Control of connected and automated vehicles: State of the art and future challenges
Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …
challenges include the unknown intentions of other road users: communication between …
Recent advances in motion and behavior planning techniques for software architecture of autonomous vehicles: A state-of-the-art survey
Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …
industrial research because of various advantages such as safety improvement, lower …
A potential field-based model predictive path-planning controller for autonomous road vehicles
Y Rasekhipour, A Khajepour, SK Chen… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Artificial potential fields and optimal controllers are two common methods for path planning
of autonomous vehicles. An artificial potential field method is capable of assigning different …
of autonomous vehicles. An artificial potential field method is capable of assigning different …
Optimal eco-driving control of connected and autonomous vehicles through signalized intersections
This article focuses on the speed planning problem for connected and automated vehicles
(CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized …
(CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized …
Trajectory planning and tracking for autonomous overtaking: State-of-the-art and future prospects
Trajectory planning and trajectory tracking constitute two important functions of an
autonomous overtaking system and a variety of strategies have been proposed in the …
autonomous overtaking system and a variety of strategies have been proposed in the …
Game theoretic modeling of driver and vehicle interactions for verification and validation of autonomous vehicle control systems
Autonomous driving has been the subject of incre-ased interest in recent years both in
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
Looking at humans in the age of self-driving and highly automated vehicles
E Ohn-Bar, MM Trivedi - IEEE Transactions on Intelligent …, 2016 - ieeexplore.ieee.org
This paper highlights the role of humans in the next generation of driver assistance and
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …
End-to-end learning of driving models with surround-view cameras and route planners
For human drivers, having rear and side-view mirrors is vital for safe driving. They deliver a
more complete view of what is happening around the car. Human drivers also heavily exploit …
more complete view of what is happening around the car. Human drivers also heavily exploit …
Safely entering the deep: A review of verification and validation for machine learning and a challenge elicitation in the automotive industry
Deep Neural Networks (DNN) will emerge as a cornerstone in automotive software
engineering. However, developing systems with DNNs introduces novel challenges for …
engineering. However, developing systems with DNNs introduces novel challenges for …
Scenario understanding and motion prediction for autonomous vehicles—review and comparison
Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …