Overtaking assistant algorithm based on model predictive control

Fisnik Sulejmani

Research output: ThesisMaster's / Diploma thesis

Abstract

It is generally accepted that an anticipatory driving style can yield a substantial contribution to improve efficiency and safety of transport. However, such an anticipatory driving style requires high attention of the driver to assess the traffic situation accurately and presume the correct reactions. Considering country road traffic a high risk is present keeping in mind the high velocities as well as the oncoming traffic participants. This work focuses on overtaking maneuvers on country roads, and a stochastic model predictive control (MPC) algorithm is implemented to manage this task. The behavior of the surrounding vehicles is predicted stochastically by using Bayesian networks. Simulation results show that the control algorithm performs safe maneuvers for all the observed scenarios. Finally, the performance of the controller is compared to the human driver, with a study in a stochastic traffic environment. The results show that the control algorithm provides the safest trip in an acceptable travel time.
Original languageEnglish
Publication statusPublished - 2019

Fields of science

  • 206002 Electro-medical engineering
  • 207109 Pollutant emission
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202027 Mechatronics
  • 202034 Control engineering
  • 203027 Internal combustion engines
  • 206001 Biomedical engineering

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

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