An integrated framework for autonomous driving: object detection, lane detection, and free space detection

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Abstract

In this paper, we present a deep neural network based real-time integrated framework to detect objects, lane markings, and drivable space using a monocular camera for advanced driver assistance systems. The object detection framework detects and tracks objects on the road such as cars, trucks, pedestrians, bicycles, motorcycles, and traffic signs. The lane detection framework identifies the different lane markings on the road and also distinguishes between the ego lane and adjacent lane boundaries. The free space detection framework estimates the drivable space in front of the vehicle. In our integrated framework, we propose a pipeline combining the three deep neural networks into a single framework, for object detection, lane detection, and free space detection simultaneously. The integrated framework is implemented in C++ and runs real-time on the Nvidia's Drive PX 2 platform.
Original languageEnglish
Title of host publication2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4)
EditorsXin-She Yang, Nilanjan Dey, Amit Joshi
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages260-265
Number of pages6
ISBN (Electronic)978-1-7281-3780-3
DOIs
Publication statusPublished - 31 Jul 2019
Event2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4) - London, United Kingdom
Duration: 30 Jul 201931 Jul 2019

Conference

Conference2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4)
CountryUnited Kingdom
CityLondon
Period30/07/1931/07/19

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Keywords

  • Advanced driver assistance system
  • Artificial intelligence
  • Autonomous driving
  • Deep neural network
  • Free space detection
  • Lane detection
  • Object detection

Cite this

Kemsaram, N., Das, A., & Dubbelman, G. (2019). An integrated framework for autonomous driving: object detection, lane detection, and free space detection. In X-S. Yang, N. Dey, & A. Joshi (Eds.), 2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4) (pp. 260-265). [8904020] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WorldS4.2019.8904020