详情

Vehicle Classification Technologies for Toll Collection

项目名称：	Vehicle Classification Technologies for Toll Collection
摘要：	Toll facilities (roads, bridges and tunnels) are used primarily for revenue generation to repay for long-term debt issued to finance construction, capacity expansion, operations and maintenance of these facilities. Tolls are one form of a broad concept known as road pricing. In addition to revenue generation, road pricing is used for other reasons including transportation demand management to reduce peak hour travel and the recurring traffic congestion on some corridors. Tolling technologies have evolved rapidly in the past two decades and today offer many solutions for toll collection. Traditional (mostly cash) tolling has been gradually replaced by electronic toll collection (ETC) that enables users to go through toll lanes without stopping. In addition to improving traffic safety and enhancing the efficient use of the existing infrastructure, ETC results in reduction in toll collection costs. The three most important components of ETC are user account identification, vehicle classification (where vehicles are charged differently according to class), and determination of the distance traveled. Most of the tolling agencies in Region-6 (and most of the U.S.) determine the user fee based on the number of axles. The latter is often identified using induction loop sensors buried in the pavement and energized by low-voltage electrical currents that produce electromagnetic fields above the roadway. Vehicles traveling through these fields produce digital signatures that are used to identify the number of axles. The loop sensors used by many tolling authorities in the U.S. are manufactured by TransCore, Inc. and are known as “Intelligent Vehicle Identification System (IVIS). The IVIS sensors have high accuracy rate in classifying vehicles. However, loop detectors present several problems including the intrusive nature of their installation and maintenance (disruptive lane closures), high failure rate, sensitivity to rebar in concrete pavements, and their undermining of the structural health of the surrounding pavement. Loop failure can result because of several reasons including cracks across saw cuts, broken loop or lead-in wires, and sealant failure. The aim of this study is to provide tolling authorities in Region-6 with detailed analysis of the fitness of various non-pavement-intrusive vehicle classification technologies (imaging, radar, Lidar, thermal profiling, etc.) under different roadway, traffic, and environmental conditions to inform decision-makers of the accuracy, performance, and lifecycle-cost of these technologies. Toll facilities have multiple lane configurations including highways with multiple lanes at highway speeds and ramps at reduced speed. The classification technology must be accurate at high speed, low speed, single lane facilities, multiple lane facilities, and all kinds of weather. The study involves in-depth review of available non-pavement-intrusive vehicle classification technologies; gathering and analyzing data on the performance and cost of available technologies from manufacturers and toll facility operators; and making presentations to the tolling industry in Region-6.
状态：	Active
资金：	94000
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	Transportation Consortium of South-Central States (Tran-SET)
项目负责人：	Dhasmana, Heena
执行机构：	Oklahoma State University, Stillwater
主要研究人员：	Ahmed, Samir
开始时间：	20220401
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management；Vehicles and Equipment