Abstract
Daily mobility patterns in highly populated urban environments rely on a well-functioning effective road network. Nevertheless, traffic bottlenecks are typical for urban environments with periodic traffic congestion . In this paper, we focus on the investigation of how traffic congestion is related with complicated crossings . First, we select an approach for the classification of the complexity of road partitions and the derivation of complicated crossings based on geodata from OpenStreetMap (OSM). Second, we calculate traffic congestions using Floating Taxi Data (FTD) from Shanghai in 2007. Then, we develop a matching technique to link the congestion and complicated crossings, and subsequently define the concept of traffic bottlenecks represented by polygons. The bottlenecks indicate locations where the transportation infrastructure is complex and traffic congestion appears periodically. Finally, we select suitable cartographic representations of traffic bottlenecks in potential thematic vehicle traffic maps .
Keywords
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Acknowledgements
The described taxi Floating Car Data set of Shanghai (‘SUVnet-Trace Data,’ http://wirelesslab.sjtu.edu.cn/taxi_trace_data.html) was obtained from the Wireless and Sensor networks Lab (WnSN) at Shanghai Jiao Tong University. We would like to thank the Laboratory for Wireless and Sensor Networks at Shanghai Jiao Tong University, especially Prof. Min-You Wu and Jia Peng, for providing access to this data.
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Keler, A., Krisp, J.M., Ding, L. (2017). Visualization of Traffic Bottlenecks: Combining Traffic Congestion with Complicated Crossings. In: Peterson, M. (eds) Advances in Cartography and GIScience. ICACI 2017. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-57336-6_34
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DOI: https://doi.org/10.1007/978-3-319-57336-6_34
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