[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

M Mamdouh et al., 2024 - Google Patents

A reinforcement learning model for autonomous vehicles with realistic car simulation in urban using unity

M Mamdouh et al., 2024

Document ID
16372204815570205654
Author
M Mamdouh A
Frouk M
Khater H
F Hassan Y
Publication year
Publication venue
Engineering Research Express

External Links

Snippet

Simulator training with reinforcement learning (RL) for autonomous vehicles (AVs) offers advantages over supervised learning. However, transferring the learned behaviours to the real world is a challenging task due to the inconsistencies between the data captured by the …
Continue reading at iopscience.iop.org (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/36Input/output arrangements of navigation systems
    • G01C21/3626Details of the output of route guidance instructions
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/10Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration
    • G01C21/12Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • G05D1/0295Fleet control by at least one leading vehicle of the fleet
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00Teaching not covered by other main groups of this subclass
    • G09B19/16Control of vehicles or other craft

Similar Documents

Publication Publication Date Title
Huang et al. Multi-modal sensor fusion-based deep neural network for end-to-end autonomous driving with scene understanding
US10976741B2 (en) Safety and comfort constraints for navigation
US11835951B2 (en) Object motion prediction and autonomous vehicle control
Müller et al. Sim4cv: A photo-realistic simulator for computer vision applications
US20230359202A1 (en) Jointly Learnable Behavior and Trajectory Planning for Autonomous Vehicles
CN108230817B (en) Vehicle driving simulation method and apparatus, electronic device, system, program, and medium
US20200159225A1 (en) End-To-End Interpretable Motion Planner for Autonomous Vehicles
Fernandes et al. CaRINA intelligent robotic car: architectural design and applications
Chen et al. Advances in intelligent vehicles
CN116051779A (en) 3D surface reconstruction using point cloud densification for autonomous systems and applications using deep neural networks
Gómez-Huelamo et al. Simulating use cases for the UAH Autonomous Electric Car
Rosero et al. A software architecture for autonomous vehicles: Team lrm-b entry in the first carla autonomous driving challenge
Li et al. Towards Autonomous Driving with Small-Scale Cars: A Survey of Recent Development
Manikandan et al. Ad hoc-obstacle avoidance-based navigation system using deep reinforcement learning for self-driving vehicles
M Mamdouh et al. A reinforcement learning model for autonomous vehicles with realistic car simulation in urban using unity
EP4124995A1 (en) Training method for training an agent for controlling a controlled device, control method for controlling the controlled device, computer program(s), computer readable medium, training system and control system
Boissé et al. Cybernetic transportation systems design and development: Simulation software cybercars
Joshi et al. LiDAR-based autonomous Self Driving mini Vehicle
Aaslund A Structured Approach to Autonomous Driving in Simulated Environments
Moudhgalya Language Conditioned Self-Driving Cars Using Environmental Object Descriptions For Controlling Cars
Kumar et al. An Overview on Automated Vehicles
Ren et al. Autonomous Driving Simulator
Singh et al. Autonomous navigating robotic car
Nilmantha Deep 3D Dynamic Object Detection towards Successful and Safe Navigation for Full Autonomous Driving
Albilani Neuro-symbolic deep reinforcement learning for safe urban driving using low-cost sensors.