Abstract

Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driver’s workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.

Abstract

In order to support the development process of Advanced Driver Assistance systems for road vehicles, TNO is operating a hardware-in-the-loop test setup. In this facility, called VeHIL, vehicles in the direct neighborhood of the test vehicle are simulated using wheeled mobile robots. Due to the required type of maneuvers, these robots have independently driven and steered wheels. Consequently, the robot is overactuated. Furthermore, since the robot is capable of high dynamic maneuvers, slip effects caused by the tires can play an important role. A position controller based on feedback linearization is presented, using the so-called multicycle approach which regards the robot as a set of independent unicycles. As a result, the wheeled mobile robot is position controlled while each unicycle is controlled taking weight transfer as well as longitudinal and lateral tire slip into account. © 2008 IEEE.

Abstract

We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The importance sampling pdf is estimated by a kernel density estimate, based on the results from the previous iteration. The concept is illustrated with a simple adaptive cruise control problem.

Abstract

Research reveals that visual information forms the major portion of the received data for driving. At night -owing to the, sometimes scarcity, sometime inhomogeneity of light- the human physiology and psychology experiences a dramatic alteration. It is found that although the likelihood of accident occurrence is higher during the day due to heavier traffic, the most fatal accidents still occur during night time. How can road safety be improved in limited lighting conditions using DMD-based high resolution headlamps? DMD-based pixel light systems, utilizing HID and LED light sources, are able to address hundreds of thousands of pixels individually. Using camera information, this capability allows 'glare-free' light distributions that perfectly adapt to the needs of all road users. What really enables these systems to stand out however, is their on-road image projection capability. This projection functionality may be used in co-operation with other driver assistance systems as an assist feature for the projection of navigation data, warning signs, car status information etc. Since contrast sensitivity constitutes a decisive measure of the human visual function, here is then a core question: what distributions of luminance in the projection space produce highly visible on-road image projections? This work seeks to address this question. Responses on sets of differently illuminated projections are collected from a group of participants and later interpreted using statistical data obtained using a luminance camera. Some aspects regarding the correlation between contrast ratio, symbol form and attention capture are also discussed.

Abstract

Various neurological disorders, like Parkinson's disease, Multiple Sclerosis, Huntington's disease and Stroke, affect millions of people worldwide. Tremor that is a result of these disorders affects the performance of many Activities of Daily Living such as dressing, bathing, self-care, and writing, which reduces the functional independence and self-rated quality of life. Standardized rating scales have been developed, however, these scales display some degree of variability due to their subjective/qualitative approach. Therefore, the accurate and objective measure of a patient's condition is crucial. Due to the lack of objectivity and accuracy from conventional procedures, there is a need to develop an objective evaluation system. In this work, a horizontal movement test is implemented in a Virtual Environment with the use of a Haptic Interface. The proposed test consists of a simple reaching task (more tasks are under development) for defining quantitative metrics. Wrist motion is accurately measured using the haptic interface and analyzed to calculate evaluation metrics based on the joint energy and spatial deviation from the ideal path. To improve the sensitivity of the metrics, a harmonic disturbance force is applied by the haptic interface to the user. The disturbance frequency is varied from 1 to 7 Hz and the duration of the movement is constraint to be constant. Fourteen healthy adults performed the experiments with 10 to 21 repetitions for each movement conditions. The results show that all users spend higher energy to complete the test at frequencies around 2.5 Hz. The statistical analysis indicates that energy is a reliable evaluation metric, with low variance, that can be used to quantify upper extremities. Copyright © 2017 ASME. 1

Abstract

Date of Conference: 11–13 October 2017 Conference Name: ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 Model reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop settings, MRAC may cause unstable system trajectories. Basing on our recent work on the stability of MRAC-human dynamics, here we follow an optimization based computations to design a linear filter and study whether or not this filter inserted between the human model and MRAC could help remove such instabilities, and potentially improve performance. To this end, we present a mathematical approach to study how the error dynamics of MRAC could favorably or detrimentally influence human operator's error dynamics in performing a certain task. An illustrative numerical example concludes the study.

Abstract

Image Processing (IP) applications have become popular with the advent of efficient algorithms and low-cost CMOS cameras with high resolution. However, IP applications are compute-intensive, consume a lot of energy and have long processing times. Image approximation has been proposed by recent works for an energy-efficient design of these applications. It also reduces the impact of long processing times. The challenge here is that the IP applications often work as a part of bigger closed-loop control systems, e.g. advanced driver assistance system (ADAS). The impact of image approximations that tolerate certain error on these image-based control (IBC) systems is very important. However, there is a lack of tool support to evaluate the performance of such closed-loop IBC systems when the IP is approximated. We propose a framework - for both software-in-the-loop (SiL) and hardware-in-the-loop (HiL) simulation - for performance evaluation of image approximation on a closed-loop automotive IBC system (IMACS). Both simulation setups model the 3D environment in 3ds Max, and simulate the system dynamics, camera position and environment in V-REP. Our SiL setup simulates the system software in C++ or Matlab. Here, V-REP runs as a server and the software as a client in synchronous mode. Our HiL simulation setup runs the system software in the NVIDIA Drive PX2 platform and communicates to V-REP using application programming interfaces (APIs) for synchronous execution. We show the effectiveness of our framework using a vision-based lateral control example.

Abstract

Date of Conference: 11–13 October 2017 Conference Name: ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 The paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies.

Abstract

This paper presents a microscopic traffic model for the validation of advanced driver assistance systems. This model describes single-lane traffic and is calibrated with data from a field operational test. To illustrate the use of the model, a Monte Carlo simulation of single-lane traffic scenarios is executed with application to cooperative adaptive cruise control system. The model is then validated by comparing the simulation results with data gathered from test drives. ©2007 IEEE.