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However, the existing car-following models set the drivers\u2019 reaction time to a fixed value without considering its dynamics. In order to improve the accuracy of car-following model, this paper proposes Deep Feature Learning-based Car-Following Model (DeepCF), a car-following model based on fatigue driving and Generative Adversarial Networks (GAN). The model is composed of the drivers\u2019 reaction time model and the car-following decision algorithm. First, we regard driving fatigue as the starting point to study the influence of driving time and the acceleration of the preceding vehicle on the drivers\u2019 reaction time, and develop a coarse-grained drivers\u2019 reaction time model. Secondly, considering the impact of fatigue driving on car-following decisions, we utilize GAN to generate a driving decision database based on reaction time and use Euclidean distance as a decision search indicator. Finally, we conduct experiments on a real data set, and the results indicate that our DeepCF model is superior to baseline models.<\/jats:p>","DOI":"10.1155\/2020\/8816681","type":"journal-article","created":{"date-parts":[[2020,12,8]],"date-time":"2020-12-08T19:32:48Z","timestamp":1607455968000},"page":"1-9","source":"Crossref","is-referenced-by-count":8,"title":["DeepCF: A Deep Feature Learning-Based Car-Following Model Using Online Ride-Hailing Trajectory Data"],"prefix":"10.1155","volume":"2020","author":[{"given":"Yizhen","family":"Xie","sequence":"first","affiliation":[{"name":"International School, Beijing University of Posts and Telecommunications, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qichao","family":"Ni","sequence":"additional","affiliation":[{"name":"School of Software, Dalian University of Technology, Dalian 116620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6111-8617","authenticated-orcid":true,"given":"Osama","family":"Alfarraj","sequence":"additional","affiliation":[{"name":"Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Software, Dalian University of Technology, Dalian 116620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojiang","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2698-3319","authenticated-orcid":true,"given":"Xiangjie","family":"Kong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amr","family":"Tolba","sequence":"additional","affiliation":[{"name":"Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia"},{"name":"Mathematics and Computer Science Department, Faculty of Science, Menoufia University, Shebin-El-Kom 32511, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2701846"},{"key":"2","first-page":"1","article-title":"A collision-free car-following model for connected automated vehicles","volume-title":"Transportation Research Board 96th Annual Meeting","author":"L. 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