Relationship Between Urban Road Traffic Characteristics and Road Grade Based on a Time Series Clustering Model: A Case Study in Nanjing, China

  • Jiechen Wang
  • Jiayi Wu
  • Jianhua Ni
  • Jie Chen
  • Changbai Xi


With the increasing number of vehicles in large- and medium-sized cities challenges in urban traffic management, control, and road planning are being faced. Taxi GPS trajectory data is a novel data source that can be used to study the potential dynamic traffic characteristics of urban roads, and thus identify locations that show a notable lack of road planning. Considering that road traffic characteristics on their own are insufficient for a comprehensive understanding of urban traffic, we develop a road traffic characteristic time series clustering model to analyze the relationship between urban road traffic characteristics and road grade based on existing taxi trajectory data. We select the main urban area of Nanjing as our study area and use the taxi trajectory data of a single month for evaluating our method. The experiments show that the clustering model exhibit good performance and can be successfully used for road traffic characteristic classification. Moreover, we analyze the correlation between traffic characteristics and road grade to identify road segments with planning designs that do not match the actual traffic demands.


time series clustering temporal characteristics of road speed taxi trajectory data urban computation machine-learning 


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Copyright information

© Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jiechen Wang
    • 1
    • 2
    • 3
  • Jiayi Wu
    • 1
  • Jianhua Ni
    • 1
  • Jie Chen
    • 1
  • Changbai Xi
    • 1
  1. 1.Department of Geographic Information ScienceNanjing University]NanjingChina
  2. 2.Jiangsu Provincial Key Laboratory of Geographic Information Science and TechnologyNanjingChina
  3. 3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and ApplicationNanjingChina

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