# Feasible Trajectories Generation for Autonomous Driving Vehicles

^{1}

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Vehicle Kinematic Model

## 3. Position Quintic Polynomial for Trajectory Generation

^{T}and y

^{T}is too short, causing the steering angle to be too large. The next part presents the method to achieve feasible and optimal trajectories subject to vehicle constraints and environmental limitations.

## 4. Trajectory Generation Subject to Constraints

## 5. Speed Quartic Polynomial Trajectory Generation

## 6. Symmetric Polynomial Trajectory Generation

## 7. Performances Comparison

## 8. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**MDPI and ACS Style**

Vu, T.M.; Moezzi, R.; Cyrus, J.; Hlava, J.; Petru, M. Feasible Trajectories Generation for Autonomous Driving Vehicles. *Appl. Sci.* **2021**, *11*, 11143.
https://doi.org/10.3390/app112311143

**AMA Style**

Vu TM, Moezzi R, Cyrus J, Hlava J, Petru M. Feasible Trajectories Generation for Autonomous Driving Vehicles. *Applied Sciences*. 2021; 11(23):11143.
https://doi.org/10.3390/app112311143

**Chicago/Turabian Style**

Vu, Trieu Minh, Reza Moezzi, Jindrich Cyrus, Jaroslav Hlava, and Michal Petru. 2021. "Feasible Trajectories Generation for Autonomous Driving Vehicles" *Applied Sciences* 11, no. 23: 11143.
https://doi.org/10.3390/app112311143