A novel algorithm to identifying vehicle travel path in elevated road area based on GPS trajectory data

• Published in: Frontiers of earth science Vol. 6; no. 4; pp. 354 - 363
• Main Authors: Xu, Xianrui, Li, Xiaojie, Hu, Yujie, Peng, Zhongren
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer-Verlag 2012; Higher Education Press; SP Higher Education Press; Springer Nature B.V
• Subjects: Algorithms; cities; Data collection; Earth and Environmental Science; Earth Sciences; elevated road; Global positioning systems; GPS; GPS trajectory; GPS数据处理; information dissemination; Information processing; Position tracking; Research Article; road network modeling; Roads; Roads & highways; topology; traffic; trajectory segmentation; vehicle status identification; Vehicles; 信息传播系统; 信息采集技术; 基础; 移动路径; 算法; 车辆行驶; 高架路; China; Shanghai China; GPS trajectory; vehicle status identification; trajectory segmentation; road network modeling; elevated road
• DOI: 10.1007/s11707-012-0340-0
• ISSN: 2095-0195

In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.