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Ning Wang, Buhao Zhang, Jian Gu, Huahua Kong, Song Hu and Shengchao Lu
The road traffic state is usually analyzed from a temporal and macroscopic perspective; however, traffic flow parameters, such as density and spacing, can explain the evolution of traffic states from the microscopic perspective and the spatial distributi...
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Mohammed Akallouch, Oussama Akallouch, Khalid Fardousse, Afaf Bouhoute and Ismail Berrada
Accurate and timely traffic information is a vital element in intelligent transportation systems and urban management, which is vitally important for road users and government agencies. However, existing traffic prediction approaches are primarily based ...
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Wachiranun Sirikul, Nida Buawangpong, Ratana Sapbamrer and Penprapa Siviroj
Background: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strategie...
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Sen Zhang, Shaobo Li, Xiang Li and Yong Yao
In order to improve the efficiency of transportation networks, it is critical to forecast traffic congestion. Large-scale traffic congestion data have become available and accessible, yet they need to be properly represented in order to avoid overfitting...
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Mouna Jiber, Abdelilah Mbarek, Ali Yahyaouy, My Abdelouahed Sabri and Jaouad Boumhidi
An efficient and credible approach to road traffic management and prediction is a crucial aspect in the Intelligent Transportation Systems (ITS). It can strongly influence the development of road structures and projects. It is also essential for route pl...
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Rafael Mena-Yedra, Ricard Gavaldà, Jordi Casas
Pág. 11 - 18
Traffic management is being more important than ever, especially in overcrowded big cities with over-pollution problems and with new unprecedented mobility changes. In this scenario, road-traffic prediction plays a key role within Intelligent Transportat...
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Chun Liu, Shuhang Zhang, Hangbin Wu and Qiang Fu
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Yuriy Lazarev, Catherine Medres, Juha Raty, Anatoliy Bondarenko
Pág. 393 - 400
The purpose of the article is the assessment and prediction of temperature conditions of roadway surfacing. The article states that the solution of this task makes it possible to reduce socio-economic losses caused by road traffic accidents. The solution...
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Paulo Infante, Gonçalo Jacinto, Daniel Santos, Pedro Nogueira, Anabela Afonso, Paulo Quaresma, Marcelo Silva, Vitor Nogueira, Leonor Rego, José Saias, Patrícia Góis and Paulo R. Manuel
Road Traffic Accidents (RTA) cause human losses and irreparable physical and psychological damage to many of the victims. They also involve a very relevant economic dimension. It is urgent to improve the management of human and material resources for mor...
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Martie van der Vlist, Luc Wismans, Paul van Beek, Leon Suijs
Pág. 3370 - 3379
Approximately 25 per cent of all congestion on motorways is caused by incidents. By virtual patrolling, incidents e.g. queues, accidents and car breakdowns on a road network, can be predicted or detected in an early stage. This early detection and predic...
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Zhengyan Cui, Junjun Zhang, Giseop Noh and Hyun Jun Park
Traffic prediction is a popular research topic in the field of Intelligent Transportation System (ITS), as it can allocate resources more reasonably, relieve traffic congestion, and improve road traffic efficiency. Graph neural networks are widely used i...
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E. Onieva, P. Lopez-Garcia, A.D. Masegosa, E. Osaba, A. Perallos
Pág. 4458 - 4467
Accurate estimation of the future state of the traffic is an attracting area for researchers in the field of Intelligent Transportation Systems (ITS). This kind of predictions can lead to traffic managers and drivers to act in consequence, reducing the e...
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Jae-Kang Lee, Yong Huh and Jisoo Park
As the development of mountain areas has recently increased in Korea, existing roads are being renovated, and new highways are being constructed, which increases driving speeds in mountainous areas. However, the mountainous region in northeastern Korea i...
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EunSu Lee, Debananda Chakraborty and Melanie McDonald
Drilling activity produces a significant amount of road traffic through unpaved and paved local roads. Because oil production is an important contributor to the local economy in the state of North Dakota, the state and local transportation agencies make ...
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Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
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Tim Martin, Lith Choummanivong
Pág. 2477 - 2486
Long-term pavement performance (LTPP) monitoring has been conducted in Australia for over 20 years. This research was funded by Austroads (representing federal, state and territory road agencies, local government and the New Zealand road agency) to promo...
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Pengyuan Wang, Xiao Huang, Joseph Mango, Di Zhang, Dong Xu and Xiang Li
Studying population prediction under micro-spatiotemporal granularity is of great significance for modern and refined urban traffic management and emergency response to disasters. Existing population studies are mostly based on census and statistical yea...
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Jinqiang Yao, Yu Qian, Zhanyu Feng, Jian Zhang, Hongbin Zhang, Tianyi Chen and Shaoyin Meng
With the development of vehicle-road network technologies, the future traffic flow will appear in the form of hybrid network traffic flow for a long time. Due to the change in traffic characteristics, the current hard shoulder running strategy based on t...
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Tebogo Bokaba, Wesley Doorsamy and Babu Sena Paul
Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent years, there has been a growing global interest in analysing RTAs, specifically concerned with analysing and modelling accident data to better understand and ...
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Yanjie Sun, Mingguang Wu, Xiaoyan Liu and Liangchen Zhou
High-precision dynamic traffic noise maps can describe the spatial and temporal distributions of noise and are necessary for actual noise prevention. Existing monitoring point-based methods suffer from limited spatial adaptability, and prediction model-b...
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