Distribution Analysis and Forecast of Traffic Flow of an Expressway Electronic Toll Collection Lane

He, Mengchang; Gao, Lun; Shuai, Chunyan; Lee, Jae Young; Luo, Jie

doi:10.1061/jtepbs.0000552

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…In terms of traffic flow prediction, He et al [2] analyzed the distribution law of traffic flow through ETC toll data and used the Gaussian mixture regression (GMR) model to predict short-term traffic flow in ETC lanes. Shuai et al [3] proposed a mixed two-layered model for predicting highway traffic flow and assessed its effectiveness by using data from 51 toll stations.…”

Section: Literature Reviewmentioning

confidence: 99%

Travel Characteristics Identification Method for Expressway Passenger Cars Based on Electronic Toll Collection Data

Cai

Zhang

Zhang³

et al. 2023

Sustainability

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Passenger cars have emerged as a substantial segment of the vehicles traversing expressways, generating extensive traffic data on a daily basis. Accurately identifying individual vehicles and their travel patterns and characteristics is crucial in addressing the issues that impede the sustainable development of expressways, including traffic accidents, congestion, environmental pollution, and losses of both personnel and property. Regrettably, the utilization of electronic toll collection (ETC) data on expressways is currently not adequate, and data analysis and feature mining methods are underdeveloped, leading to the undervaluation of data potential. Focusing on ETC data from expressways, this study deeply analyzes the spatiotemporal characteristics of travel by passenger car users. Here, we propose an advanced user classification model by combining the traditional clustering algorithm with the feature grouping recognition model based on a back propagation neural network (BPNN) algorithm. Real-world data on expressway vehicle travel are used to validate our models. The results show a significant improvement in iteration efficiency of over 26.4% and a 23.17% accuracy improvement compared to traditional algorithms. The travel feature grouping recognition model yielded an accuracy of 95.23%. Furthermore, among the identified groups, such as “Public and commercial affairs” and “Commuting”, there is a notable characteristic of high travel frequency and concentrated travel periods. This indicates that these groups have placed significant pressure on the construction of a safe, efficient, and sustainable urban transportation system.

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Section: Literature Reviewmentioning

confidence: 99%

Travel Characteristics Identification Method for Expressway Passenger Cars Based on Electronic Toll Collection Data

Cai

Zhang

Zhang³

et al. 2023

Sustainability

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“…Second, the Euclidean distance d(x, c i ) from each sample to each center is calculated, as shown in formula (6).…”

Section: K-means Clustering Analysismentioning

confidence: 99%

“…e application of ETC is beneficial in promoting traffic management in toll plazas and saves fuel for vehicles [5]. Compared with the manual toll collection system, the ETC system has the advantages of speed and convenience [6]. Applying for ETC can indeed bring convenience to drivers and make high-speed traffic smoother, greener, and more environmentally friendly than before.…”

Section: Introductionmentioning

confidence: 99%

Which Factors Affect User Satisfaction with ETC? Evidence from Shanghai and Beijing

Xiao

et al. 2022

Journal of Advanced Transportation

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Owing to the current development trend of globalization and informatization, traditional transportation technologies and means can no longer meet the needs of economic and social development. Thus, intelligent transportation will be an inevitable and revolutionary choice for the development of the transportation industry. As a subsystem of the intelligent transportation system, the electronic nonstop toll collection (ETC) system provides a good solution to the problems of traffic congestion, environmental pollution, energy consumption, and low toll operation efficiency caused by expressway toll collection. This high-technology system is utilized in many fields, such as radio communication and computer and automatic control in the transportation field. China’s expressway ETC systems have evident effects on congestion reduction at toll stations. Although the advantages of ETC lanes are significant, and China actively implements ETC-handling policies, some drivers are reluctant to install ETC on-board systems or they have negative experiences after handling them. According to a survey, existing literature lacks research on the factors affecting user satisfaction with ETC. On the basis of the questionnaire data of ETC user experience in Shanghai and Beijing, we comprehensively investigate the reasons of banking, ETC equipment, and drivers’ personal factors and travel characteristics to establish an ordinal logistics model. Through cluster analysis, drivers in the two cities are divided into three groups, and the significance of related variables is further analyzed. This research can help us understand the degree of influence of different factors on user satisfaction with ETC to a certain extent. Moreover, effective methods and measures can be used to promote the popularity of ETC vehicle equipment and the utilization rate of ETC-dedicated lanes.

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“…The traditional method of expressway toll collection in China is not flexible, accurate, or intelligent [2]; cash payers must queue up to obtain a card as well as to pay the fees, and the procedures are cumbersome, easily cause congestion, and fees can be easily avoided. In electronic toll collection (ETC), queueing for cards and fees is not needed, but on-boardunit (OBU) installation is cumbersome, installation fees are required, and penetration rates are low.…”

Section: Introductionmentioning

confidence: 99%

Sofware-Defined Space-Ground-Vehicle Integrated Network Architecture for Unconscious Payment

2022

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The continuous development trend of expressways urgently needs expressway sensing, which is required to be able to perceive unknown risk factors to ensure a safe and stable transportation environment as well as effectively and continuously monitor the safe operation of expressways. Using unconscious payment can greatly improve traffic efficiency and meet the development direction of intelligent transportation. However, charging errors occur when using unconscious payment, primarily because the expressway network fails to realize national networking. Most of the literature focuses on two aspects of sensing, transmission and computing, while research on the overall network architecture is lacking. A ground network cannot solve the network coverage problem in remote areas. Therefore, the basic infrastructure needed to realize expressway sensing includes both aerial and ground nodes, such as cars, roadside equipment, unmanned aerial vehicles, airships, and satellites. This network communication architecture requires effective management of infrastructure and support of various applications. The software-defined network has strong flexibility; thus, in this paper, we propose a software-defined spaceground-vehicle integrated network (SD-SGVIN) architecture that includes three layers: physical facility, logic control, and application. The SD-SGVIN can separate the highway sensing applications from the physical entity. All kinds of applications can acquire, transmit, and process vehicle data through a shared physical infrastructure. We discuss the design, implementation, and advantages of the proposed network structure, hoping to provide a new direction for the research and promotion of expressway sensing and unconscious payment.

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Distribution Analysis and Forecast of Traffic Flow of an Expressway Electronic Toll Collection Lane

Cited by 3 publications

References 20 publications

Travel Characteristics Identification Method for Expressway Passenger Cars Based on Electronic Toll Collection Data

Travel Characteristics Identification Method for Expressway Passenger Cars Based on Electronic Toll Collection Data

Which Factors Affect User Satisfaction with ETC? Evidence from Shanghai and Beijing

Sofware-Defined Space-Ground-Vehicle Integrated Network Architecture for Unconscious Payment

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