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GIS-Aided Traffic Monitoring Using Multiple Sensor Integration

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Encyclopedia of GIS

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Abstract

Traffic understanding is a crucial part of the autonomous driving. The adjacent objects should be detected, tracked, and classified while the platform is in motion. This entry presents a multiple sensor integration solution to achieve the object segmentation, tracking, and recognition. The point cloud is applied to segment and track the objects. GPS/IMU navigation solution is used to estimate the motion of the platform and compensate it from the motion of the tracked objects. Then, the moving objects are discriminated, and a histogram of gradient (HOG)-based pedestrian detection is used to recognize the pedestrians on the road. GIS databases are used to locate the static objects such as road signs, to filter out the off-road objects such as buildings and vegetation and to provide speed limit and direction of the traffic used in object recognition.

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Author information

Authors and Affiliations

  1. The Ohio State University, 2070 Neil Ave., 43210, Columbus, OH, USA

    Siavash Hosseinyalamdary

Authors
  1. Siavash Hosseinyalamdary
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Correspondence to Siavash Hosseinyalamdary .

Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, MN, USA

    Shashi Shekhar

  2. Management Science and Information Systems Department, Rutgers Business School, Rutgers, The State University of New Jersey, Newark, NJ, USA

    Hui Xiong

  3. Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA, USA

    Xun Zhou

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Hosseinyalamdary, S. (2017). GIS-Aided Traffic Monitoring Using Multiple Sensor Integration. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_1620

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