The goal of the SHRP 2 Project L33 Validation of Urban Freeway Models was to assess and enhance the predictive travel time reliability models developed in the SHRP 2 Project L03, Analytic Procedures for Determining the Impacts of Reliability Mitigation Strategies. SHRP 2 Project L03, which concluded in 2010, developed two categories of reliability models to be used for the estimation or prediction of travel time reliability within planning, programming, and systems management contexts: data-rich and data-poor models. The objectives of Project L33 were the following: • The first was to validate the most important models – the “Data Poor” and “Data Rich” models with new datasets. • The second objective was to assess the validation outcomes to recommend potential enhancements. • The third was to explore enhancements and develop a final set of predictive equations. • The fourth was to validate the enhanced models. • The last was to develop a clear set of application guidelines for practitioner use of the project outputs. The datasets in these 5 zip files are in support of SHRP 2 Report S2-L33-RW-1, Validation of Urban Freeway Models, https://rosap.ntl.bts.gov/view/dot/3604 The 5 zip files contain a total of 60 comma separated value (.csv) files. The compressed zip files total 3.8 GB in size. The files have been uploaded as-is; no further documentation was supplied. These files can be unzipped using any zip compression/decompression software. The files can be read in any simple text editor. [software requirements] Note: Data files larger than 1GB each. Direct data download links: L03-01: https://doi.org/10.21949/1500858 L03-02: https://doi.org/10.21949/1500868 L03-03: https://doi.org/10.21949/1500869 L03-04: https://doi.org/10.21949/1500870 L03-05: https://doi.org/10.21949/1500871

The Highway Capacity Manual (HCM) historically has been among the most important reference guides used by transportation professionals seeking a systematic basis for evaluating the capacity, level of service, and performance measures for elements of the surface transportation system, particularly highways but also other modes. The objective of this project was to determine how data and information on the impacts of differing causes of nonrecurrent congestion (incidents, weather, work zones, special events, etc.) in the context of highway capacity can be incorporated into the performance measure estimation procedures contained in the HCM. The methodologies contained in the HCM for predicting delay, speed, queuing, and other performance measures for alternative highway designs are not currently sensitive to traffic management techniques and other operation/design measures for reducing nonrecurrent congestion. A further objective was to develop methodologies to predict travel time reliability on selected types of facilities and within corridors. This project developed new analytical procedures and prepared chapters about freeway facilities and urban streets for potential incorporation of travel-time reliability into the HCM. The methods are embodied in two computational engines, and a final report documents the research. This zip file contains comma separated value (.csv) files of data to support SHRP 2 report S2-L08-RW-1, Incorporating travel time reliability into the Highway Capacity Manual. Zip size is 1.83 MB. Files were accessed in Microsoft Excel 2016. Data will be preserved as is. To view publication see: https://rosap.ntl.bts.gov/view/dot/3606

The Washington site used the reliability guide from Project L02, analysis tools for forecasting reliability and estimating impacts from Project L07, Project L08, and Project C11 as well as the guide on reliability performance measures from the Project L05 product. The Washington site focused on the I-5 and I-405 corridors from Lynnwood to Tukwila (approximately 30 miles long for each corridor running through the Puget Sound metropolitan region), and the SR-522 urban arterial near Seattle. The pilot testing demonstrated that the SHRP 2 Reliability data and analytical products clearly addressed the practical challenges that transportation agencies face when monitoring and analyzing travel time reliability. However, most tools require significant improvements at the application level. Project L38D was intended to evaluate a suite of projects to determine their readiness for implementation. Those projects had a logical structure consisting of data collection, analysis, and project prioritization. The datasets in this zip file, which is 90.5 MB in size, are in support of SHRP 2 reliability project L38D, "Pilot testing of SHRP 2 reliability data and analytical products: Washington." The project report can be accessed via the following URL: https://rosap.ntl.bts.gov/view/dot/3610 This zip file contains 20 Comma Separated Values (CSV) files, which can be opened using most text editing programs.

The objective of this project was to develop technical relationships between reliability improvement strategies and reliability performance metrics. This project defined reliability, explained the importance of travel time distributions for measuring reliability, and recommended specific reliability performance measures. The research reexamined the contribution of the various causes of nonrecurring congestion on urban freeway sections, however, some attention was also given to rural highways and urban arterials). Numerous actions that can potentially reduce nonrecurring congestion were identified with an indication of their relative importance. Models for predicting nonrecurring congestion were developed using three methods, all based on empirical procedures: The first involved before and after studies; the second was termed a 'data poor' approach and resulted in a parsimonious and easy-to-apply set of models; the third was entitled a 'data rich model' and used cross-section inputs including data on selected factors known to directly affect nonrecurring congestion. An important conclusion of the study is that actions to improve operations, reduce demand, and increase capacity all can improve travel time reliability. The 3 attached zip files contains comma separated value (.csv) files of data to support SHRP 2 report S2-L03-RR-1, Analytical procedures for determining the impacts of reliability mitigation strategies.Zip size is 1.83 MB. Files were accessed in Microsoft Excel 2016. Data will be preserved as is. To view publication see: https://rosap.ntl.bts.gov/view/dot/3605

충청남도 아산시 교차시설(차량이 교차하는 장소의 위치) 현황에 대한 데이터로 위치정보, 교차시설 정보, 관리기관 등의 데이터를 제공합니다.

충청남도 아산시 교차시설(차량이 교차하는 장소의 위치) 현황에 대한 데이터로 위치정보, 교차시설 정보, 관리기관 등의 데이터를 제공합니다.

The Traffic Records Improvement Program Reporting System (TRIPRS) contains detailedinformation on all projects contained in the strategic plans submitted by the states and U.S.Territories for the NHTSA Section 408 grant application. Recently, it has been adopted byFMCSA, FHWA, and the US-DOT TRCC as a tool to track all safety data improvement fundsgiven to states. Reporting tool supported by NCSA. NATIONAL DRIVER REGISTER & TRAFFIC RECORDS (NVS-422).

특수교량의 안전 상태를 실시간으로 모니터링하고, 계측값의 기준치를 기준으로 이상신호를 감지하여 제공합니다. 이를 통해 교량의 안전성을 체계적으로 관리하고, 예방적 조치를 취할 수 있도록 지원합니다. 또한, RESTful API를 통해 효율적인 데이터 접근과 활용을 제공합니다. 서비스는 실시간으로 변동하는 계측값을 기준으로 상태를 모니터링하여 신속한 대응을 가능하게 하며, 교량의 유지보수 및 위험 관리에 중요한 역할을 합니다. 다양한 데이터 포맷(XML, JSON)을 지원하여 다양한 시스템과 호환이 가능하며, 안전한 데이터 교환을 위해 인증된 서비스 키를 사용합니다. 이 서비스는 고속도로, 철도 등 다양한 교량 환경에서 효율적으로 활용될 수 있으며, 교량 안전 관리 체계를 강화하는 데 기여합니다. 또한, 데이터 갱신 주기는 비정기로 설정되어 상황에 맞는 유연한 데이터 업데이트를 제공합니다.

The Travel Monitoring Analysis System (TMAS) - Stations dataset was compiled on December 31, 2023 and was published on July 22, 2024 from the Federal Highway Administration (FHWA), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Geospatial station data from the FHWA TMAS database contains latitude and longitude data from over 7,000 permanent (temporal data representing each time period) traffic monitoring sites in all 50 states plus DC. Data from these stations are submitted to FHWA every month and is a result of a long standing partnership between FHWA and the state DOTs.

국토교통과학기술진흥원에서 실행한 연구 관리 관련하여 교육, 상담, 설명회 등 프로그램 진행한 일정과 진행시간을 포함한 데이터를 제공하고 있습니다.