Vehicle Trajectory Similarity: Models, Methods, and Applications

Autor(es)

De Sousa, Roniel S. ^{[1, 2]} ; Boukerche, Azzedine ^[2] ; Loureiro, Antonio A. F. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Minas Gerais, Dept Comp Sci, BR-31270901 Belo Horizonte, MG - Brazil

^[2] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5 - Canada

• Tipo de documento: Artigo Científico
• Fonte: ACM COMPUTING SURVEYS; v. 53, n. 5 OCT 2020.
• Citações Web of Science: 0

Resumo

The increasing availability of vehicular trajectory data is at the core of smart mobility solutions. Such data offer us unprecedented information for the development of trajectory data mining-based applications. An essential task of trajectory analysis is the employment of efficient and accurate methods to compare trajectories. This work presents a systematic survey of vehicular trajectory similarity measures and provides a panorama of the research field. First, we show an overview of vehicle trajectory data, including the models and some preprocessing techniques. Then, we give a comprehensive review of methods to compare trajectories and their intrinsic properties. We classify the methods according to the trajectory representation and features such as metricity, computational complexity, and robustness to noise and local time shift. Last, we discuss the applications of vehicular trajectory similarity measures and some open research problems. (AU)

• Processo FAPESP: 18/23064-8 - Mobilidade na computação urbana: caracterização, modelagem e aplicações (MOBILIS)
• Beneficiário: Antonio Alfredo Ferreira Loureiro
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 15/24494-8 - Comunicação e processamento de big data em nuvens e névoas computacionais
• Beneficiário: Nelson Luis Saldanha da Fonseca
• Modalidade de apoio: Auxílio à Pesquisa - Temático