Positioning method of expressway ETC gantry by multi‐source traffic data

Abstract

With the rapid development of expressway Electronic Toll Collection (ETC) technology in China, the expressway management system is becoming digital and intelligent, which provides a solid foundation for expressway vehicle infrastructure cooperation and autonomous driving. The gantry position is the key part of the ETC system. However, there are still some problems (e.g. gantry position missing or false), which can seriously affect the intelligent development of expressways. To address these two issues, an ETC gantry positioning method is proposed. First, the ETC transaction data and the GPS data on expressways are preprocessed to remove abnormal data and retrieve missed data. Then, combined with Dead Reckoning (DR) and Median Center, the potential position of the gantry is calculated from ETC transaction data and GPS data. Finally, the switching strategy based on Kalman Filter (KF) is used to capture the final gantry position. By comparing the results of the proposal with the collected gantry position, it is found that the positioning error of the gantry position calculated by this proposal is about 37 m. The positioning accuracy is 98.78% with the threshold of 100 m. The experimental results show that the proposal can effectively locate the expressway gantry.

Guest Editorial: Modelling, operation and management of traffic mixed with connected and automated vehicles

“…Based on electronic toll collection (ETC) transaction data and global positioning system (GPS) data, Guo et al. [8] propose an ETC gantry positioning method. Combined with dead reckoning (DR) and median centre, the potential position of the gantry is calculated from ETC transaction data and GPS data.…”

Dynamic Identification Method for Potential Threat Vehicles beyond Line of Sight in Expressway Scenarios

“…When the vehicle and the ETC gantry generate a transaction record, the transaction time of the vehicle can be obtained; then, the approximate travelling time of the vehicle in this section and the average speed of the vehicle can be calculated, so as to calculate the distance ∆S between the over-the-horizon vehicle and the PTV, and the specific location of the vehicle can be further estimated. The calculation is shown in Formula (13).…”

“…The number of ETC users has risen to over 260 million, providing strong data support for expressway over-the-horizon safety detection. At present, many scholars have developed research on intelligent driving based on ETC data, including dynamic speed limit recognition on expressways [9], traffic flow prediction on expressways [10,11], and vehicle speed prediction [12], among other related research [13]. Through the exchange of information between vehicles, roads, and the cloud [14], the ETC gantry of highways is used to collect vehicle traffic information, and the intervention of cloud platforms can process and analyze large-scale vehicle data and road condition information, thereby detecting potential threat factors outside the driver's line-of-sight range and transmitting this warning information to corresponding vehicles subscribing to beyond-line-of-sight services.…”

CSFPre: Expressway key sections based on CEEMDAN-STSGCN-FCM during the holidays for traffic flow prediction

“…ETC gantry data and toll data can record the driving conditions of each vehicle on the expressway. Therefore, using ETC gantry data and toll data, we can accurately estimate the location of ETC gantries [6], prediction of traffic flow [7], travel time [8], travel speed [9], and service area vehicle recognition and dwell time estimation [10]. Since the expressway traffic management department cannot fully grasp the changing trend of road status during holidays, travelers cannot timely understand the changes in road conditions, resulting in too concentrated vehicle travel and difficulty in effective traffic control and diversion, causing traffic congestion [11].…”