Artificial Life and Robotics

, Volume 24, Issue 4, pp 527–533 | Cite as

Merging trajectory generation method using real-time optimization with enhanced robustness against sensor noise

  • Wenjing CaoEmail author
  • Masakazu Mukai
  • Taketoshi Kawabe
Original Article


To reduce drivers’ mental load and traffic congestion caused by merging maneuver, a merging trajectory generation method aiming for practical automatic driving was proposed in the past research by the authors. In this paper, the robustness of the method against sensor noises is enhanced. The robustness is improved by the dummy optimization variables that relax the equality constraints and the barrier functions. The stage costs composed by these introduced dummy variables are designed to generate safe and smooth merging maneuver. The effectiveness of the proposed method for a typical case is observed in the simulation results. To check if the proposed method works well under different initial conditions, 116 initial conditions are generated randomly. The proposed method solves all the cases of merging problem, while the conventional method fails in 80% of the cases.


Merging maneuver Robustness enhancement Sensor noise Model predictive control Automatic drive 



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Copyright information

© International Society of Artificial Life and Robotics (ISAROB) 2019

Authors and Affiliations

  1. 1.Department of Engineering and Applied Sciences, Faculty of Science and TechnologySophia UniversityTokyoJapan
  2. 2.Department of Electrical and Electronic Engineering, Faculty of EngineeringKogakuin UniversityTokyoJapan
  3. 3.Department of Electrical Engineering, Faculty of Information Science and Electrical EngineeringKyushu UniversityFukuokaJapan

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