An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles
The full-fledged development and the practical use of autonomous vehicles (AVs) would be a great technological achievement and would substantially reduce the enormous damages caused by driving accidents to life and property. Technology based companies such as Google and Audi are getting closer to re...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-02-01
|
| Series: | Engineering Science and Technology, an International Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098620342658 |
| _version_ | 1831672648577318912 |
|---|---|
| author | Nastaran Tork Abdollah Amirkhani Shahriar B. Shokouhi |
| author_facet | Nastaran Tork Abdollah Amirkhani Shahriar B. Shokouhi |
| author_sort | Nastaran Tork |
| collection | DOAJ |
| description | The full-fledged development and the practical use of autonomous vehicles (AVs) would be a great technological achievement and would substantially reduce the enormous damages caused by driving accidents to life and property. Technology based companies such as Google and Audi are getting closer to realizing the dream of seeing fully AVs on the road. A vehicle’s severely nonlinear dynamics due to the forces acting between road and vehicle tires, the coupling characteristic, and the uncertainties of parameters such as wheel moment of inertia and vehicle mass have made it rather difficult to approximate a precise mathematical model of vehicle dynamics. In this paper, to overcome these challenges we propose a model-independent control method based on improved adaptive neural controllers for path tracking control of AVs. In the structure of these improved neural controllers, we employ interval type-2 fuzzy sets (IT2FS) as activation functions. Despite the interdependence of a vehicle’s longitudinal and lateral motions, many of the research works on the path tracking of AVs have only focused on lateral motion control. By using the inputs of steering angle and torque, the presented control scheme tackles the simultaneous control of lateral and longitudinal moves. Results obtained from the lateral controller based on an improved neural network (NN) have been analyzed first at a constant velocity of 20 m/s and with/without considering parametric uncertainties. Then the longitudinal controller based on the improved NN is compared with sliding mode and common NN based controllers. Finally, the results obtained by simulating the simultaneous control of lateral and longitudinal motions indicate maximum tracking errors of 0.04 m (for lateral path following) and 0.02 m/s (for longitudinal velocity) and demonstrate the desirable performance of the proposed control approach. |
| first_indexed | 2024-12-19T23:56:18Z |
| format | Article |
| id | doaj.art-515df243abe24a2dbd733cc7dc9ecd1f |
| institution | Directory Open Access Journal |
| issn | 2215-0986 |
| language | English |
| last_indexed | 2024-12-19T23:56:18Z |
| publishDate | 2021-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Engineering Science and Technology, an International Journal |
| spelling | doaj.art-515df243abe24a2dbd733cc7dc9ecd1f2022-12-21T20:00:59ZengElsevierEngineering Science and Technology, an International Journal2215-09862021-02-01241126137An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehiclesNastaran Tork0Abdollah Amirkhani1Shahriar B. Shokouhi2School of Electrical Engineering, Iran University of Science and Technology, Tehran 16846-13114, IranSchool of Automotive Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran; Corresponding author.School of Electrical Engineering, Iran University of Science and Technology, Tehran 16846-13114, IranThe full-fledged development and the practical use of autonomous vehicles (AVs) would be a great technological achievement and would substantially reduce the enormous damages caused by driving accidents to life and property. Technology based companies such as Google and Audi are getting closer to realizing the dream of seeing fully AVs on the road. A vehicle’s severely nonlinear dynamics due to the forces acting between road and vehicle tires, the coupling characteristic, and the uncertainties of parameters such as wheel moment of inertia and vehicle mass have made it rather difficult to approximate a precise mathematical model of vehicle dynamics. In this paper, to overcome these challenges we propose a model-independent control method based on improved adaptive neural controllers for path tracking control of AVs. In the structure of these improved neural controllers, we employ interval type-2 fuzzy sets (IT2FS) as activation functions. Despite the interdependence of a vehicle’s longitudinal and lateral motions, many of the research works on the path tracking of AVs have only focused on lateral motion control. By using the inputs of steering angle and torque, the presented control scheme tackles the simultaneous control of lateral and longitudinal moves. Results obtained from the lateral controller based on an improved neural network (NN) have been analyzed first at a constant velocity of 20 m/s and with/without considering parametric uncertainties. Then the longitudinal controller based on the improved NN is compared with sliding mode and common NN based controllers. Finally, the results obtained by simulating the simultaneous control of lateral and longitudinal motions indicate maximum tracking errors of 0.04 m (for lateral path following) and 0.02 m/s (for longitudinal velocity) and demonstrate the desirable performance of the proposed control approach.http://www.sciencedirect.com/science/article/pii/S2215098620342658Autonomous vehicleFuzzy setsLateral and longitudinal controlPath-tracking |
| spellingShingle | Nastaran Tork Abdollah Amirkhani Shahriar B. Shokouhi An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles Engineering Science and Technology, an International Journal Autonomous vehicle Fuzzy sets Lateral and longitudinal control Path-tracking |
| title | An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles |
| title_full | An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles |
| title_fullStr | An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles |
| title_full_unstemmed | An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles |
| title_short | An adaptive modified neural lateral-longitudinal control system for path following of autonomous vehicles |
| title_sort | adaptive modified neural lateral longitudinal control system for path following of autonomous vehicles |
| topic | Autonomous vehicle Fuzzy sets Lateral and longitudinal control Path-tracking |
| url | http://www.sciencedirect.com/science/article/pii/S2215098620342658 |
| work_keys_str_mv | AT nastarantork anadaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles AT abdollahamirkhani anadaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles AT shahriarbshokouhi anadaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles AT nastarantork adaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles AT abdollahamirkhani adaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles AT shahriarbshokouhi adaptivemodifiedneurallaterallongitudinalcontrolsystemforpathfollowingofautonomousvehicles |