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

Siebinga, 2024 - Google Patents

Communication-Enabled Interactions in Highway Traffic: A joint driver model for merging

Siebinga, 2024

Document ID
371137223151620433
Author
Siebinga O
Publication year

External Links

Snippet

Automated driving technologies offer significant societal benefits but face challenges, particularly in interactions between automated and human-driven vehicles during lane changes and merging on highways. This thesis addresses this issue by focusing on joint …
Continue reading at research.tudelft.nl (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • 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
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems
    • G08G1/167Driving aids for lane monitoring, lane changing, e.g. blind spot detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis

Similar Documents

Publication Publication Date Title
Guo et al. Is it safe to drive? An overview of factors, metrics, and datasets for driveability assessment in autonomous driving
US11643106B2 (en) Movement prediction of pedestrians useful for autonomous driving
US11667301B2 (en) Symbolic modeling and simulation of non-stationary traffic objects for testing and development of autonomous vehicle systems
Gazis et al. Nonlinear follow-the-leader models of traffic flow
Zhou et al. Review of learning-based longitudinal motion planning for autonomous vehicles: research gaps between self-driving and traffic congestion
Munigety et al. Towards behavioral modeling of drivers in mixed traffic conditions
CN111542831A (en) System and method for predicting human interaction with vehicle
US11919545B2 (en) Scenario identification for validation and training of machine learning based models for autonomous vehicles
Siebinga et al. A human factors approach to validating driver models for interaction-aware automated vehicles
Zhang et al. Predictive trajectory planning for autonomous vehicles at intersections using reinforcement learning
Lu et al. Performance evaluation of surrogate measures of safety with naturalistic driving data
Guo et al. Modeling driver’s evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning
Amini et al. Development of a conflict risk evaluation model to assess pedestrian safety in interaction with vehicles
Benrachou et al. Use of social interaction and intention to improve motion prediction within automated vehicle framework: A review
Wang et al. Uncovering interpretable internal states of merging tasks at highway on-ramps for autonomous driving decision-making
Zhao et al. Measuring sociality in driving interaction
Islam et al. Enhancing Longitudinal Velocity Control With Attention Mechanism-Based Deep Deterministic Policy Gradient (DDPG) for Safety and Comfort
Scheel et al. Recurrent models for lane change prediction and situation assessment
Arbabi et al. Planning for autonomous driving via interaction-aware probabilistic action policies
Siebinga Communication-Enabled Interactions in Highway Traffic: A joint driver model for merging
Huang et al. A data-driven operational integrated driving behavioral model on highways
Sun et al. Learning two-dimensional merging behaviour from vehicle trajectories with imitation learning
Huang Safe intention-aware maneuvering of autonomous vehicles
Malik et al. Explainable Artificial Intelligence for Autonomous Vehicles: Concepts, Challenges, and Applications
Piazzoni Modeling perception errors in autonomous vehicles and their impact on behavior