This thesis addresses the problem of road intersection safety with regard to a mixed population of automated vehicles and non-automated road users. The work derives and evaluates safety-critical scenarios at road junctions, which can pose a particular safety problem involving automated cars. A simulation and evaluation framework for car-to-car accidents is presented and demonstrated, which allows examining the safety performance of automated driving systems within those scenarios. Given the recent advancements in automated driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual testing environments or on real-world test tracks. Since it is unrealistic to cover all possible combinations of traffic situations and environment conditions, the challenge is to find the key driving situations to be evaluated at junctions. Against this background, a novel method to derive critical pre-crash scenarios from historical car accident data is presented. It employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1,056 junction crashes in the UK, which were exported from the in-depth On-the-Spot database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions. As a follow-up to the scenario generation, the thesis further presents a novel, modular framework to transfer the derived collision scenarios to a sub-microscopic traffic simulation environment. The software CarMaker is used with MATLAB/Simulink to simulate realistic models of vehicles, sensors and road environments and is combined with an advanced Monte Carlo method to obtain a representative set of parameter combinations. The analysis of different safety performance indicators computed from the simulation outputs reveals collision and near-miss probabilities for selected scenarios. The usefulness and applicability of the simulation and evaluation framework is demonstrated for a selected junction scenario, where the safety performance of different in-vehicle collision avoidance systems is studied. The results show that the number of collisions and conflicts were reduced to a tenth when adding a crossing and turning assistant to a basic forward collision avoidance system. Due to its modular architecture, the presented framework can be adapted to the individual needs of future users and may be enhanced with customised simulation models. Ultimately, the thesis leads to more efficient workflows when virtually testing automated driving at intersections, as a complement to field operational tests on public roads.

Use of cellular phones while driving, and safety implications thereof, has captured public and scientific interest. Previous research has shown that driver reactions and attention are impacted by cellular phone use. Generally, previous research studies have not focused on how visual attention and driver performance may interact. Strayer and colleagues found lower recognition for items present in the driving environment when drivers were using a cellular phone than when not using the phone; however, the tested items were not directly relevant to driving. Relevance to driving may have an impact on attention allocation. The current project used a mediumidelity driving simulator to extend previous research in two ways: 1) how attention is allocated across driving-relevant and -irrelevant items in the environment was investigated, and 2) driving performance measures and eye movement measures were considered together rather than in isolation to better illustrate the impact of cellular phone distraction on driver behavior. Results from driving performance measures replicated previous findings that vehicle control is negatively impacted by driver distraction. Interestingly, there were no interactions of relevance and distraction found, suggesting that participants responded to potential hazards similarly in driving-only and distraction conditions. In contrast to previous research, eye movement patterns (primarily measured by number of gazes) were impacted by distraction. Gaze patterns differed across relevance levels, with hazards receiving the most gazes, and signs receiving the fewest. The relative size of the critical items may have impacted gaze probability in this relatively undemanding driving environment. In contrast to the driving performance measures, the eye movement measures did show an interaction between distraction and relevance; thus, eye movements may be a more direct and more sensitive measure of driver attention. Recognition memory results were consistently near chance performance levels and did not reflect the patterns found in the eye movement or driving performance measures.

No description available.

Previous studies have shown that the experience of negative emotions is rarer, while experience of positive emotions is more frequent in the elderly, suggesting an overall improvement in emotional well-being as people age. However, most research did not account for the dynamic characteristics of emotions (e.g. peak intensity, latency, duration) and the levels of emotional challenges. In addition, since most previous studies have focused on studying the experience, expression, and psychophysiological response of emotion, it is still not fully understood how performance in cognitive or behavioral tasks (e.g., automobile driving) can be affected by emotions in older age. To address this gap, the current study examined the effect of normal aging on the dynamic processes of emotion during different levels of emotional challenge (aim 1), and the effect of emotion on driving in older adults as compared to middle-aged adults (aim 2). Parkinson’s disease (PD) is an age-related neurodegenerative disease that shares similar pathological characteristics with the process of normal aging (i.e., reduced dopamine), but to a much higher degree. In addition to investigating the effect of normal aging, the current study also examined the effect of “abnormal aging” on emotion and driving using PD as a model (aim 3). Participants included 16 older (65 - 79 years old), 16 middle-aged (38 - 55 years old) neurologically normal adults, and 16 patients with mild PD (56 - 80 years old). This study focused on fear and anger, the two negative emotions that are most likely to be elicited by driving experiences and to disrupt driving behaviors. Low-level and high-level fear and anger challenges were created using simulated driving scenarios: 1) Low fear task, participants drove in fog and frequently encountered static obstacles on the road; 2) High fear task, participants drove at nighttime and frequently encountered deer running across the road; 3) Low anger task, participants drove following a slow-moving vehicle; 4) High anger task, participants followed a slow vehicle and were honked at by a tailgating vehicle. Participants rated the intensity of fear and anger experiences at 1- minute intervals when they were driving. Comparing older adults against middle-aged adults, it was found that 1) fear intensity was lower in older adults in the low fear task. In contrast, latency and duration of fear were similar between groups in both fear tasks. 2) Anger intensity was lower in older adults in both anger tasks. Anger latency and duration were similar between groups in the high anger task, but anger took longer to develop and was of shorter duration in older adults in the low anger task. 3) In the low fear task, older adults exhibited more cautious driving behaviors (e.g., more frequent uses of brake). In the high anger task older adults were less able to control the acceleration and brake pedals smoothly (e.g., higher forces for brake and acceleration). These results suggest that age differences in the dynamic processes of emotion and the effect of emotion on driving may depend on the type of emotion and level of emotional challenge. When comparing PD patients against age- and education-matched neurologically normal participants (n = 18), it was found that the PD patients reported experiencing similar degrees of fear and anger as the normal comparisons. However, in the high fear task PD patients were less responsive to deer running across the road (e.g., mean and variation of force for brake was lower in PD patients). This finding suggests an impaired ability in PD patients to respond to the sudden appearance of driving hazards. Collectively, the findings of this study provide a window into how the moment-to-moment experience of negative emotions in response to environmental challenges may contribute to the overall emotional well-being of older adults. They also suggest that both the type of emotion and the level of challenge may be important factors in determining the experience of emotion and the effect of emotion on driving during “normal” and “abnormal” aging.

The topic of this dissertation was the use of distributed computing to improve the modeling of the interaction between passenger cars and trucks. The two main focus areas were the development of a methodology to combine microscopic traffic simulation programs with driving simulator programs, and the application of a prototype distributed traffic simulation to study the impact of the length of an impeding vehicle on passing behavior. The methodology was motivated by the need to provide an easier way to create calibrated traffic flows in driving simulations and to capture vehicle behavior within microscopic traffic simulations. The original design for the prototype was to establish a two-way, real time exchange of vehicle data, however problems were encountered that imposed limitations on its development and use. The passing study was motivated by the possible changes in federal truck size and weight regulations and the current inconsistency between the passing sight distance criteria for the design of two lane highways and the marking of no-passing zones. Test drivers made passing maneuvers around impeding vehicles that differed in length and speed. The main effects of the impeding vehicle length were found to be significant for the time and distance in the left lane, and the start and end gap distances. Passing equations were formulated based on the mechanics of the passing maneuver and included behavior variables for calibration. Through a sensitivity analysis, it was shown that increases in vehicle speeds, vehicle length, and gap distance increased the distance traveled in the left lane, while increases in the speed difference and speed gain decreased the distance traveled in the left lane. The passing equations were calibrated using the current AASHTO values and used to predict the impact of increased vehicle lengths on the time and distance in the left lane. The passing equations are valuable for evaluating passing sight distance criteria and observed passing behavior.

The multiple object tracking task (Pylyshyn and Storm, 1988) has long been a standard tool for use in understanding how we attend to multiple moving points in the visual field. In the current experiments, it is first demonstrated that this classical task can be adapted for use in a simulated driving environment, where it is commonly thought to apply. Standard requirements of driving (steering, maintaining headway) are shown to reduce tracking ability. Subsequent experiments (2a, 2b, 2c) investigate the way in which participants respond to events at target and distractor locations, and have bearing on Pylyshyn’s (1989) “indexing” hypothesis. The final experiment investigates the effect of the colour-composition of the tracking set on performance, and may have implications for our theoretical understanding of how tracking is performed. / AUTO21, NSERC, CANDrive

BACKGROUND- Motor vehicle crashes pose a serious public health problem. Many serious crashes are due to faulty driving by unfit operators, including several categories of neurological patients. Unfortunately, there seems to be little agreement among health professionals, driving experts, and state government on how to advise these individuals. REVIEW SUMMARY- This article reviews the question of driving in neurological patients. Decisions on driver fitness should be based on empirical observations of performance and not on criteria of age or medical diagnosis, which alone are unreliable predictors. Relevant data can be collected either on a road test or off-road, using different probes of vision and cognition, in the setting of a Department of Motor Vehicles office or medical clinic. The use of a driving simulator is also feasible. The predictive value of these performance assessments is a topic of active research. CONCLUSION- Understanding how performance data from off-road and on-road observations correlate with real-life crash risk is a key step toward developing safe, fair, and accurate means of predicting driver fitness. One potential benefit is the prevention of injury, and another is the preservation of mobility and independence of individuals whose licenses are being unduly revoked because of old age or illness.

Geo-specific road database development is important to a driving simulation system and a very labor intensive process. Road databases for driving simulation need high resolution and accuracy. Even though commercial software is available on the market, a lot of manual work still has to be done when the road crosssectional profile is not uniform. This research deals with geo-specific road databases development, especially for roads with non-uniform cross sections. In this research, the United States Geographical Survey (USGS) road information is used with aerial photos to accurately extract road boundaries, using image segmentation and data compression techniques. Image segmentation plays an important role in extracting road boundary information. There are numerous methods developed for image segmentation. Six methods have been tried for the purpose of road image segmentation. The major problems with road segmentation are due to the large variety of road appearances and the many linear features in roads. A method that does not require a database of sample images is desired. Furthermore, this method should be able to handle the complexity of road appearances. The proposed method for road segmentation is based on the mean-shift clustering algorithm and it yields a high accuracy. In the phase of building road databases and visual databases based on road segmentation results, the Linde-Buzo-Gray (LBG) vector quantization algorithm is used to identify repeatable cross section profiles. In the phase of texture mapping, five major uniform textures are considered - pavement, white marker, yellow marker, concrete and grass. They are automatically mapped to polygons. In the chapter of results, snapshots of road/visual database are presented.

This dissertation presents two studies examining the interaction between workload history and driver mental workload. The first experiment focuses on testing for the presence of a hysteresis effect in the driving task. The second experiment examines the proposition that cueing impending periods of higher task demand can reduce the impact of any such potential hysteresis effects. Thirty-two licensed drivers served as participants and all served in both studies. Using the directions provided by a Heads-Up-Display navigation system, participants followed a pre-set route in the simulated environment. At specified points within the drive, the navigation system would purposefully fail which required drivers to relay a ten digit alphanumeric error code to a remote operator in order to reset the system. Results indicated that this increase in task demand from the navigation system's failure leads to a significant increase in perceived mental workload as compared to pre-failure periods. This increase in driver mental workload was not significantly reduced by the time the drive ended, indicating the presence of a hysteresis effect. In the second experiment, the navigation system provided a completely reliable visual warning before failure. Results indicate that cueing had neither an effect on perceived mental workload, nor any ameliorating effect on the hysteretic type effect seen in mental workload recovery. The conclusion of these findings being that the overall safety and efficiency of the surface transportation system would likely improve by designs which accommodate the periods immediately following a reduction in stress. Whether from leaving high demand areas such as work zones or in the period immediately after using a in-car information device such as a GPS or a cell phone, these post-high workload periods are associated with increased variability in driver inputs and levels of mental workload.

Cette thèse vise à avoir une meilleure compréhension des mécanismes qui sous-tendent la perception visuelle spatiale, et plus particulièrement la perception de la distance égocentrique. Nous cherchons à déterminer les raisons qui font que la distance égocentrique est, en général, sous-estimée lorsque l’observateur est placé dans un dispositif de réalité virtuelle par rapport au monde réel. Dans une première étude, nous montrons que la présence d’indice visuels liés à la parallaxe du mouvement de la tête impacte le comportement de suivi de véhicule des conducteurs en simulateur de conduite de manière différente selon qu’elle est couplée à une vision stéréoscopique ou non. Dans la seconde étude, nous montrons que l’étude de la variabilité interpersonnelle peut se révéler très informative et conduit à penser que le phénomène de sous-estimation de la distance en réalité virtuelle n’est pas généralisable à tous les participants. Dans la troisième étude, par le biais d’un modèle d’identification de facteur de gains, nous proposons une méthode afin de distinguer l’effet des erreurs de perceptions de distance égocentrique de celui des erreurs de perception de la distance parcourue. Les résultats de ces études montrent que la variabilité inter-individuelle doit être prise en compte dans l’évaluation de la perception spatiale. Ils apportent de plus des éléments de preuve en faveur d’une utilisation de différents référentiels spatiaux dépendant de la tâche demandée et pouvant varier significativement d’un individu à l’autre. Ces résultats sont à prendre en compte dès lors qu’on cherche à généraliser au monde réel les résultats d’études effectuées grâce à la réalité virtuelle. / This thesis aims to better understand the mechanisms that underlie spatial visual perception, and more particularly the perception of egocentric distance. We seek to determine the reasons that egocentric distance is, in general, underestimated when the observer is placed in a virtual reality device in relation to the real world. In a first study, we show that the presence of visual cues related to the head motion parallax impacts the drivers behavior in driving simulator differently depending on whether it is coupled to a stereoscopic vision or not. In the second study, we show that the analyse of interpersonal variability can be very informative and leads us to believe that the phenomenon of underestimation of distance in virtual reality is not generalizable to all participants. In the third study, using a gain factor identification model, we propose a method to distinguish the effect of egocentric distance perceptual errors from the perception of distance traveled. The results of these studies show that inter-individual variability must be taken into account in the evaluation of spatial perception. In addition, its provide evidence for the use of different spatial referenceframe that depend on the task requested and can vary significantly from one individual to another. These results are to be taken into account when one seeks to generalize to the real world the results of studies carried out thanks to the virtual reality.