Author ORCID Identifier

https://orcid.org/0000-0001-9530-7213

Document Type

Report

Publication Date

Winter 2024

Abstract

Toll facilities (roads, bridges, and tunnels) are intended for revenue generation to pay off the 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. The aim of this study is to provide the tolling industry with detailed analysis of the suitability of various non‐ pavement‐intrusive vehicle classification technologies (imaging using radar, Lidar, thermal profiling, etc.) under different roadway, traffic, and environmental conditions to inform decision‐makers of the accuracy, performance, and cost of these technologies. Tolling technologies for vehicle identification and classification are fragmented, lack interoperability, and continuously changing. Several vendors including Vitronic, Kapsch, SINELEC and SICK offer non-pavement intrusive automatic vehicle classification solutions for tolling and road pricing applications. These solutions share the common characteristic of using visual or infrared imaging and/or lidar for estimation of vehicle profile/shape. Some vendors provide solutions for axle counting without the use of induction loops. Based on the data gathered during this study, Vitronic, SICK, and SINELEC (in that order) appear to have non pavement-intrusive systems with high potential for reliably implementing shape/profile classification as well as axle counting. Toll authorities should consider moving away from vehicle classification based on axle counting to alternate schemes based on profile/shape since lidar technology is more mature and readily available.

Comments

Tran-SET Project 22ITSOSU64

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