[HTML][HTML] Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions
Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …
research because of its multi-faceted advantages that includes improved safety, reduced …
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 …
Cyber threats facing autonomous and connected vehicles: Future challenges
Vehicles are currently being developed and sold with increasing levels of connectivity and
automation. As with all networked computing devices, increased connectivity often results in …
automation. As with all networked computing devices, increased connectivity often results in …
Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach
It has been well recognized that human driver's limits, heterogeneity, and selfishness
substantially compromise the performance of our urban transport systems. In recent years, in …
substantially compromise the performance of our urban transport systems. In recent years, in …
Hierarchical reinforcement learning for self‐driving decision‐making without reliance on labelled driving data
Decision making for self‐driving cars is usually tackled by manually encoding rules from
drivers' behaviours or imitating drivers' manipulation using supervised learning techniques …
drivers' behaviours or imitating drivers' manipulation using supervised learning techniques …
A comparative study of state-of-the-art driving strategies for autonomous vehicles
The autonomous vehicle is regarded as a promising technology with the potential to
reshape mobility and solve many traffic issues, such as accessibility, efficiency …
reshape mobility and solve many traffic issues, such as accessibility, efficiency …
Real-time trajectory planning for autonomous urban driving: Framework, algorithms, and verifications
This paper focuses on the real-time trajectory planning problem for autonomous vehicles
driving in realistic urban environments. To solve the complex navigation problem, we adopt …
driving in realistic urban environments. To solve the complex navigation problem, we adopt …
Lateral vehicle trajectory optimization using constrained linear time-varying MPC
B Gutjahr, L Gröll, M Werling - IEEE Transactions on Intelligent …, 2016 - ieeexplore.ieee.org
In this paper, a trajectory optimization algorithm is proposed, which formulates the lateral
vehicle guidance task along a reference curve as a constrained optimal control problem …
vehicle guidance task along a reference curve as a constrained optimal control problem …
Conditional predictive behavior planning with inverse reinforcement learning for human-like autonomous driving
Making safe and human-like decisions is an essential capability of autonomous driving
systems, and learning-based behavior planning presents a promising pathway toward …
systems, and learning-based behavior planning presents a promising pathway toward …
Intelligent and connected vehicles: Current status and future perspectives
Intelligent connected vehicles (ICVs) are believed to change people's life in the near future
by making the transportation safer, cleaner and more comfortable. Although many …
by making the transportation safer, cleaner and more comfortable. Although many …