Formal methods to comply with rules of the road in autonomous driving: State of the art and grand challenges

N Mehdipour, M Althoff, RD Tebbens, C Belta - Automatica, 2023 - Elsevier
We provide a review of recent work on formal methods for autonomous driving. Formal
methods have been traditionally used to specify and verify the behavior of computer …

A review of model predictive controls applied to advanced driver-assistance systems

A Musa, M Pipicelli, M Spano, F Tufano, F De Nola… - Energies, 2021 - mdpi.com
Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in
the automotive field, as enablers for vehicle energy consumption, safety, and comfort …

Parallel vision for intelligent transportation systems in metaverse: Challenges, solutions, and potential applications

H Zhang, G Luo, Y Li, FY Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Metaverse and intelligent transportation system (ITS) are disruptive technologies that have
the potential to transform the current transportation system by decreasing traffic accidents …

HiVeGPT: Human-machine-augmented intelligent vehicles with generative pre-trained transformer

J Zhang, J Pu, J Xue, M Yang, X Xu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Recently, a chat generative pre-trained transformer (ChatGPT) attracts widespread attention
in the academies and industries because of its powerful conversational ability with human …

A tube-MPC approach to autonomous multi-vehicle racing on high-speed ovals

A Wischnewski, T Herrmann, F Werner… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Autonomous vehicle racing has emerged as vibrant, innovative technology development,
demonstration platform in recent years. Universities, companies demonstrate their …

A faster cooperative lane change controller enabled by formulating in spatial domain

H Wang, W Hao, J So, X Xiao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Lane-Change (LC) maneuvers are deemed to jeopardize traffic safety, mobility, and
sustainability. Cooperative Lane-Change (CLC) solves this problem by accelerating the LC …

Model predictive control of nonlinear processes using neural ordinary differential equation models

J Luo, F Abdullah, PD Christofides - Computers & Chemical Engineering, 2023 - Elsevier
Abstract Neural Ordinary Differential Equation (NODE) is a recently proposed family of deep
learning models that can perform a continuous approximation of a linear/nonlinear dynamic …

An improved model predictive control-based trajectory planning method for automated driving vehicles under uncertainty environments

T Qie, W Wang, C Yang, Y Li, Y Zhang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
For automated driving vehicles, trajectory planning is responsible for obtaining feasible
trajectories with velocity profiles according to driving environments. From the perspective of …

Stochastically predictive co-optimization of the speed planning and powertrain controls for electric vehicles driving in random traffic environment safely and efficiently

X Zhou, F Sun, C Zhang, C Sun - Journal of Power Sources, 2022 - Elsevier
With inevitable random disturbance in traffic scenarios, electric vehicles (EVs) may face the
driving safety issue, while, if operated over cautiously, the frequent speed variation …

Gaussian process-based stochastic model predictive control for overtaking in autonomous racing

T Brüdigam, A Capone, S Hirche, D Wollherr… - arXiv preprint arXiv …, 2021 - arxiv.org
A fundamental aspect of racing is overtaking other race cars. Whereas previous research on
autonomous racing has majorly focused on lap-time optimization, here, we propose a …