research-article

Path Planning and Tracking Control for Automatic Driving Obstacle Avoidance

Authors:

RICAI '19: Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence

Pages 300 - 304

https://doi.org/10.1145/3366194.3366247

Published: 20 September 2019 Publication History

Get Access

Abstract

This paper studies the path planning and tracking control of obstacle avoidance lane change in intelligent auto driving. Firstly, the vehicle two-degree-of-freedom model of front wheel steering is established by the knowledge of automobile kinematics and dynamics. Secondly, the trajectory planning is realized by the fifth-order polynomial curve fitting method. Then the linear time-varying model predictive control method is used to realize the tracking control of the trajectory. Finally, MATLAB simulation is used to verify the feasibility of the above ideas. The experimental results show that the fifth-order polynomial can quickly and accurately fit the ideal curve; the model predictive control can also stably control the car to follow the prescribed path.

References

[1]

WNAG C Y, ZHAO W Z, XU Z J.2017. Path planning and sta-bility control of collision avoidance system based on active frontsteering[J]. Science China Technological Sciences, 60(8): 1231--1243

Crossref

Google Scholar

[2]

XIAOLING SONG, LUBIN CAO. 2016. Vehicle obstacle avoidance local path planning based on improved intelligent water droplet algorithm[J]. Automotive Engineering, 38(2): 185--191

Google Scholar

[3]

RUNXIN NIU, TAO MEI, JINGTING XIA. 2010. Intelligent vehicle autonomous driving and obstacle avoidance based on tentacle algorithm construction and correction[J]. Automotive Engineering, 32(12): 1083--1087

Google Scholar

[4]

TU Q, CHEN H, LI J. 2017. A potential field based lateral planningmethod for autonomous vehicles[J]. SAE International Journal of Passenger Cars-Electronic and Electrical Systems. 10(1): 24--34

Google Scholar

[5]

Barraquand J, Latombe J C. 1990. A Monte-Carlo Algorithm for PathPlanning with Many Degrees of Freedom[C]. Proceedings of the 1990 IEEE International Conference on Robotics and Automation. Cincinnati, OH, USA: IEEE: 1712--1717.

Google Scholar

[6]

Yun X P, Tan K C. 1997. A Wall_following Method for Escaping LocalMinima in Potential Field Based Motion Planning[C]. Proceedings of the 8th International Conference on Advanced Robotics. Monter-ey, CA: IEEE: 421--426.

Google Scholar

Cited By

View all

Zhang HYao JTian S(2024)Model Predictive Control for Trajectory Planning Considering Constraints on Vertical Load VariationElectronics10.3390/electronics1308148813:8(1488)Online publication date: 14-Apr-2024
https://doi.org/10.3390/electronics13081488
Biniewicz JPyrz M(2024)Influence of the Road Model on the Optimal Maneuver of a Racing MotorcycleApplied Sciences10.3390/app1410400614:10(4006)Online publication date: 8-May-2024
https://doi.org/10.3390/app14104006
Tang LWang ZDu H(2022)Design of path planning and tracking control for a UGVProceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence10.1145/3584376.3584410(193-199)Online publication date: 16-Dec-2022
https://dl.acm.org/doi/10.1145/3584376.3584410

Index Terms

Path Planning and Tracking Control for Automatic Driving Obstacle Avoidance
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Computational control theory
      2. Motion path planning

Recommendations

Adaptive path planning and tracking system based on model predictive control for autonomous vehicle local obstacle avoidance
Abstract
Path planning and tracking control are the key technologies of autonomous vehicle. The planned path and tracking results affect driving stability and safety directly. In this paper, an improved local path planning method based on model ...
Path Planning based on Astar Algorithm in Automatic Driving
ICACS '22: Proceedings of the 6th International Conference on Algorithms, Computing and Systems

With the rise of automatic driving technology, it needs to be studied more and more problems, path planning is this paper needs to study, at present, the existing algorithms are mainly some traditional algorithms and some improved algorithms on the ...
Path planning with obstacle avoidance by G 1 PH quintic splines

We propose a two-step approach for the construction of planar smooth collision-free navigation paths. Obstacle avoidance techniques that rely on classical data structures are initially considered for the identification of piecewise linear paths having ...

Comments

Information & Contributors

Information

Published In

RICAI '19: Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence

September 2019

803 pages

ISBN:9781450372985

DOI:10.1145/3366194

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 September 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

RICAI 2019

RICAI 2019: 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence

September 20 - 22, 2019

Shanghai, China

Acceptance Rates

RICAI '19 Paper Acceptance Rate 140 of 294 submissions, 48%;

Overall Acceptance Rate 140 of 294 submissions, 48%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
136
Total Downloads

Downloads (Last 12 months)14
Downloads (Last 6 weeks)0

Reflects downloads up to 09 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Zhang HYao JTian S(2024)Model Predictive Control for Trajectory Planning Considering Constraints on Vertical Load VariationElectronics10.3390/electronics1308148813:8(1488)Online publication date: 14-Apr-2024
https://doi.org/10.3390/electronics13081488
Biniewicz JPyrz M(2024)Influence of the Road Model on the Optimal Maneuver of a Racing MotorcycleApplied Sciences10.3390/app1410400614:10(4006)Online publication date: 8-May-2024
https://doi.org/10.3390/app14104006
Tang LWang ZDu H(2022)Design of path planning and tracking control for a UGVProceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence10.1145/3584376.3584410(193-199)Online publication date: 16-Dec-2022
https://dl.acm.org/doi/10.1145/3584376.3584410

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Adaptive path planning and tracking system based on model predictive control for autonomous vehicle local obstacle avoidance

Path Planning based on Astar Algorithm in Automatic Driving

Path planning with obstacle avoidance by G 1 PH quintic splines

Comments

Published In

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Other Metrics

Article Metrics

Other Metrics

Cited By

Login options

Full Access

PDF

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Adaptive path planning and tracking system based on model predictive control for autonomous vehicle local obstacle avoidance

Path Planning based on Astar Algorithm in Automatic Driving

Path planning with obstacle avoidance by G 1 PH quintic splines

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Get Access

Login options

Full Access

View options

PDF

eReader

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations