Emerging trends in intelligent vehicles: The IEEE TIV perspective
This article is focused on bibliographic analysis and collaboration pattern analysis of the text
papers published in the IEEE Transactions on Intelligent Vehicles (TIV) from January 2019 …
papers published in the IEEE Transactions on Intelligent Vehicles (TIV) from January 2019 …
Trajectory optimization of an electric vehicle with minimum energy consumption using inverse dynamics model and servo constraints
Trajectory planning is a crucial aspect of autonomous driving for energy conservation ans
savings, especially in electric vehicles (EVs). A particular vehicle inverse dynamics model is …
savings, especially in electric vehicles (EVs). A particular vehicle inverse dynamics model is …
Autonomous driving on curvy roads without reliance on frenet frame: A cartesian-based trajectory planning method
Curvy roads are a particular type of urban road scenario, wherein the curvature of the road
centerline changes drastically. This paper is focused on the trajectory planning task for …
centerline changes drastically. This paper is focused on the trajectory planning task for …
Recent advances in path integral control for trajectory optimization: An overview in theoretical and algorithmic perspectives
This paper presents a tutorial overview of path integral (PI) approaches for stochastic
optimal control and trajectory optimization. We concisely summarize the theoretical …
optimal control and trajectory optimization. We concisely summarize the theoretical …
Deep neural networks with Koopman operators for modeling and control of autonomous vehicles
Y Xiao, X Zhang, X Xu, X Liu… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Autonomous driving technologies have received notable attention in the past decades. In
autonomous driving systems, identifying a precise dynamical model for motion control is …
autonomous driving systems, identifying a precise dynamical model for motion control is …
Alternating direction method of multipliers for constrained iterative LQR in autonomous driving
J Ma, Z Cheng, X Zhang, M Tomizuka… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In the context of autonomous driving, the iterative linear quadratic regulator (iLQR) is known
to be an efficient approach to deal with the nonlinear vehicle model in motion planning …
to be an efficient approach to deal with the nonlinear vehicle model in motion planning …
Sine resistance network-based motion planning approach for autonomous electric vehicles in dynamic environments
This article proposes a motion planning approach for autonomous electric vehicles to
generate an appropriate planned path according to the time-varying surrounding …
generate an appropriate planned path according to the time-varying surrounding …
Enhance sample efficiency and robustness of end-to-end urban autonomous driving via semantic masked world model
End-to-end autonomous driving provides a feasible way to automatically maximize overall
driving system performance by directly mapping the raw pixels from a front-facing camera to …
driving system performance by directly mapping the raw pixels from a front-facing camera to …
Local learning enabled iterative linear quadratic regulator for constrained trajectory planning
Trajectory planning is one of the indispensable and critical components in robotics and
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
Decentralized iLQR for cooperative trajectory planning of connected autonomous vehicles via dual consensus ADMM
Cooperative trajectory planning of connected autonomous vehicles (CAVs) generally admits
strong nonlinearity and non-convexity, rendering great difficulties in finding the optimal …
strong nonlinearity and non-convexity, rendering great difficulties in finding the optimal …