Two-dimensional merging path generation using model predictive control

Wenjing Cao, Masakazu Mukai, Taketoshi Kawabe

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

A merging path generation method for automated vehicle merging is proposed. This method can make the relevant vehicles cooperate with each other with constraint accelerations, keep the vehicles in their lanes and generate collision free merging path. The merging problem is considered in the two-dimensional space. We set up the mathematic model of the system, formulate the two-dimensional merging problem as an optimization problem and solve it by model predictive control (MPC). To compare the simulation results with the practice, three typical cases were researched. In order to be more practical, the initial conditions of the cases were set according to the data obtained through analyzing the helicopter-shot video. The results represent that the MPC-controlled merging maneuver carried out safely and smoothly, and the relative positions after merging is also the same with the practical results in all the three representative conditions considered. The absolute values of the accelerations of the vehicles are all kept below a practical value 3 m/s2. The importance of cooperation in merging maneuver can also be noticed in the simulation results. By letting the relevant vehicles cooperate, this control algorithm would generate collision free merging path even in the very severe condition. The computational time for the three cases is also short enough for the method to be implemented in actual situation.

Original languageEnglish
Pages (from-to)350-356
Number of pages7
JournalArtificial Life and Robotics
Volume17
Issue number3-4
DOIs
Publication statusPublished - Feb 2013

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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