Autonomous vehicles (AV) are expected to improve road safety and reduce traffic
congestion by optimizing routes and reducing human errors. AVs have the potential to …

A real-time, metadata-driven electric vehicle routing optimization to reduce on-road energy
requirements is proposed in this work. The proposed strategy employs the state–action …

The local path planning, as one of the navigation stages, plays a significant role in the
energy consumption of Self-Guided Vehicles (SGV). Since SGV must operate for several …

Eco‐driving assistance systems encourage economical driving behaviour and support the
driver in optimising his/her driving style to achieve fuel economy and consequently …

A real-time, data-driven electric vehicle (EVs) routing optimization to achieve energy
consumption minimization is proposed in this work. The proposed framework utilizes the …

The local path planning, as one of the navigation stages, plays a significant role in the
energy consumption of Self-Guided Vehicles (SGV). Since SGV must operate for several …

The average battery life of drones in use today is around 30 minutes, which poses significant
limitations for ensuring long-range operation, such as seamless delivery and security …

Eco-driving is a driving vehicle strategy aimed at minimizing energy consumption; that is, it is
a method to improve vehicle efficiency by optimizing driving behavior without making any …

This paper presents a multi-agent reinforcement learning (MARL) algorithm to address the
scheduling and routing problems of multiple automated guided vehicles (AGVs), with the …

This article describes the application of Reinforcement Learning (RL) with an embedded
heuristic algorithm to a multi-objective hybrid vehicle optimization. A multi-objective …