scholarly journals LINEARIZATION OF A NONLINEAR VEHICLE MODEL

2021 ◽  
pp. 33-37
Author(s):  
Lubica Miková
Keyword(s):  
Dynamic Models ◽  
Equations Of Motion ◽  
Lateral Position ◽  
Front Wheel ◽  
Driver Assistance ◽  
Vehicle Model ◽  
Driver Assistance Systems ◽  
Nonlinear Vehicle Model ◽  
Mathematical Equations ◽  
Assistance Systems

The purpose of this article is to create a mathematical model of a vehicle using dynamic equations of motion and simulation of perturbations acting on a vehicle. It is assumed that the tire in the car model behaves linearly. Because the vehicle model is nonlinear, the model will need to be linearized in order to find the transfer function between the angle of rotation of the front wheel and the lateral position of the vehicle. For this purpose, simple dynamic models of the car were created, which reflect its lateral and longitudinal dynamics. These types of models are usually used with a linearized form of mechanical and mathematical equations that are required when designing controllers, active suspension and other driver assistance systems.

scholarly journals Detection and Tracking of Road Barrier Based on Radar and Vision Sensor Fusion

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Taeryun Kim ◽  
Bongsob Song
Keyword(s):  
Lateral Position ◽  
Vision Sensor ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Estimation Algorithms ◽  
Detection And Tracking ◽  
First Case ◽  
Lateral Distance ◽  
Assistance Systems

The detection and tracking algorithms of road barrier including tunnel and guardrail are proposed to enhance performance and reliability for driver assistance systems. Although the road barrier is one of the key features to determine a safe drivable area, it may be recognized incorrectly due to performance degradation of commercial sensors such as radar and monocular camera. Two frequent cases among many challenging problems are considered with the commercial sensors. The first case is that few tracks of radar to road barrier are detected due to material type of road barrier. The second one is inaccuracy of relative lateral position by radar, thus resulting in large variance of distance between a vehicle and road barrier. To overcome the problems, the detection and estimation algorithms of tracks corresponding to road barrier are proposed. Then, the tracking algorithm based on a probabilistic data association filter (PDAF) is used to reduce variation of lateral distance between vehicle and road barrier. Finally, the proposed algorithms are validated via field test data and their performance is compared with that of road barrier measured by lidar.

Application of Artificial Neural Networks (ANN) Based Model for Monitoring of Vehicle Longitudinal Dynamic Performance

2008 ◽  
Author(s):  
Albert Albers ◽  
Jiangang Wang ◽  
Sascha Ott ◽  
Tobias Du¨ser ◽  
Sarawut Lerspalungsanti
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Internal State ◽  
Driver Assistance ◽  
Mechatronic System ◽  
Vehicle Model ◽  
Driver Assistance Systems ◽  
Observer Model ◽  
Assistance Systems ◽  
Artificial Neural

Nowadays, with the integration of diverse driver assistance systems the vehicle has become a complex mechatronic system. The goal of this improvement is to help a driver to manage his vehicle and to perceive his environment. The functional capability of these driver assistance systems is mostly influenced by the functionality of mechanical and/or hydraulic components in the vehicle and the sensors, which are essential elements for the estimation of external and internal state of the vehicle. To ensure the reliability of the vehicle there is a great need to develop a monitoring system to meet the new requirements. In a complex mechatronic system the functionality and reliability of the whole system depend not only on those of the subsystems. To monitor the functionality of a system, it is necessary to understand how the system works. Thus it becomes more difficult for the driver to monitor the functionality and the working state of modern vehicle. In order to help a driver to monitor the performance of his/her vehicle, an appropriate condition monitoring system is required. This paper outlines an approach to estimate the vehicle longitudinal performance for the purpose of developing a fault monitoring system based on simulation technique. Firstly, the necessity of this monitoring system is expounded. After introduction of diverse methods for the analysis of the system safety, structure of this monitoring system is introduced. The kernel of this system is a vehicle model and an observer model. Regarding the requirements of a real-time operating system, the vehicle model in this work is built by applying an artificial neural network (ANN). The achieved structure of the network and simulation results are presented in this paper. Furthermore the real-time capability of the networks is verified within this work.

scholarly journals A Novel Approach to Sensorimotor Skill Acquisition Utilizing Sensory Substitution: A Driving Simulation Study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sayako Ueda ◽  
Hiroyuki Sakai ◽  
Takatsune Kumada
Keyword(s):  
Skill Acquisition ◽  
Visual Information ◽  
Driving Simulator ◽  
Lateral Position ◽  
Sensory Substitution ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistance Systems ◽  
Auditory Cueing ◽  
Lane Keeping

AbstractThe aim of this study is to demonstrate the potential of sensory substitution/augmentation (SS/A) techniques for driver assistance systems in a simulated driving environment. Using a group-comparison design, we examined lane-keeping skill acquisition in a driving simulator that can provide information regarding vehicle lateral position by changing the binaural balance of auditory white noise delivered to the driver. Consequently, lane-keeping accuracy was significantly degraded when the lower visual scene (proximal part of the road) was occluded, suggesting it conveyed critical visual information necessary for lane keeping. After 40 minutes of training with auditory cueing of vehicle lateral position, lane-keeping accuracy returned to the baseline (normal driving) level. This indicates that auditory cueing can compensate for the loss of visual information. Taken together, our data suggest that auditory cueing of vehicle lateral position is sufficient for lane-keeping skill acquisition and that SS/A techniques can potentially be used for the development of driver assistance systems, particularly for situations where immediate time-sensitive actions are required in response to rapidly changing sensory information. Although this study is the first to apply SS/A techniques to driver assistance, further studies are however required to establish the generalizability of the findings to real-world settings.

Nonlinear State Estimation of Tire-Road Contact Forces Using a 14 DoF Vehicle Model

2012 ◽  
Vol 165 ◽  
pp. 155-159 ◽  
Author(s):  
Lawrence Louis ◽  
Dieter Schramm
Keyword(s):  
Degrees Of Freedom ◽  
Stability Control ◽  
Contact Forces ◽  
Driver Assistance ◽  
Vehicle Model ◽  
Driver Assistance Systems ◽  
Roll Control ◽  
Nonlinear State Estimation ◽  
Assistance Systems ◽  
Nonlinear State

The knowledge of the wheel forces is fundamental to the development of Advanced Driver Assistance Systems (ADAS) such as Electronic Stability Control (ESC) and Anti-Roll Control (ARC). However the direct measurement of the wheel forces has been very difficult. To overcome this drawback, it has been a common practice in the industry to estimate the forces at the tire-road contact using mathematical vehicle models and estimators, especially the Extended Kalman Filter (EKF). In this contribution, the performance of the EKF is evaluated using a complete spatial model with 14 degrees of freedom.

scholarly journals Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach

2021 ◽  
Vol 13 (8) ◽  
pp. 4264
Author(s):  
Matúš Šucha ◽  
Ralf Risser ◽  
Kristýna Honzíčková
Keyword(s):  
Autonomous Vehicles ◽  
Qualitative Data ◽  
Expert Interviews ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistant Systems ◽  
Vehicle Technology ◽  
Assistance Systems ◽  
Technical Solutions ◽  
Near Future

Globally, pedestrians represent 23% of all road deaths. Many solutions to protect pedestrians are proposed; in this paper, we focus on technical solutions of the ADAS–Advanced Driver Assistance Systems–type. Concerning the interaction between drivers and pedestrians, we want to have a closer look at two aspects: how to protect pedestrians with the help of vehicle technology, and how pedestrians–but also car drivers–perceive and accept such technology. The aim of the present study was to analyze and describe the experiences, needs, and preferences of pedestrians–and drivers–in connection with ADAS, or in other words, how ADAS should work in such a way that it would protect pedestrians and make walking more relaxed. Moreover, we interviewed experts in the field in order to check if, in the near future, the needs and preferences of pedestrians and drivers can be met by new generations of ADAS. A combination of different methods, specifically, an original questionnaire, on-the-spot interviewing, and expert interviews, was used to collect data. The qualitative data was analyzed using qualitative text analysis (clustering and categorization). The questionnaire for drivers was answered by a total of 70 respondents, while a total of 60 pedestrians agreed to complete questionnaires concerning pedestrian safety. Expert interviews (five interviews) were conducted by means of personal interviews, approximately one hour in duration. We conclude that systems to protect pedestrians–to avoid collisions of cars with pedestrians–are considered useful by all groups, though with somewhat different implications. With respect to the features of such systems, the considerations are very heterogeneous, and experimentation is needed in order to develop optimal systems, but a decisive argument put forward by some of the experts is that autonomous vehicles will have to be programmed extremely defensively. Given this argument, we conclude that we will need more discussion concerning typical interaction situations in order to find solutions that allow traffic to work both smoothly and safely.

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