Sensor based Prediction of Human Driving Decisions using Feed forward Neural Networks for Intelligent Vehicles

Shriram C. Jugade, Alessandro C. Victorino, Veronique B. Cherfaoui, Stratis Kanarachos

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

2 Citations (Scopus)

Abstract

Prediction of human driving decisions is an important aspect of modeling human behavior for the application to Advanced Driver Assistance Systems (ADAS) in the intelligent vehicles. This paper presents a sensor based receding horizon model for the prediction of human driving commands. Human driving decisions are expressed in terms of the vehicle speed and steering wheel angle profiles. Environmental state and human intention are the two major factors influencing the human driving decisions. The environment around the vehicle is perceived using LIDAR sensor. Feature extractor computes the occupancy grid map from the sensor data which is filtered and processed to provide precise and relevant information to the feed-forward neural network. Human intentions can be identified from the past driving decisions and represented in the form of time series data for the neural network. Supervised machine learning is used to train the neural network. Data collection and model validation is performed in the driving simulator using the SCANeR studio software. Simulation results are presented alone with the analysis.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages691-696
Number of pages6
ISBN (Electronic)978-1-7281-0323-5
ISBN (Print)978-1-7281-0321-1
DOIs
Publication statusPublished - 10 Dec 2018
Event21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States
Duration: 4 Nov 20187 Nov 2018

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-November

Conference

Conference21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
CountryUnited States
CityMaui
Period4/11/187/11/18

Keywords

  • ADAS
  • Autonomous Navigation
  • human driving behavior
  • human driving decisions
  • Intelligent vehicle
  • Neural Networks
  • Shared Control

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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  • Cite this

    Jugade, S. C., Victorino, A. C., Cherfaoui, V. B., & Kanarachos, S. (2018). Sensor based Prediction of Human Driving Decisions using Feed forward Neural Networks for Intelligent Vehicles. In 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018 (pp. 691-696). [8569441] (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2018-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2018.8569441