four issues and recommended next steps include: ? Inequitable distribution of ATIS and other connected vehicle functionality may need to be evaluated for the level of potential impact on underserved populations. ? Driver distraction?an issue shared by many connected vehicle applications?is among the central concerns of connected vehicle policy research. Analysis is currently under way by USDOT and industry experts. ? Data integration may result from market forces or from standards development organizations becoming involved in the ATIS application market. The USDOT may choose to provide support if the private sector is motivated to work with public agencies. ? Similarly, tools for providing ATIS data to transportation management centers may evolve if private-sector stakeholders are motivated to work with USDOT towards greater system-wide efficiency and effectiveness. Based on the results of this analysis, the policy team does not foresee a need for any new policies to be enacted or any major issues that will stand in the way of successful private sector ATIS development. "--Technical report documentation page.
Both the Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs have similar overarching goals to improve surface transportation system efficiency and individual traveler mobility. However, eachprogram has a unique research approach seeking to meet these goals. The DMA Program focuses on exploiting new forms of data from wirelessly connected vehicles, travelers, and the infrastructure to enable transformative mobility applications. The ATDM Program focuses its research efforts on accelerating the pace of dynamic control within transportation systems management through operational practices that incorporate predictive and active responses to changing operational conditions. In order to explore potential transformations in transportation systems performance, both programs require an Analysis Modeling and Simulation (AMS) capability. AMS tools and methodologies offer a cost-effective approach to addressing complex questions on optimization of longer-range investments, shorter-term operational practices, and overall system performance. Both programs have invested significant resources in the development of advanced concepts and foundational research, but the potential impacts from deployment are uncertain and poorly quantified. The two programs must identify the technologies, applications, and operational approaches that work cost-effectively in concert with each other in order to justify large-scale demonstrations and pilot deployments.A capable, reliable AMS Testbed provides a valuable mechanism to address this shared need by providing a laboratory for the refinement and integration of research concepts in a virtual computer-based AMS environment prior to field deployment. An AMS Testbed as envisioned here refers to a set of computer models that can replicate the effects of public agencies and private sector in a region implementing concepts, bundles, and strategies associated with the DMA and ATDM Programs. The purpose of this document is to provide a high-level framework for AMS Testbeds that recognizes both technical risk and the primary evaluation needs of the DMA and ATDM Programs. Four technical approaches that are consistent with the AMS framework are also presented.
Analysis Modeling and Simulation (AMS) Testbeds can make significant contributions in identifying the benefits of more effective, more active systems management resulting from integrating transformative applications enabled by new data from wirelessly connected vehicles, travelers, and infrastructure. To this end, the Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs have jointly sponsored the planning of multiple AMS Testbeds to support the two programs in evaluating and demonstrating the system-wide impacts of deploying application bundles and strategies in an AMS environment. The purpose of this report is to document a preliminary plan for evaluating impacts of individual DMA applications, individual DMA bundles, and logical combinations of bundles and applications and identifying conflicts and synergies for maximum benefit.
"Abstract: This report documents policy considerations for Response, Emergency Staging and Communications, Uniform Management, and Evacuation (R.E.S.C.U.M.E.). R.E.S.C.U.M.E. comprises a "bundle" of mobility applications that use existing and new connected vehicle data sets and other data to provide first-responders, emergency management centers, and read crews with enhanced information, allowing them to respond faster and more effectively to incidents and emergencies than they can today. The policy team has documented four potential policy issues for R.E.S.C.U.M.E.: 1. Multi-Agency Coordination for Information Broker Function: Because the Information Broker functions in R.E.S.C.U.M.E. will, in many cases, be distributed among multiple entities it will be important for participating agencies to determine roles and responsibilities when implementing R.E.S.C.U.M.E. 1. Compliance with HIPAA Privacy Requirements: R.E.S.C.U.M.E. applications - in particular, EVAC - may handle personal health information (PHI), and must be certain to be consistent with the privacy requirements of the Health Insurance Portability and Accountability Act of 1996 (HIPAA). 3. Data and Message Standards for Emergency Communication: The RESP-STG application must be able to integrate data from multiple sources and immediately disseminate appropriate messages and warning to multiple agencies. The EVAC application will need to integrate medical records and other data from a variety of sources. Consequently, the need for data and messaging standards to facilitate inter-agency and inter-jurisdictional emergency information sharing is apparent. 4. INC-ZONE Implementation: The INC-ZONE application will require small but important changes to the procedures that response crews follow when they arrive at incident scenes, and also may have implications for incident/work zone signage design standards. Recommendations for addressing these policy issues include development of guidance materials for state and local agencies, and completion of planned cost-benefit studies and privacy impact assessments."--Technical report documentation page.
Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility 'structural' analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data's impact on mobility and an introduction to the tools necessary to apply new techniques. The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.
"Abstract: This document details the impact assessment conducted by the Volpe Center for the integrated Dynamic Transit Operations (IDTO) prototype demonstrations in Columbus, Ohio and Central Florida. The prototype is one result of the U.S. Department of Transportation's Dynamic Mobility applications (DMA) program which seeks to enhance and transform future surface transportation systems management. The set of IDTO impacts were evaluated based upon a series of hypothesis tests governing travel behavior and strategies enacted by participating organizations. These tests related to usage of the IDTO technological bundle, changes in travel demand, changes in travel time, changes in operational costs, and changes in interorganizational cooperation. Each of the hypotheses was tested based upon information provided by the prototype developer and participating organizations as well as analysis conducted by the IA team."--Technical report documentation page.
This book deals with the estimation of travel time in a very comprehensive and exhaustive way. Travel time information is and will continue to be one key indicator of the quality of service of a road network and a highly valued knowledge for drivers. Moreover, travel times are key inputs for comprehensive traffic management systems. All the above-mentioned aspects are covered in this book. The first chapters expound on the different types of travel time information that traffic management centers work with, their estimation, their utility and their dissemination. They also remark those aspects in which this information should be improved, especially considering future cooperative driving environments.Next, the book introduces and validates two new methodologies designed to improve current travel time information systems, which additionally have a high degree of applicability: since they use data from widely disseminated sources, they could be immediately implemented by many administrations without the need for large investments. Finally, travel times are addressed in the context of dynamic traffic management systems. The evolution of these systems in parallel with technological and communication advancements is thoroughly discussed. Special attention is paid to data analytics and models, including data-driven approaches, aimed at understanding and predicting travel patterns in urban scenarios. Additionally, the role of dynamic origin-to-destination matrices in these schemes is analyzed in detail.