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"No. 1917 explores the development of a more accurate, cost-effective methodology for estimating vehicle miles traveled; a reality-based approach to soliciting stated preference data; possible causes of loop errors under non-forced-flow traffic conditions; and wireless magnetic sensor networks as a low-cost alternative to inductive loops for traffic measurement."--pub website.
Traffic congestion is a major operational problem for freeways in Washington State. Recent studies have estimated that more than 50 percent of freeway congestion is caused by traffic incidents. To help the Washington State Department of Transportation (WSDOT) identify effective countermeasures against such congestion-inducing incidents, a thorough understanding of travel delays caused by incidents is essential. By using traffic data extracted from archived loop detector measurements and incident log data recorded by the WSDOT Incident Response (IR) team, this research project developed a new algorithm for quantifying travel delays produced by different incident categories. The algorithm applies a modified deterministic queuing theory to estimate incident-induced delay by using 1-minute aggregated loop detector data. Incident-induced delay refers to the difference between the total delay and the recurrent travel delay at the time and location influenced by the incident. The uniqueness of the delay calculation in this study is the use of a dynamic traffic-volume-based background profile, which is considered a more accurate representation of prevailing traffic conditions. According to the test results, the proposed algorithm can provide good estimates for incident-induced delay and capture the evolution of freeway traffic flow during incident duration. Because actual traffic data measured by loop detectors were used in this study to compute vehicle arrival and departure rates for delay calculations, the estimated incident-induced delay should be very close to the reality. Additionally, the proposed algorithm was implemented in the Advanced Roadway Incident Analyzer (ARIA) system. ARIA is a database-driven computer system that automates all the computational processes. More accurate incident delay information will help WSDOT improve its understanding of congestion-inducing incidents and select more effective countermeasures against incident-related traffic congestion on freeways.
Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. - Synthesizes the newest developments in data-driven transportation science - Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed - Useful for both theoretical and technically-oriented researchers
This current report presents research findings and recommendations for improving several mobility performance measure data collection sources and measurement estimation techniques. Major sections of the report address criteria to report statewide congestion, required enhancements to the existing CDOT travel data collection and analysis system, short-term improvements, and long-term improvements.
"For more than 50 years, the Transportation Research Record has been internationally recognized as one of the preeminent peer-reviewed journals for transportation research papers from authors in the United States and from around the world. One of the most cited transportation journals, the TRR offers unparalleled depth and breadth in the coverage of transportation topics from both academic and practitioner perspectives. All modes of passenger and freight transportation are addressed in papers covering a wide array of disciplines, including policy, planning, administration, economics and financing, operations, construction, design, maintenance, safety, and more."--Publisher's website