详情

Guide for Long-Term Automatic Traffic Signal Performance Measurement Systems Applications

项目名称：	Guide for Long-Term Automatic Traffic Signal Performance Measurement Systems Applications
摘要：	In the United States, more than 300,000 traffic signals are currently in operation. To maintain the operation and performance of traffic signals, state departments of transportation (DOTs) have relied on manual counts entered into signal software (i.e., Synchro) and simulation models (i.e., Vissim) to develop traffic signal timings. These timing calculations are often retained unless an agency receives public complaints, although the performance may have degraded gradually over time as travel demand changes. Automated traffic signal performance measures (ATSPMs) could provide additional information to DOTs to help improve signal performance at intersections. ATSPMs started in the mid-2000s with the collection and analysis of high-resolution event-based data for traffic signal performance. Since then, conducted research has advanced the development of a schema method using event-based data for assessing and improving the performance of traffic signals, traffic signal systems, and traffic signal system business practices. ATSPM systems primarily present raw data in graphic representation to provide visual tools to assist signal operators in assessing signal performance on a regular basis, proactively identifying problems associated with signal timing, and to seek opportunities for improving traffic signal operation to improve traffic flow and system efficiency. However, ATSPMs user experiences have identified limitations of the current high-resolution data schema on which the ATSPMs are established including: (1) The unavailability of a universal schema or easy conversion from one data format to another for different types of systems, causing state DOTs and public agencies to duplicate their effort in creating and managing data and information. In addition, due to limited standardized guidelines about managing high-resolution signal data and associated metadata information, state DOTs and other public agencies may handle complex traffic signal system cases slightly different, which can lead to inconsistent methodologies between agencies. (2) Connected automated vehicles (CAV) and sensor technology, a new data source of short-term trajectory information as vehicles and pedestrians approach an intersection, are currently not included in the data schema for ATSPMs. (3) The unavailability of a well-documented standard available for recording geo-spatial metadata. Research is needed to define effective practices for state DOTs and public agencies for managing ATSPM data long-term and ensure these practices are scalable, transferable, and enable CAV integration. The objective of this research is develop a guide to assist state DOTs and public agencies with long-term management of ATSPM systems applications for scalability, transferability, and CAV integration.
状态：	Proposed
资金：	500000
资助组织：	National Cooperative Highway Research Program；Federal Highway Administration；American Association of State Highway and Transportation Officials (AASHTO)
项目负责人：	McKenney, Christopher T
开始时间：	20220808
主题领域：	Administration and Management；Data and Information Technology；Highways；Operations and Traffic Management；Vehicles and Equipment