Deep learning for intelligent traffic sensing and prediction: recent advances and future challenges
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SURVEY PAPER
Deep learning for intelligent traffic sensing and prediction: recent advances and future challenges Xiaochen Fan1 · Chaocan Xiang2 · Liangyi Gong3 · Xin He2 · Yuben Qu4 · Saeed Amirgholipour1 · Yue Xi5 · Priyadarsi Nanda1 · Xiangjian He1 Received: 12 May 2020 / Accepted: 19 August 2020 © China Computer Federation (CCF) 2020
Abstract With the emerging concepts of smart cities and intelligent transportation systems, accurate traffic sensing and prediction have become critically important to support urban management and traffic control. In recent years, the rapid uptake of the Internet of Vehicles and the rising pervasiveness of mobile services have produced unprecedented amounts of data to serve traffic sensing and prediction applications. However, it is significantly challenging to fulfill the computation demands by the big traffic data with ever-increasing complexity and diversity. Deep learning, with its powerful capabilities in representation learning and multi-level abstractions, has recently become the most effective approach in many intelligent sensing systems. In this paper, we present an up-to-date literature review on the most advanced research works in deep learning for intelligent traffic sensing and prediction. Keywords Traffic prediction · Deep learning · Pervasive computing · Intelligent transportation system · Literature review
1 Introduction The concept of smart cities (Gharaibeh et al. 2017; Silva et al. 2018) has become prevalent across different urban domains that apply information and communication technologies (ICT) to the physical world. By the term of ‘smart city’, it refers to a technology-intensive ecosystem that aims to deliver a wide range of ubiquitous services and
utility applications, such as intelligent transportation, home automation, smart grid, e-health, environment monitoring, and smart logistics (Chamoso et al. 2018; Nagy and Simon 2018). With the rapid population growth and the unprecedentedly growing number of vehicles, intelligent transportation management has become critical for the sustainability of smart cities. The emerging intelligent transportation system (ITS) (Moustaka et al. 2018) is envisioned to
* Chaocan Xiang [email protected]
Priyadarsi Nanda [email protected]
* Xiangjian He [email protected]
1
Xiaochen Fan [email protected]
School of Electrical and Data Engineering, University of Technology Sydney, Sydney, Australia
2
Liangyi Gong [email protected]
College of Computer Science, Chongqing University, Chongqing, China
3
Xin He [email protected]
School of Software and BNRist, Tsinghua University, Beijing, China
4
Yuben Qu [email protected]
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
5
School of Computer Science, Northwestern Polytechnical University, Xi’an, China
Saeed Amirgholipour [email protected] Yue Xi [email protected]
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revolutionize the existing transpor
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