ETC-Enabled Intelligent Expressway: From Toll Collection to Vehicle–Road–Cloud Integration

Following China’s completion of the removal of provincial boundary toll stations and expressway network integration reform, a large number of electronic toll collection (ETC) gantries were deployed along expressway mainlines nationwide, transforming these facilities from dedicated toll terminals into pervasive traffic-sensing infrastructure covering the entire road network. However, the data value and technological potential embedded in this major infrastructure transformation have not yet been systematically reviewed. This paper adopts a narrative review methodology, incorporating 71 publications identified through multi-database systematic searches. The review is organized along the functional upgrade path of ETC gantries, covering the progression from toll terminals to traffic sensing nodes, multi-source fusion hubs, and finally vehicle–road–cloud cooperative control nodes, and synthesizes research progress in expressway traffic sensing, multi-source data fusion, safety operations, and emerging applications. The review reveals that ETC data have enabled a diverse methodological repertoire spanning travel time estimation, traffic flow prediction, origin–destination (OD) matrix inference, toll plaza safety analysis, dynamic pricing strategies, and environmental impact assessment. Nevertheless, a single ETC data source suffers from inherent limitations: spatial–temporal resolution constrained by gantry spacing and real-time capability limited by transmission latency. This fundamental contradiction constitutes the core driving force behind multi-source data fusion and vehicle–road–cloud integration technologies. The paper further argues that establishing a closed-loop pipeline integrating sensing, fusion, decision, and control and anchored on ETC gantry nodes represents the key direction for realizing intelligent expressway transformation.

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Publication Details

Journal
Applied Sciences
Published
2026-04-14
DOI
https://doi.org/10.3390/app16083815
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

ETC-Enabled Intelligent Expressway: From Toll Collection to Vehicle–Road–Cloud Integration

Ruifa Luo, Yue Qian, Song Hu, Xiaoguang Yang
Applied Sciences
Traffic Prediction and Management Techniques
article

ETC-Enabled Intelligent Expressway: From Toll Collection to Vehicle–Road–Cloud Integration

Ruifa Luo, Yue Qian, Song Hu, Xiaoguang Yang
article en

Abstract

Following China’s completion of the removal of provincial boundary toll stations and expressway network integration reform, a large number of electronic toll collection (ETC) gantries were deployed along expressway mainlines nationwide, transforming these facilities from dedicated toll terminals into pervasive traffic-sensing infrastructure covering the entire road network. However, the data value and technological potential embedded in this major infrastructure transformation have not yet been systematically reviewed. This paper adopts a narrative review methodology, incorporating 71 publications identified through multi-database systematic searches. The review is organized along the functional upgrade path of ETC gantries, covering the progression from toll terminals to traffic sensing nodes, multi-source fusion hubs, and finally vehicle–road–cloud cooperative control nodes, and synthesizes research progress in expressway traffic sensing, multi-source data fusion, safety operations, and emerging applications. The review reveals that ETC data have enabled a diverse methodological repertoire spanning travel time estimation, traffic flow prediction, origin–destination (OD) matrix inference, toll plaza safety analysis, dynamic pricing strategies, and environmental impact assessment. Nevertheless, a single ETC data source suffers from inherent limitations: spatial–temporal resolution constrained by gantry spacing and real-time capability limited by transmission latency. This fundamental contradiction constitutes the core driving force behind multi-source data fusion and vehicle–road–cloud integration technologies. The paper further argues that establishing a closed-loop pipeline integrating sensing, fusion, decision, and control and anchored on ETC gantry nodes represents the key direction for realizing intelligent expressway transformation.

Applied SciencesVol. 16(8)
Tongji University (CN), Beijing Transportation Research Center (CN)
Tongji University
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Traffic Prediction and Management Techniques
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