Masha Maltz

Effects of an In-Vehicle Collision Avoidance Warning System on Short- and Long-Term Driving Performance

Many new in-vehicle systems focus on accident prevention by facilitating the driving task. One such driving aid is an in-vehicle collision avoidance warning system (IVCAWS), used to alert the driver to an impending collision. Our study evaluated the effects of an imperfect IVCAWS both on driver headway maintenance and on driver behavior in response to warning system errors. Our results showed that drivers tend to overestimate their headway and consequently drive with short and potentially dangerous headways, and that IVCAWSs are a useful tool for educating drivers to stimate headway more accurately. Moreover, our study showed that after a relatively short exposure to the system, drivers were able to maintain longer and safer headways for at least six months. The practical implications of these results are that the use of an IVCAWS should be considered for inclusion in driver education and training programs.

Imperfect in-vehicle collision avoidance warning systems can aid drivers

An experiment was conducted to determine the effects of an in-vehicle collision avoidance warning system (IVCAWS) on driver performance. A driving simulator was driven by 135 licensed drivers. Of these, 120 received alerts from the IVCAWS when their headway to a lead car was less than 2s, and the other 15 (the control group) received no alerts. Drivers received varied alert interfaces: auditory, visual, and multimodal. The system had varied levels of reliability, determined by both false alarm rate and failure of the IVCAWS to alert to short headway. Results indicated that the IVCAWS led to safer (longer) headway maintenance. High false alarm rates induced drivers to slow down unnecessarily; large numbers of missed alerts did not have any significant impact on drivers. Driver acceptance of the system was mixed. Interface played a role in driver reliance on the system, with the multimodal interfaces generating least reliance. Actual or potential applications of this research include IVCAWS interface selection for greater system efficacy and user acceptance and the advisability of implementation, even of imperfect systems, for drivers who seek to maintain a safer headway.

New Alternative Methods of Analyzing Human Behavior in Cued Target Acquisition

Target acquisition tasks in natural environments are often augmented by cuing systems that advise human observers during the decision process. With present technological limitations, cuing systems are imperfect, so the question arises whether cuing aids should be implemented under all conditions. We examined target acquisition performance under different levels of task complexity and cuing system reliability. We introduce here two new methods to help define observer behavior trends in cued target acquisition: a quantitative measure of observer search behavior in a temporal sense and a measure of the extent of observer reliance on the cue. We found that observer reliance on the cue correlated with task difficulty and the perceived reliability of the cue. Cuing was generally helpful in complex tasks, whereas cuing reduced performance in easy tasks. Consequently, cuing systems should be implemented only when the task is difficult enough to warrant the intrusion of a cue into the task. Actual or potential applications of this research include the design and implementation of imperfect automated aids dealing with augmented reality

Effects of an Encoding Scheme on Perceived Video Quality Transmitted Over Lossy Internet Protocol Networks

We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP network with a quality of service mechanism. The parameters of the encoding schemes include the transmission bit rate, the compression depth, the frame size and the frame rate. We demonstrate that when jointly considering the impact of the coding bit rate, the packet loss ratio and the video characteristics, we can identify an optimal encoding scheme that maximizes viewer-perceived quality. The video content, the compression and the transmission are represented by a vector X which contains d parameters. Based on subjective tests, we obtain a set of observation pairs of labeled samples Pi = {Xi, Qi} , where Qi is the quality class related to the vector of input parameters Xi. To determine the significance of these results, we use the analysis of variance (ANOVA) statistical method, which identifies those factors that cause differences in the averages in the subjective tests results, and determines the significance of the results. Finally, we introduce a novel method to predict an optimal encoding scheme based on canonical discriminant analysis (CDA) for feature classification.

Relative effects of distortion and noise on target acquisition: the advisability of image restoration

Any image acquired by optical, electro-optical, or electronic means is likely to be degraded by the environment. The resolution of the acquired image depends on the total modulation transfer function (MTF) of the system and the additive noise. Image restoration techniques can improve image resolution significantly; however, as the noise increases, improvements via image processing become more limited because im- age restoration increases the noise level in the image. We characterize the influence of the MTF and noise level on human target acquisition probability to ascertain the advantages, if any, of image restoration. Con- ditions when restoration would be advisable are determined.

DRIVER PERFORMANCE WITH A COLLISION AVOIDANCE SYSTEM

Intelligent transportation systems (ITS) have enhanced the way we can deal with road safety issues. Unlike in-vehicle safety systems such as air bags and safety belts that focus on injury reduction, many new in-vehicle systems are now focused on accident prevention by providing assistance to the driver during the driving task. One such driving aid is a warning system to alert the driver to an impending collision. Our study evaluated the effects of imperfect warning collision alarms on driver behavior. Results showed that drivers tend to overestimate their headway, and that systems that alert drivers to unsafe temporal headways are useful in teaching drivers to estimate headway more accurately. Subjects responded properly to the warnings, both under conditions of true and of false alarms.

Cue Utilization in a Visually Demanding Task

Modern technologies make it possible to provide operators who perform visually demanding tasks with devices that help them in the performance of these tasks. Relatively little is known about the adaptive changes that occur in operators’ reliance on such devices as a function of their validity. In our study, participants performed a task with high visual demands in which aid was offered in the form of cues that could potentially ease the workload drastically. The experimental conditions differed in the validity of the cues. Participants either received invalid, moderately valid, or highly valid cues, or no cues in the control condition. We were mainly interested in the adaptive changes over time in the reliance on the cues.

Decision modeling for a target acquisition task

In most applications of target detection electro-optical systems, the man-in-the-loop plays a crucial part in the performance of the system. If one were dealing with an automatic target acquisition system, a great deal of effort would justifiably be invested in calculating the threshold for determining a target for optimum system performance. When the system is human-operated, understanding the decisionmaking process of the human observer is of major importance to the successful performance of the system.

Multispectral image fusion for target detection

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Effects of the Eencoding Scheme on the Perceived Compressed Video Quality Transmitted Over Lossy IP Networks

In this paper we analyze the viewer-perceived quality of a compressed video stream, which is transmitted over a lossy IP network with QoS (quality of service) mechanism. We demonstrate that when jointly considering the impact of coding bit rate, packet loss ratio and video characteristics, there is an optimal encoding scheme, which maximizes the viewer-perceived quality. The video content, the compression and the transmission are represented in a vector X of d parameters. Based on the subjective tests, we obtain a set of observation pairs of labeled samples Pi = {Xi ,Qi}, where Qi is the quality class related to the vector of input parameters Xi. We introduce a novel method to predict the optimal encoding scheme based on canonical discriminant analysis (CDA) for feature classification.