Research Article

Optimization Based Lateral and Longitudinal Trajectory Planning for Autonomous Vehicles

Number: 27 November 30, 2021
EN TR

Optimization Based Lateral and Longitudinal Trajectory Planning for Autonomous Vehicles

Abstract

In recent years, autonomous vehicles have gained significant attention with the help of technological developments. To fulfill the desired performance expectations, various sub-problems have to be solved efficiently in such complex systems. When these sub-problems are examined in detail, it can be seen that the motion and trajectory planning play a crucial role. Within the scope of this study, the trajectory planning problem was handled in the Frenet coordinate frame and an efficient optimization-based trajectory planning approach was proposed for autonomous driving. The proposed method was essentially based on the analytical solution of an optimization problem which was derived in the offline phase. In the real-time application, only the corresponding trajectory coefficients should be determined by solving a linear set of equations. Encountered practical problems and solution recommendations were also discussed in this study. The effectiveness of the proposed method was demonstrated via real-time simulations that were realized in the “Automotive Data and Time-Triggered Framework (ADTF)” framework.

Keywords

References

  1. Açıkel, S., & Gökçen, A. (2019). Localization and point cloud based 3d mapping with autonomous robots. Avrupa Bilim ve Teknoloji Dergisi, 82-92.
  2. Eugensson, A., Brännström, M., Frasher, D., Rothoff, M., Solyom, S., & Robertsson, A. (2013, May). Environmental, safety legal and societal implications of autonomous driving systems. In International Technical Conference on the Enhanced Safety of Vehicles (ESV). Seoul, South Korea (Vol. 334).
  3. Gao, Y. (2014). Model predictive control for autonomous and semiautonomous vehicles (Doctoral dissertation, UC Berkeley).
  4. Glaser, S., Vanholme, B., Mammar, S., Gruyer, D., & Nouveliere, L. (2010). Maneuver-based trajectory planning for highly autonomous vehicles on real road with traffic and driver interaction. IEEE Transactions on intelligent transportation systems, 11(3), 589-606.
  5. González, D., Pérez, J., Milanés, V., & Nashashibi, F. (2015). A review of motion planning techniques for automated vehicles. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1135-1145.
  6. Heinrich, S. (2018). Planning universal on-road driving strategies for automated vehicles (Vol. 119). Springer.
  7. Kalra, N., & Paddock, S. M. (2016). Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?. Transportation Research Part A: Policy and Practice, 94, 182-193.
  8. Kuwata, Y., Teo, J., Fiore, G., Karaman, S., Frazzoli, E., & How, J. P. (2009). Real-time motion planning with applications to autonomous urban driving. IEEE Transactions on control systems technology, 17(5), 1105-1118.

Details

Primary Language

Turkish

Subjects

Engineering

Journal Section

Research Article

Publication Date

November 30, 2021

Submission Date

May 5, 2021

Acceptance Date

September 20, 2021

Published in Issue

Year 1970 Number: 27

APA
Mutlu, İ. (2021). Otonom Araçlar İçin Optimizasyon Tabanlı Yanal ve Doğrusal Yörünge Planlama. Avrupa Bilim Ve Teknoloji Dergisi, 27, 539-548. https://doi.org/10.31590/ejosat.932390