Human-like driver model for emergency collision avoidance using neural network autoregressive with exogenous inputs
One of the most difficult challenges in providing a reliable and safe autonomous collision avoidance maneuver is developing the driver model that provides the planning system with the risk of an impending collision. Over the last few years, researchers have extensively studied several methodologies...
Main Authors: | Nurhaffizah, Hassan, Mohd Hatta, Mohammad Ariff, Hairi, Zamzuri, Sarah ‘Atifah, Saruchi, Nurbaiti, Wahid |
---|---|
Format: | Book Chapter |
Language: | English English English |
Published: |
Woodhead Publishing
2024
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/41786/1/Machine%20Intelligence%20in%20Mechanical%20Engineering.pdf http://umpir.ump.edu.my/id/eprint/41786/2/Human-like%20driver%20model%20for%20emergency%20collision%20avoidance_ABST.pdf http://umpir.ump.edu.my/id/eprint/41786/3/Human-like%20driver%20model%20for%20emergency%20collision%20avoidance.pdf |
Similar Items
-
Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
by: Nurbaiti, Wahid, et al.
Published: (2024) -
Artificial neural network for modelling of the correlation between lateral acceleration and head movement in a motion sickness study
by: Saruchi, Sarah ‘Atifah, et al.
Published: (2019) -
A brief review on motion sickness for autonomous vehicle
by: Saruchi, Sarah ‘Atifah, et al.
Published: (2022) -
Multi-actuators vehicle collision avoidance system - Experimental validation
by: Umar Zakir, Abdul Hamid, et al.
Published: (2018) -
Novel motion sickness minimization control via fuzzy-pid controller for autonomous vehicle
by: Saruchi, Sarah Atifah, et al.
Published: (2020)