This paper presents AHMEDULLAHBOT which is a 4DOF self-driven vehicle capable of localizing itself in a grid and planning a path between two nodes. It can avoid particular nodes and plan path between two allowed nodes. Breadth-first search & Dijkstra's Algorithm have been used for finding the path between two allowed nodes. The vehicle is also capable of transferring blocks from one node to ano...

In recent years, advancements in electric vehicle (EV) technology and rising petrol prices have increased the demand for EVs also made them important Smart Grid (SG) economy. During high energy demand, Vehicle to (V2G) comprises a notable feature that returns stored back grid. However, due dynamic nature of availability, determining best charging discharging strategy is quite difficult. The exi...

Integrating plug-in electric vehicles (PEVs) into a smart grid can pose some challenges, particularly when significant number of these are simultaneously charged and discharged. However, management PEVs in vehicle-to-grid (V2G) system result benefits to the such as load leveling, cost reduction. This paper proposes unit commitment model for V2G connected power grid. The considers different pene...

The electric vehicle (EV) industry is quickly growing in the present scenario, and will have more demand future. A sharp increase sales of EVs by 160% 2021 represents 26% new worldwide automotive market. are deemed to be transportation future, as they offer significant cost savings reduce carbon emissions. However, their interactions with power grid, charging stations, households require commun...

The problem of autonomous vehicle navigation between lanes, around obstacles and towards a short term goal can be solved using Reinforcement Learning. The multi-lane road ahead of a vehicle may be represented by a Markov Decision Process (MDP) grid-world containing positive and negative rewards, allowing for practical computation of an optimal path using either value iteration (VI) or policy it...