Evolving Model for Studying Driver-Vehicle System Performance in Longitudinal Control of Headway

1998 ◽  
Vol 1631 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Paul S. Fancher ◽  
Zevi Bareket
Keyword(s):  
Rate Of Change ◽  
Time Range ◽  
Longitudinal Control ◽  
Functional Relationships ◽  
Vehicle System ◽  
Range Rate ◽  
Evolving Model ◽  
Vehicle Dynamics Control ◽  
Parameter Values ◽  
Human Factors Research

A model for studying and evaluating the performance of drivers in controlling headway situations is currently being used to better understand how a driver’s perception of headway range and its rate of change in time (range rate) influence the performance of the driver-vehicle system in freeway driving situations. The model is based upon ideas derived from vehicle dynamics, control theory, and human factors research. It is an interpretive model in the sense that results obtained during real driving are processed to evaluate the parameter values and functional relationships used in the model. In this way, the model evolves as new data and information become available and as calculated results are interpreted and understood.

scholarly journals Analysis of the Influence of Suspension Actuator Limitations on Ride Comfort in Passenger Cars Using Model Predictive Control

Actuators ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 77 ◽  
Author(s):  
Erik Enders ◽  
Georg Burkhard ◽  
Nathan Munzinger
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Ride Comfort ◽  
Rate Of Change ◽  
High Rate ◽  
Passenger Cars ◽  
Wheel Load ◽  
Country Road ◽  
Necessary Constraints ◽  
Vehicle Dynamics Control

Active suspension systems help to deliver superior ride comfort and can be used to resolve the objective conflict between ride comfort and road-holding. Currently, there exists no method for analyzing the influence of actuator limitations, such as maximum force and maximum rate of change, on the achievable ride comfort. This research paper presents a method that is capable of doing this. It uses model predictive control to eliminate the influence of feedback controller performance and to integrate both actuator limitations and necessary constraints on dynamic wheel-load variation and suspension travel. Various scenarios are simulated, such as driving over a speed bump and inner city driving, as well as driving on a country road and motorway driving, using a state-of-the-art quarter-car model, parameterized for a luxury class vehicle. It is analyzed how comfort, or in one scenario road-holding, can be improved with consideration for the actuator limitations. The results indicate that actuator rate limitation has a strong influence on vertical vehicle dynamics control system performance, and that relatively small maximum forces of around 1000 to 2000 N are sufficient to successfully reject disturbances from road irregularities, provided the actuator is capable of supplying the forces at a sufficiently high rate of change.

Emergency Control of Vehicle Platoons: Control of Following-Law Vehicles

1976 ◽  
Vol 98 (3) ◽  
pp. 239-244 ◽  
Author(s):  
R. J. Rouse ◽  
L. L. Hoberock
Keyword(s):  
Emergency Operation ◽  
Dynamical Analysis ◽  
Normal Operation ◽  
Target Velocity ◽  
Longitudinal Control ◽  
Emergency Control ◽  
Vehicle System ◽  
Design Speed ◽  
Vehicle Platoons

This work presents a dynamical analysis of platooned following-law vehicles under longitudinal control proposed in [1]. It is shown that controller gains selected for normal operation give inadequate performance in emergency operation. Dangerous spacing in platoons moving at lower than design speed and delayed target velocity update effects are investigated. Stability of the vehicle system in emergency operation is related to controller gains, and simulations for various emergency contingencies are presented.

Longitudinal Control for a Magnetic Navigation Unmanned Electric Vehicle

2015 ◽  
Vol 734 ◽  
pp. 327-331
Author(s):  
Li Zou ◽  
Feng Luo
Keyword(s):  
Electric Vehicle ◽  
Magnetic Navigation ◽  
Test Results ◽  
Tracking Accuracy ◽  
Longitudinal Control ◽  
The Road ◽  
Speed Tracking ◽  
Smooth Switching ◽  
Vehicle Dynamics Control ◽  
Switch Strategy

This paper designs a longitudinal controller for a magnetic navigation unmanned electric vehicle to obtain desired values for speed tracking. The motion control algorithm is proposed using PID control via fuzzy logic for PID parameters online adjusting. A switch strategy is designed to guarantee the smooth switching between the drive actuator and the brake one. The vehicle is a modification of an electric sightseeing car. A simple model of a typical front drive car for vehicle dynamics control system is built to help the design of the controller. The road test results demonstrated that the longitudinal controller provided high tracking accuracy and strong robustness.

scholarly journals A nomenclature for the standard linguistic description of the kinematics of networks

2015 ◽  
Author(s):  
Jaderick P Pabico ◽  
Eliezer A Albacea
Keyword(s):  
Real World ◽  
Rate Of Change ◽  
Collaboration Network ◽  
Time Range ◽  
Linguistic Description ◽  
Friendship Relations ◽  
Computer Scientists ◽  
Twitter Users ◽  
Kinematic Properties ◽  
Over Time

The rate of change \(\partial M/\partial t\) of some metric \(M\) measured as one of the kinematic properties of a network described by a graph \(G\) transitioning from \(G(V_{t}, E_{t})\) to \(G(V_{t+\partial t}, E_{t+\partial t})\) over time range \(\partial t\) has been described in the literature with linguistic descriptions that often provide ambiguity. For example, one rate of change \((\partial M/\partial t)_{1}\) has been described as ``dynamic'' and another \((\partial M/\partial t)_{2}\) as ``highly dynamic'' but \((\partial M/\partial t)_{1}>(\partial M/\partial t)_{2}\). We propose in this paper a nomenclature for the standard linguistic description of the kinematics of networks in the hope that description in the literature will be standardized and understood with the corresponding quantitative meaning. We termed a network as ``static'' when \(\partial M/\partial t=0\), as ``non-volatile'' when \(0<\partial M/\partial t\le 1\), and as ``volatile'' when \(\partial M/\partial t>1\). In the development of the linguistic nomenclature, we borrowed heavily from the standard used in signal theory to provide linguistic descriptions to various ranges for \(\partial M/\partial t>1\). We described the kinematics of example real-world networks where the proposed nomenclature was used: (1) The collaboration network of Filipino Computer Scientists; (2) The network created from friendship relations among Batangas and Laguna Facebook users; and (3) The network created from the followed-follower relations among the top ten globally influential Twitter users.

scholarly journals A nomenclature for the standard linguistic description of the kinematics of networks

2015 ◽  
Author(s):  
Jaderick P Pabico ◽  
Eliezer A Albacea
Keyword(s):  
Real World ◽  
Rate Of Change ◽  
Collaboration Network ◽  
Time Range ◽  
Linguistic Description ◽  
Friendship Relations ◽  
Computer Scientists ◽  
Twitter Users ◽  
Kinematic Properties ◽  
Over Time

The rate of change \(\partial M/\partial t\) of some metric \(M\) measured as one of the kinematic properties of a network described by a graph \(G\) transitioning from \(G(V_{t}, E_{t})\) to \(G(V_{t+\partial t}, E_{t+\partial t})\) over time range \(\partial t\) has been described in the literature with linguistic descriptions that often provide ambiguity. For example, one rate of change \((\partial M/\partial t)_{1}\) has been described as ``dynamic'' and another \((\partial M/\partial t)_{2}\) as ``highly dynamic'' but \((\partial M/\partial t)_{1}>(\partial M/\partial t)_{2}\). We propose in this paper a nomenclature for the standard linguistic description of the kinematics of networks in the hope that description in the literature will be standardized and understood with the corresponding quantitative meaning. We termed a network as ``static'' when \(\partial M/\partial t=0\), as ``non-volatile'' when \(0<\partial M/\partial t\le 1\), and as ``volatile'' when \(\partial M/\partial t>1\). In the development of the linguistic nomenclature, we borrowed heavily from the standard used in signal theory to provide linguistic descriptions to various ranges for \(\partial M/\partial t>1\). We described the kinematics of example real-world networks where the proposed nomenclature was used: (1) The collaboration network of Filipino Computer Scientists; (2) The network created from friendship relations among Batangas and Laguna Facebook users; and (3) The network created from the followed-follower relations among the top ten globally influential Twitter users.

The Research of Self-Balancing Vehicle Based on Posture Sensor System

2014 ◽  
Vol 599-601 ◽  
pp. 735-738 ◽  
Author(s):  
Mei Xia Gao ◽  
Jian Pu Bai
Keyword(s):  
Tilt Angle ◽  
Rate Of Change ◽  
The Body ◽  
Control Circuit ◽  
Sensor System ◽  
Main Subject ◽  
Dc Motors ◽  
Vehicle System ◽  
Two Sides

The main subject of this thesis is to study a uneasily two-wheeled self-balancing vehicle system. Two tires are placed on two sides of the body parallel in this system . Controlling the rotation of two DC motors can achieve the goal of walking upright. The circuit part is mainly made up by attitude sensors parts (including Gyroscope and Accelerometer), control circuit and the driver board. Attitude sensors measure the tilt angle and the rate of change of inclination of vehicle, and then the controller calculate the responding data and finally drive two DC motors forward or backward to produce forward or backward acceleration to make the car balancing.

Reliability assessment of autonomous vehicles based on the safety control structure

2022 ◽  
pp. 1748006X2110697
Author(s):  
Feipeng Wang ◽  
Diana Filipa Araújo ◽  
Yan-Fu Li
Keyword(s):  
Autonomous Vehicles ◽  
Directed Acyclic Graph ◽  
Control Structure ◽  
Reliability Assessment ◽  
Critical Systems ◽  
Safety Control ◽  
Social Trends ◽  
Functional Relationships ◽  
Vehicle System ◽  
Market Launch

The recent social trends and accelerated technological progress culminated in the development of autonomous vehicles (AVs). Reliability assessment for AV systems is in high demand before its market launch. In safety-critical systems (SCSs) such as AV systems, the reliability concept should be broadened to consider more safety-related issues. In this paper, reliability is defined as the probability that the system performs satisfactorily for a given period of time under stated conditions. This paper proposes a reliability assessment framework of AV, consisting of three main stages: (i) modeling the safety control structure through the Systems-Theoretic Accident Model and Processes (STAMP); (ii) mapping the control structure and functional relationships to a directed acyclic graph (DAG); and (iii) construct a Bayesian network (BN) on DAG to assess the system reliability. The fully automated (level 5) vehicle system is shown as a numeric example to illustrate how this suggested framework works. A brief discussion on involving human factors in systems to analyze lower levels of automated vehicles is also included, demonstrating the need for further research on real case studies.

Functional relationships for the estimation of van Genuchten parameter values in landfill processes models

2015 ◽  
Vol 38 ◽  
pp. 222-231 ◽  
Author(s):  
Jim White ◽  
Kiriaki Zardava ◽  
Dharumarajen Nayagum ◽  
William Powrie
Keyword(s):  
Functional Relationships ◽  
Parameter Values

Learning-by-Doing versus Fully-Informing as Training Strategies

1986 ◽  
Vol 30 (14) ◽  
pp. 1443-1447 ◽  
Author(s):  
David W. Martin
Keyword(s):  
Cell Parameter ◽  
Learning By Doing ◽  
Rate Of Change ◽  
Attention Allocation ◽  
The Third ◽  
Training Technique ◽  
Point Total ◽  
Parameter Values ◽  
Laboratory Task ◽  
Allocation Strategies

A learning-by-doing training technique was compared to full-information training in both a generic laboratory task and an application setting. The generic task required trainees to search for targets in a dynamic numerical array. Cells in the array were defined by rate of change, probability of target, and cost of errors. Learning-by-doing trainees had to adopt attention allocation strategies using only running point-total feedback. Informed subjects were given cell parameter values. During training informed subjects were superior until the sixth training day. At transfer to a new, unknown parameter set learning-by-doing subjects showed a clear superiority until the third day of transfer. They had apparently learned to infer system dynamics from system feedback. This finding was not replicated in the context of a flight simulator. The failure to validate the laboratory result in the more applied setting could be due to the effects of additional dimensions and skills required for the flying task that are not included in the laboratory task.

Effects of Initial Conditions on Monte Carlo Estimates of Bias in Estimating Functional Relationships

1988 ◽  
Vol 45 (1) ◽  
pp. 185-187 ◽  
Author(s):  
Robert G. Kope
Keyword(s):  
Monte Carlo ◽  
Time Series Data ◽  
Initial Conditions ◽  
Series Data ◽  
Stock Size ◽  
Functional Relationships ◽  
Stock Recruitment ◽  
Relationship Of ◽  
Parameter Values ◽  
The Relationship

Some of the results presented by Walters (1985. Can. J. Fish. Aquat. Sci. 42: 147–149) for the magnitude of bias in estimating functional relationships from time series data resulted from his choice of initial stock size in Monte Carlo simulations rather than the dynamics of the model. Walters used the same initial stock size in each simulation while varying parameters in the stock–recruitment relationship. Starting each simulation at the equilibrium stock size or allowing initial stock size to vary randomly produces larger estimates of bias and leads to different conclusions about the relationship of bias to parameter values in the model.

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