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

Mian et al., 2020 - Google Patents

Modeling of individual differences in driver behavior

Mian et al., 2020

Document ID
15983187559964473958
Author
Mian M
Jaffry W
Publication year
Publication venue
Journal of Ambient Intelligence and Humanized Computing

External Links

Snippet

Computational transportation is a scientific discipline which uses traffic flow simulation for intervention design and analysis. Realistic traffic flow simulation depends on realistic computational modeling of individual agents such as drivers. Whereas, realistic agent model …
Continue reading at link.springer.com (other versions)

Classifications

    • 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
    • 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
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • 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

Similar Documents

Publication Publication Date Title
Sohrabi et al. Quantifying the automated vehicle safety performance: A scoping review of the literature, evaluation of methods, and directions for future research
Ali et al. A hazard-based duration model to quantify the impact of connected driving environment on safety during mandatory lane-changing
Do et al. Simulation‐based connected and automated vehicle models on highway sections: A literature review
Khattak et al. Cooperative lane control application for fully connected and automated vehicles at multilane freeways
Lu et al. A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks
Carrone et al. Autonomous vehicles in mixed motorway traffic: capacity utilisation, impact and policy implications
Ali et al. Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment
Kesting et al. General lane-changing model MOBIL for car-following models
Liu et al. Fine-tuning ADAS algorithm parameters for optimizing traffic safety and mobility in connected vehicle environment
Sun et al. Research and implementation of lane-changing model based on driver behavior
Mian et al. Modeling of individual differences in driver behavior
Ali et al. A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment
Ulak et al. Assessment of traffic performance measures and safety based on driver age and experience: A microsimulation based analysis for an unsignalized T-intersection
Xie et al. SIV-DSS: Smart in-vehicle decision support system for driving at signalized intersections with V2I communication
Pawar et al. Response of major road drivers to aggressive maneuvering of the minor road drivers at unsignalized intersections: A driving simulator study
Khashayarfard et al. Studying the simultaneous effect of autonomous vehicles and distracted driving on safety at unsignalized intersections
Luo et al. Modeling the strategic behavior of drivers for multi-lane highway driving
Papathanasopoulou et al. Flexible car–following models for mixed traffic and weak lane–discipline conditions
Malenje et al. Vehicle yielding probability estimation model at unsignalized midblock crosswalks in Shanghai, China
Long et al. Research on Decision‐Making Behavior of Discretionary Lane‐Changing Based on Cumulative Prospect Theory
Khondaker et al. Variable speed limit strategy with anticipatory lane changing decisions
Beza et al. How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?
Li et al. Modeling driver behavior in the dilemma zone based on stochastic model predictive control
Shladover et al. Development and performance evaluation of AVCSS deployment sequences to advance from today's driving environment to full automation
Aghabayk et al. Including heavy vehicles in a car‐following model: modelling, calibrating and validating