{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T05:53:22Z","timestamp":1726206802916},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T00:00:00Z","timestamp":1556755200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61503048","61602171"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of\u00a0Hunan Province","doi-asserted-by":"publisher","award":["2016JJ2006"],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"With the development of intelligent transportation system (ITS) and vehicle to X (V2X), the connected vehicle is capable of sensing a great deal of useful traffic information, such as queue length at intersections. Aiming to solve the problem of existing models\u2019 complexity and information redundancy, this paper proposes a queue length sensing model based on V2X technology, which consists of two sub-models based on shockwave sensing and back propagation (BP) neural network sensing. First, the model obtains state information of the connected vehicles and analyzes the formation process of the queue, and then it calculates the velocity of the shockwave to predict the queue length of the subsequent unconnected vehicles. Then, the neural network is trained with historical connected vehicle data, and a sub-model based on the BP neural network is established to predict the real-time queue length. Finally, the final queue length at the intersection is determined by combining the sub-models by variable weight. Simulation results show that the sensing accuracy of the combined model is proportional to the penetration rate of connected vehicles, and sensing of queue length can be achieved even in low penetration rate environments. In mixed traffic environments of connected vehicles and unconnected vehicles, the queuing length sensing model proposed in this paper has higher performance than the probability distribution (PD) model when the penetration rate is low, and it has an almost equivalent performance with higher penetration rate while the penetration rate is not needed. The proposed sensing model is more applicable for mixed traffic scenarios with much looser conditions.<\/jats:p>","DOI":"10.3390\/s19092059","type":"journal-article","created":{"date-parts":[[2019,5,7]],"date-time":"2019-05-07T07:15:46Z","timestamp":1557213346000},"page":"2059","source":"Crossref","is-referenced-by-count":91,"title":["Connected Vehicle as a Mobile Sensor for Real Time Queue Length at Signalized Intersections"],"prefix":"10.3390","volume":"19","author":[{"given":"Kai","family":"Gao","sequence":"first","affiliation":[{"name":"College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410114, China"},{"name":"Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha 410114, China"}]},{"given":"Farong","family":"Han","sequence":"additional","affiliation":[{"name":"College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410114, China"}]},{"given":"Pingping","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-0394-4635","authenticated-orcid":false,"given":"Naixue","family":"Xiong","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin 300350, China"}]},{"given":"Ronghua","family":"Du","sequence":"additional","affiliation":[{"name":"College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410114, China"},{"name":"Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha 410114, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1610","DOI":"10.1016\/j.trpro.2017.05.207","article-title":"Real-time traffic signal control for isolated intersection, using car-following logic under connected vehicle environment","volume":"25","author":"Chandan","year":"2017","journal-title":"Transp. 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