A New Lane Departure Warning Algorithm Considering the Driver’s Behavior Characteristics

In order to meet the driving safety warning required for different driver types and situations, a new lane departure warning (LDW) algorithm was proposed. Its adaptability is much better through setting the different thresholds of time to lane crossing (TLC) using fuzzy control method for driver with different driving behaviors in different lanes and different vehicle movements. To ensure the accuracy of computation of TLC under the different actual driving scenarios, the algorithm was established based on vehicle kinematics and advanced mathematics compared to other ways of computation of TLC. On this basis, a LDW strategy determining driver's intentions was presented by introducing identifying vehicle movements. Finally, a vast quantity of the real vehicle experiments was given to demonstrate the effectiveness of the proposed LDW algorithm. The results of the tests show that the algorithm can decrease false alarm rate effectively because of distinguishing from unconscious by real-time vehicle movements, and promote the adaptability to the driver behavior characteristics, so it has favorable driver acceptance and strong intelligence

A Driving Risk Surrogate and Its Application in Car-Following Scenario at Expressway

Traffic safety is important in reducing death and building a harmonious society. In addition to studies of accident incidences, the perception of driving risk is significant in guiding the implementation of appropriate driving countermeasures. Risk assessment can be conducted in real-time for traffic safety due to the rapid development of communication technology and computing capabilities. This paper aims at the problems of difficult calibration and inconsistent thresholds in the existing risk assessment methods. It proposes a risk assessment model based on the potential field to quantify the driving risk of vehicles. Firstly, virtual energy is proposed as an attribute considering vehicle sizes and velocity. Secondly, the driving risk surrogate(DRS) is proposed based on potential field theory to describe the risk degree of vehicles. Risk factors are quantified by establishing submodels, including an interactive vehicle risk surrogate, a restrictions risk surrogate, and a speed risk surrogate. To unify the risk threshold, acceleration for implementation guidance is derived from the risk field strength. Finally, a naturalistic driving dataset in Nanjing, China, is selected, and 3063 pairs of following naturalistic trajectories are screened out. Based on that, the proposed model and other models use for comparisons are calibrated through the improved particle optimization algorithm. Simulations prove that the proposed model performs better than other algorithms in risk perception and response, car-following trajectory, and velocity estimation. In addition, the proposed model exhibits better car-following ability than existing car-following models

Advanced driver assistance systems information management and presentation

With the development of advanced driving assistance systems, in-vehicle communication and information systems, there are situations where the driver becomes overloaded by information, creating potentially dangerous conditions. In this Thesis a novel strategy is proposed, to prioritise and present information. Firstly two main criteria are extracted, that allow the ability to rank messages: the risk associated with the non-presentation of the message, and its relevance to the environment. Fuzzy cognitive maps enable to represent expert knowledge and model these relationships. Secondly, a strategy to present information is proposed. Using an importance index, calculated from the previous risk and relevance indices, but also information nature, time constraints and access frequency, a set of best interfaces is selected. Furthermore design a model of driver workload is designed, based on the multiple resources theory. By estimating in real time the workload of the driver, the system enables to choose an optimal interface, that should prevent overload. This Thesis presents then the tools developed for the implementation and testing of the model. A video capture and data transfer program, based on the IEEE-1394 bus, enable in-vehicle real-time data capture and collection. Moreover, a software package for replay of the acquired data, analysis and simulation is developed. Finally, the implementation of the prioritisation and presentation strategy is outlined. The last part of this work is dedicated to the experiments and results. Using an experimental vehicle, data in different driving conditions are collected. the experiment is completed by creating data to simulate potentially dangerous situations, where driver is overloaded with information. The results show that the information management and presentation system is able to prevent overload in most conditions. Its structure and design allow to incorporate expert knowledge to refine the classification.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Methods for Utilizing Connected Vehicle Data in Support of Traffic Bottleneck Management

The decision to select the best Intelligent Transportation System (ITS) technologies from available options has always been a challenging task. The availability of connected vehicle/automated vehicle (CV/AV) technologies in the near future is expected to add to the complexity of the ITS investment decision-making process. The goal of this research is to develop a multi-criteria decision-making analysis (MCDA) framework to support traffic agencies’ decision-making process with consideration of CV/AV technologies. The decision to select between technology alternatives is based on identified performance measures and criteria, and constraints associated with each technology. Methods inspired by the literature were developed for incident/bottleneck detection and back-of-queue (BOQ) estimation and warning based on connected vehicle (CV) technologies. The mobility benefits of incident/bottleneck detection with different technologies were assessed using microscopic simulation. The performance of technology alternatives was assessed using simulated CV and traffic detector data in a microscopic simulation environment to be used in the proposed MCDA method for the purpose of alternative selection. In addition to assessing performance measures, there are a number of constraints and risks that need to be assessed in the alternative selection process. Traditional alternative analyses based on deterministic return on investment analysis are unable to capture the risks and uncertainties associated with the investment problem. This research utilizes a combination of a stochastic return on investment and a multi-criteria decision analysis method referred to as the Analytical Hierarchy Process (AHP) to select between ITS deployment alternatives considering emerging technologies. The approach is applied to an ITS investment case study to support freeway bottleneck management. The results of this dissertation indicate that utilizing CV data for freeway segments is significantly more cost-effective than using point detectors in detecting incidents and providing travel time estimates one year after CV technology becomes mandatory for all new vehicles and for corridors with moderate to heavy traffic. However, for corridors with light, there is a probability of CV deployment not being effective in the first few years due to low measurement reliability of travel times and high latency of incident detection, associated with smaller sample sizes of the collected data

Development of rear-end collision avoidance in automobiles

The goal of this work is to develop a Rear-End Collision Avoidance System for automobiles. In order to develop the Rear-end Collision Avoidance System, it is stated that the most important difference from the old practice is the fact that new design approach attempts to completely avoid collision instead of minimizing the damage by over-designing cars. Rear-end collisions are the third highest cause of multiple vehicle fatalities in the U.S. Their cause seems to be a result of poor driver awareness and communication. For example, car brake lights illuminate exactly the same whether the car is slowing, stopping or the driver is simply resting his foot on the pedal. In the development of Rear-End Collision Avoidance System (RECAS), a thorough review of hardware, software, driver/human factors, and current rear-end collision avoidance systems are included. Key sensor technologies are identified and reviewed in an attempt to ease the design effort. The characteristics and capabilities of alternative and emerging sensor technologies are also described and their performance compared. In designing a RECAS the first component is to monitor the distance and speed of the car ahead. If an unsafe condition is detected a warning is issued and the vehicle is decelerated (if necessary). The second component in the design effort utilizes the illumination of independent segments of brake lights corresponding to the stopping condition of the car. This communicates the stopping intensity to the following driver. The RECAS is designed the using the LabVIEW software. The simulation is designed to meet several criteria: System warnings should result in a minimum load on driver attention, and the system should also perform well in a variety of driving conditions. In order to illustrate and test the proposed RECAS methods, a Java program has been developed. This simulation animates a multi-car, multi-lane highway environment where car speeds are assigned randomly, and the proposed RECAS approaches demonstrate rear-end collision avoidance successfully. The Java simulation is an applet, which is easily accessible through the World Wide Web and also can be tested for different angles of the sensor

Nutzerorientierte Gestaltung haptischer Signale in der Lenkung: Zum Einsatz direktionaler Lenkradvibrationen in Fahrerassistenzsystemen

Die vorliegende Arbeit widmet sich dem Einsatz von Lenkradvibrationen zur Informationsübermittlung an der Schnittstelle zwischen Fahrzeug und Fahrer unter Berücksichtigung physiologischer und psychologischer Aspekte. Als besondere Eigenschaft wird die Möglichkeit zur Erzeugung örtlich aufgelöster Vibrationen erkannt. Damit ist es möglich, über einseitige Lenkradvibrationen Richtungsinformationen an Fahrer zu kommunizieren. In drei Hauptstudien werden mit insgesamt 150 Probanden verschiedene Aspekte der Fahrerreaktion auf einseitige Lenkradvibrationen untersucht. Zunächst wird in einem grundlegenden Laborexperiment die intuitive Reaktion auf einseitige Lenkradvibrationen ermittelt. Im Anschluss wird die subjektive Präferenz der einseitigen Lenkradvibration in der Anwendung als Spurverlassenswarnsignal nachgewiesen. Zuletzt wird der Versuch unternommen, die einseitige Lenkradvibration zur Initiierung einer Ausweichreaktion in einer drohenden Frontalkollisionssituation einzusetzen.In this work applications of steering wheel vibrations are discussed. Tactile excitations that are perceived with mechanosensors in the skin of the human palm are explicitly focussed to differentiate from the state of the art. Because of the compatibility of the location of stimulus and response, haptic signals at the steering wheel are advantageously utilized to influence lateral vehicle guidance. The thesis summarizes findings of the psychophysical perception of tactile steering wheel vibrations and supplements these findings with new insights on the effect of variations in specific stimulus parameters on the perceived intensity and interpretation of messages transfered by vibrations at the steering wheel. A peculiar feature of vibro-tactile stimulation is the possibility to produce spatially distributed vibrations, which allows for communication of information on direction to the driver. Based on a review of the literature, a subjective preference of lane departure warning signals relying on vibro-tactile excitation and comprising information on directionality is hypothesized. This thesis therefore focusses on single-sided steering wheel vibrations. A single-sided vibro-tactile stimulation is assumed to be semantically associated with the rumble phenomenon induced in case of lane deparuture, thus facilitating the interpretation of the warning signal and leading to an enhancement of driver reactions when utilized as a lane departure warning signal. Three main studies examining a total of 150 subjects were conducted to reveal specific aspects of driver reactions towards single-sided steering wheel vibrations. First of all, a fundamental laboratory study examined intuitive reactions on single-sided steering wheel vibrations, legitimizing the stimulus-response mapping necessary to utilize this kind of signal as a lane departure warning signal. The second study confirmed the subjective predominance of the single-sided vibration as a lane departure warning signal when comparing this signal to alternative haptic warning signals at the steering wheel that were previously optimized for this application. In a final step, the third study examined the possible application of the single-sided steering wheel vibration to initiate an evasive steering reaction in case of an imminent forward collision situation Based on the results of the experimental studies conducted in this work, the utilization of the single-sided steering wheel vibration as a lane departure warning signal is strongly recommended. The signal both transfers the reason for the warning and recommends an action in a discrete and unintrusive manner. Any further application of the single-sided vibration, particularly the advice on a steering reaction in a collision situation, which was originally favored, can not be supported based on the present work

Driver drowsiness monitoring using eye movement features derived from electrooculography

The increase in vehicle accidents due to the driver drowsiness over the last years highlights the need for developing reliable drowsiness assistant systems by a reference drowsiness measure. Therefore, the thesis at hand is aimed at classifying the driver vigilance state based on eye movements using electrooculography (EOG). In order to give an insight into the states of driving, which lead to critical safety situations, first, driver drowsiness, distraction and different terminologies in this context are described. Afterwards, countermeasures as techniques for keeping a driver awake and consequently preventing car crashes are reviewed. Since countermeasures do not have a long-lasting effect on the driver vigilance, intelligent driver drowsiness detection systems are needed. In the recent past, such systems have been developed on the market, some of which are introduced in this study. As also stated in previous studies, driver state is quantifiable by objective and subjective measures. The objective measures monitor the driver either directly or indirectly. For indirect monitoring of the driver, one uses the driving performance measures such as the lane keeping behavior or steering wheel movements. On the contrary, direct monitoring mainly comprises the driver’s physiological measures such as the brain activities, heart rate and eye movements. In order to assess these objective measures, subjective measures such as self-rating scores are required. This study introduces these measures and discusses the concerns about their interpretation and reliability. The developed drowsiness assistant systems on the market are all based on driving performance measures. These measures presuppose that the vehicle is steered solely by the driver himself. As long as other assistance systems with the concept to keep the vehicle in the middle of the lane are activated, driving performance measures would make wrong decisions about warnings. The reason is what the sensors measure is a combination of the driver’s behavior and the activated assistance system. In fact, the drowsiness warning system cannot determine the contribution of the driver in the driving task. This underscores the need for the direct monitoring of the driver. Previous works have introduced the drop of the alpha spindle rate (ASR) as a drowsiness indicator. This rate is a feature extracted out of the brain activity signals during the direct monitoring the driver. Additionally, ASR was shown to be sensitive to driver distraction, especially a visual one with an counteracting effect. We develop an algorithm based on eye movements to reduce the negative effect of the driver visual distraction on the ASR. This helps to partially improve the association of ASR with the driver drowsiness. Since the focus of this study is on driver eye movements, we introduce the human visual system and describe the idea of what and where to define the visual attention. Further, the structure of the human eye and relevant types of eye movements during driving are defined. We also categorize eye movements into two groups of slow and fast eye movements. We show that blinks, in principle, can belong to both of these groups depending on the driver’s vigilance state. EOG as a tool to measure the driver eye movements allows us to distinguish between drowsiness or distraction-related and driving situation dependent eye movements. Thus, in a pilot study, an experiment under fully controlled conditions is carried out on a proving ground to investigate the relationship between driver eye movements and different real driving scenarios. In this experiment, unwanted head vibrations within EOG signals and the sawtooth pattern (optokinetic nystagmus, OKN) of eyes are realized as situation dependent eye movements. The former occurs due to ground excitation and the latter happens during small radius (50m) curve negotiation. The statistical investigation expresses a significant variation of EOG due to unwanted head vibrations. Moreover, an analytical model is developed to explain the possible relationship of KON and tangent point of the curve. The developed model is validated against the real data on a high curvature track. In order to cover all relevant eye movement patterns during awake and drowsy driving, different experiments are conducted in this work including daytime and nighttime experiments under real road and simulated driving conditions. Based on the measured signals in the experiments, we study different eye movement detection approaches. We, first, investigate the conventional blink detection method based on the median filtering and show its drawback in detecting slow blinks and saccades. Afterwards, an adaptive detection approach is proposed based on the derivative of the EOG signal to simultaneously detect not only the eye blinks, but also other driving-relevant eye movements such as saccades and microsleep events. Moreover, in spite of the fact that drowsiness influences eye movement patterns, the proposed algorithm distinguishes between the often confused driving-related saccades and decreased amplitude blinks of a drowsy driver. The evaluation of results shows that the presented detection algorithm outperforms the common method based on median filtering so that fast eye movements are detected correctly during both awake and drowsy phases. Further, we address the detection of slower eye blinks, which are referred to as typical patterns of the drowsiness, by applying the continuous wavelet transform to EOG signals. In our proposed algorithm, by adjusting parameters of the wavelet transform, fast and slow blinks are detected simultaneously. However, this approach suffers from a larger false detection rate in comparison to the derivative-based method. As a result, for blink detection in this work, a combination of these two methods is applied. To improve the quality of the collected EOG signals, the discrete wavelet transform is benefited to remove noise and drift. For the noise removal, an adaptive thresholding strategy within the discrete wavelet transform is proposed which avoids sacrificing noise removal for saving blink amplitude or vice versa. In previous research, driver eye blink features (blink frequency, duration, etc.) have shown to be correlated to some extent with drowsiness. Hence, within a level of uncertainty they can contribute to driver drowsiness warning systems. In order to improve such systems, we investigate characteristics of detected blinks with respect to their different origins. We observed that in a real road experiment, blinks occur both spontaneously or due to gaze shifts. Gaze shifts between fixed positions, which occurred due to secondary visuomotor task, induced and modulated the occurrence of blinks. Moreover, the direction of the gaze shifts affected the occurrence of such blinks. Based on the eye movements during another experiment in a driving simulator without a secondary task, we found that the amount of gaze shifts (between various positions) is positively correlated with the probability of the blink occurrence. Therefore, we recommend handling gaze shift-induced blinks (e.g. during visual distraction) differently from those occurring spontaneously in drowsiness warning systems that rely solely on the variation of blink frequency as a driver state indicator. After studying dependencies between blink occurrence and gaze shifts, we extract 19 features out of each detected blink event of 43 subjects collected under both simulated and real driving conditions during 67 hours of both daytime and nighttime driving. This corresponds to the largest number of extracted eye blink features and the largest number of subjects among previous studies. We propose two approaches for aggregating features to improve their association with the slowly evolving drowsiness. In the first approach, we solely investigate parts of the collected data which are best correlated with the subjective self-rating score, i.e. Karolinska Sleepiness Scale. In the second approach, however, the entire data set with the maximum amount of information regarding driver drowsiness is scrutinized. For both approaches, the dependency between single features and drowsiness is studied statistically using correlation coefficients. The results show that the drowsiness dependency to features evolves to a larger extent non-linearly rather than linearly. Moreover, we show that for some features, different trends with respect to drowsiness are possible among different subjects. Consequently, we challenge warning systems which rely only on a single feature for their decision strategy and underscore that they are prone to high false alarm rates. In order to study whether a single feature is suitable for predicting safety-critical events, we study the overall variation of the features for all subjects shortly before the occurrence of the first unintentional lane departure and first unintentional microsleep in comparison to the beginning of the drive. Based on statistical tests, before the lane departure, most of the features change significantly. Therefore, we justify the role of blink features for the early driver drowsiness detection. However, this is not valid for the variation of features before the microsleep. We also focus on all 19 blink-based features together as one set. We assess the driver state by artificial neural network, support vector machine and k-nearest neighbors classifiers for both binary and multi-class cases. There, binary classifiers are trained both subject-independent and subject-dependent to address the generalization aspects of the results for unseen data. For the binary driver state prediction (awake vs. drowsy) using blink features, we have attained an average detection rate of 83% for each classifier separately. For 3-class classification (awake vs. medium vs. drowsy), however, the result was only 67%, possibly due to inaccurate self-rated vigilance states. Moreover, the issue of imbalanced data is addressed using classifier-dependent and classifier-independent approaches. We show that for reliable driver state classification, it is crucial to have events of both awake and drowsy phases in the data set in a balanced manner. The reason is that the proposed solutions in previous researches to deal with imbalanced data sets do not generalize the classifiers, but lead to their overfitting. The drawback of driving simulators in comparison to real driving is also discussed and to this end we perform a data reduction approach as a first remedy. As the second approach, we apply our trained classifiers to unseen drowsy data collected under real driving condition to investigate whether the drowsiness in driving simulators is representative of the drowsiness under real road conditions. With an average detection rate of about 68% for all classifiers, we conclude their similarity. Finally, we discuss feature dimension reduction approaches to determine the applicability of extracted features for in-vehicle warning systems. On this account, filter and wrapper approaches are introduced and compared with each other. Our comparison results show that wrapper approaches outperform the filter-based methods

Haptic Signals in the Steering System: Controllability of Additional Steering Torque Inputs

In der vorliegenden Arbeit werden die Auswirkungen zusätzlicher Lenkmomenten auf das Fahrer-Fahrzeug-System untersucht. Solche Lenkmomentsignale zeigen großes Potential z.B. bei Spurführungssystemen. So kann der Fahrer sehr schnell auf diese Signale reagieren und gegenüber anderen Signalen sind bessere Leistungen in der Spurführung erreichbar. Allerdings zeigen sich in Einzelfällen falsche Interpretationen dieser Signale. Dies unterstreicht die Wichtigkeit eines angemessenen Designs der Zusatzlenkmomente. Einerseits leistet diese Arbeit eine Umsetzung der im RESPONSE Code of Practice geforderten Untersuchungsmethodik zur Bewertung der Controllability solcher Eingriffe. Dazu werden unterschiedliche Fahrmanöver untersucht und eine pylonenbegrenzte Engstelle als sensitivstes Manöver identifiziert. Ergänzend werden verschiedene Fahrergruppen betrachtet. Im Fokus stehen ältere Fahrer und Fahranfänger als potentielle Risikogruppen. Hinsichtlich der Auswirkungen von Zusatzlenkmomenten ist jedoch kein Unterschied gegenüber normalen Fahrern feststellbar. Weiter setzt sich diese Arbeit zum Ziel, die Auswirkungen zusätzlicher Lenkmomente auf das Fahrer-Fahrzeug-System zu analysieren. Hierfür wird ein experimenteller Ansatz in Realfahrzeug und Fahrsimulator mit Normalfahrern gewählt. Als wesentlich wird in dieser Arbeit der wechselseitige Einfluss von Amplitude und Anstiegssteilheit eines Lenkmoments identifiziert. So zeigt sich, dass durch die Begrenzung der Anstiegssteilheit eines Zusatzmoments auch höhere Amplituden für den Fahrer zumutbar bleiben. Von besonderem Interesse ist die Variation des Fahrzeugübertragungsverhaltens und den Auswirkungen auf die Fahrerwahrnehmung und -reaktion. So ergibt sich, dass das Lenkmoment nicht wesentlich für die Bewertung der Kontrollierbarkeit durch den Fahrer ist. Vielmehr scheint die resultierende Querdynamik die Führungsgröße des Fahrers besser zu beschreiben und fahrzeugübergreifende Grenzwerte für zumutbare Zusatzlenkmomente abzuleiten.This work describes the assessment of the driver’s perception and reaction to additional steering torque signals. These additional torque signals represent haptic signals to the driver. By applying these signals it is possible to support the driver in the lateral control task of lanekeeping. Numerous studies have shown advantages of those signals compared to acoustical or visual cues in specific contexts. However, there are singular cases reported in literature where participants misinterpreted the signals and responded incorrectly. Therefore, a careful design of the torque signals is vitally important. This work provides a methodological approach for investigating the controllability of torque signals according to demands of the RESPONSE Code of Practice. Therefore, the signals are investigated in different driving tasks and a bottleneck maneuver is identified as most sensitive in this context. Furthermore, younger and older drivers are examined as potentially weaker driver groups. The results do not indicate any effect from age on reaction times or perceptions of the signals. To provide design recommendations, the effects of steering torque signals on the driver-vehicle-system are investigated on a test track and in a driving simulator. The gradient and amplitude of the torque signal show a clear influence, while below a certain gradient the effect of the amplitude disappears. Therefore, it is recommended to limit the gradient of steering torque signals for use in the vehicle to ensure controllability. With the goal to identify the underlying perception processes, the drivers’ subjective assessment of the applied torque correlated to objective measures of vehicle motion. This approach allows identification of the main command variables of the drivers’ perception and evaluation. The analyses in this work show vehicle motion parameters as more adequate for estimating the drivers’ subjective evaluation than the applied torque or movement in the steering system

Interstate Interstitials: Bumper Stickers, Driver-Cars and the Spaces of Social Encounter on Contemporary American Superhighways

Since the turn of the 21st century, it has been the established aim of mobilities scholars to investigate the ways in which contemporary life is conditioned and carried out through the movements of people, things and ideas. Despite concerns over global climate change on the one hand, and the heyday of peak-oil receding quickly into the rear view mirror on the other, the primary vehicle of mobility in the United States remains the personal automobile. Contemporary American notions of self and identity are frequently interpreted through the individual’s relationship(s) to cars and driving, and while cars themselves are mass-manufactured items, they afford a number of many non-technical practices of customization as modes of individuation. Perhaps most commonplace of these practices is the use of bumper stickers. This thesis is a critical examination of the type of everyday cultural construction and social encounter that may emerge from reading bumper stickers in motion. Such a practice is informed by both the structural and systemic conditions of American superhighway automobility, as well as by the phenomenological effects of isolation and speed on the road these conditions produce. An embodied subject, emerges through participation in the regime of automobility, but the body I have in mind is not, strictly speaking, the unitary, human body. It is, rather, a performed, materially-heterogeneous assemblage: a reader-car, through which unexpected—often asymmetrical and asynchronous, but nonetheless social— spaces of interaction coalesce and extend