This research examined the relationship between experience and driving performance with secondary tasks. Data were collected from 42 teenage drivers and their parents using an instrumented vehicle for two one hour test track sessions spaced 12 months apart. For part of the sessions, participants followed a lead vehicle which allowed for range data to be collected. Teenage and experienced drivers' driving were compared for cell phone and odometer tasks. Variables such as Speed, Range to Forward Vehicle, and Driving-Related Eyeglance percentages were all analyzed utilizing ANOVA. Post-hoc analysis on continuous data was performed using a Tukey HSD test. Lane Deviations were examined using Chi-Square analyses. Experienced drivers drove faster overall than teenage drivers. Teenage drivers drove faster in the 12 month session than the first session. No significant effects were found for Speed Variance, Range Variance, or Lane Deviations. Experienced drivers had a higher percentage of driving-related glances than teenage drivers. For the odometer task, teenage drivers were found to follow further behind a lead vehicle than adults. Driving experience was believed to have an effect on driver eyeglance patterns due to increased development of attentional control resulting in better switching between the task and the driving environment. Experienced drivers likely drove faster due to increased confidence in their driving ability. This research supports current GDL cell phone restrictions. A drivers' education lesson plan framework was developed to address these differences. Future research should focus on further refining GDL legislation to address the cognitive differences between teenage and experienced drivers. / Master of Science

L'objectif de cette thèse est de déterminer l'impact de la distraction du conducteur et de la consommation d'alcool, ainsi que leurs interactions, sur les performances des conducteurs novices. Des mesures subjectives des comportements à risques et des performances objectives sur simulateur de conduite sont recueillies. Une première expérience étudie les déterminants psycho-sociaux de la prise de risque et le type de comportements à risques rapportés par les jeunes conducteurs. La seconde expérience s'intéresse aux performances lors d'une tâche d'attention divisée sur simulateur de conduite en fonction de l'expérience, de l'âge et du type d'apprentissage suivi. Enfin, la troisième expérimentation a pour objectif d'étudier l'impact de faible et forte dose d'alcool sur les performances de jeunes conducteurs, novices et expérimentés, lors d'une tâche d'attention divisée. Ces recherches permettent d'approfondir nos connaissances sur les mécanismes d'actions de la distraction et de l'alcool sur les performances du conducteur, en particulier des novices. / The aim of this thesis is to investigate the effects of driver distraction by a secondary task, alcohol consumption and their interaction on performance depending on driving experience. Objective and subjective measures are recorded. The first experience studies the determinants of risk-taking and the kind of risky driving behaviour recalled by young drivers. Differences depending on driving experience, sex, and initial training show an increment of driving risk-taking for young drivers with 3 years of driving experience and with traditional training. The aim of the second experiment is to study the effects of a divided attention task on performance depending on driving experience, age and initial training. Novice drivers have more difficulties to divide their attention between two tasks than experienced drivers, notably when one of these tasks is complex or located in peripheral vision. The third experiment studies the negative impact of alcohol (low and high doses) on young drivers' performances, novice and experienced, during a divided attention task. The classical detriment effect of alcohol on driving performance is replicated, and this effect is more pronounced for novice drivers who adopt a risky driving behaviour under the influence of alcohol, even with a low dose of alcohol. This research improves our fundamental knowledge on how distraction and alcohol impair drivers' performance, notably when they are novice.

<p> The automotive industry has experienced significant digitalization in the past three decades,  revolutionizing the way we interact with vehicles and enhancing our driving experience. Tech firms worldwide have been investing in autonomous driving technologies, gaining a competitive edge in the market. As our lives become more screen-centric, the demand for advanced in-car user interfaces has increased, leading to a growing focus on enhancing the overall driving experience and integrating seamless connectivity within vehicles. To ensure efficiency and safety, it is essential to design user interfaces that prioritize simplicity and reduce distractions.  The autonomous driving capability has been observed across OEMs, making mobility efficient and safe while also being time efficient. Shifting to electric vehicles with autonomous driving aims to reduce emissions and promote electrification. Digitalization has become more prominent in the industry, focusing on user experience and convenience through innovative interfaces. As humans are vulnerable to mistakes, the market is becoming more competitive, with features like instrument clusters, steering wheel controls, and head-up displays (HUD) becoming common in modern vehicles. Advanced technologies like voice recognition and touchscreen interfaces are also becoming popular in the automotive industry, but they must run flawlessly to provide the best user experience.  The advent of autonomous driving requires rethinking interface design principles. It investigates the transitions from traditional physical controls to touchscreens and voice commands by analysing the historical development of in-car infotainment systems. It addresses obstacles encountered during this evolution, such as user adaptation to novel interfaces and cognitive burden caused by information overflow. In addition, it examines the specific design considerations for autonomous mode dashboards.  </p>

The aim of the present study was to investigate the correlates and predictors of hazard perception skill among drivers. Specifically, it was examined whether novice and experienced drivers would differ from each other in terms of hazard perception skill. In addition, the role of personality factors and driving skills in predicting hazard perception among drivers was inspected. Drivers&rsquo / hazard perception skills were assessed by using both a computer-based hazard perception latency test (Turkish Hazard Perception Test in Traffic) which consists 31 video clips recorded in real traffic, and a self-report measure (Self-Reported Hazard Perception Scale). Following the completion of hazard perception measures, Turkish drivers (N = 135 / 90 males, 45 females) also responded to the measures of driving skills, big five personality factors, and sensation seeking. The results of the study indicated that both computer-based and self-reported hazard perception measures significantly differentiated novice and experienced drivers after controlling for the effects of age. Results of the regression analyses demonstrated that computer-based hazard perception skills were significantly predicted by perceptual motor skills subscale of the Driving Skill Inventory. Self-reported hazard perception skill was also strongly predicted by age and perceptual motor skills. The results further revealed that sensation seeking and big five traits did not predict either the computer-based or the self-reported hazard perception skill among drivers. It was concluded that the effects of personality factors could be more observable in on-road assessment of hazard perception. However, the significant difference between novice and experienced drivers showed that hazard perception training should be included to the driver-training curriculum in Turkey as an intervention to promote young novice drivers safety. The findings of the present study were argued in the light of the literature and in relation to the implications for traffic safety in Turkey. Additionally, limitations of the study and suggestions for future researches were discussed.

L'objectif de cette thèse est d'identifier les liens entre les facteurs accidentogènes chez les jeunes conducteurs, en analysant les effets de la complexité de la situation et de l'expérience de conduite sur la charge de travail, la tension, la vigilance et les performances. L'hypothèse générale est que les situations coûteuses, i.e. simples et très complexes, ainsi que le manque d'expérience peuvent mener à une forte dépense énergétique. Ainsi, un haut niveau de tension et un faible niveau de vigilance peuvent provoquer des dégradations de performances à travers la hausse de la charge de travail, caractérisant une surcharge du conducteur. Ceci devrait s'observer plus précocement pour les novices ayant suivi un Apprentissage Traditionnel (AT), puis pour ceux ayant suivi un Apprentissage Anticipé de la Conduite (AAC), puis pour les conducteurs arrivant à la fin du permis probatoire, et enfin pour les plus expérimentés. Une première expérimentation menée sur des données subjectives a confirmé les liens entre les niveaux de charge de travail, de tension et de vigilance en fonction de la complexité de la situation. Une seconde expérimentation menée sur des données subjectives et physiologiques a également confirmé les liens entre les niveaux de charge de travail, de tension et de vigilance, avec une sous-estimation du niveau physiologique par les novices AT. Les résultats établissant les liens entre des caractéristiques de la situation de conduite et des caractéristiques individuelles menant à des accidents de la route pourront permettre d'adapter les actions de sensibilisation et les modules de formations à la conduite. / The aim of this thesis is to identify the links between the accidents factors among young drivers, by analyzing the effects of situation complexity and driving experience on workload, tension, vigilance and performance. The general hypothesis is that costly situations, i.e. simple and very complex, and the lack of experience can lead to a high energy expenditure. Thus, a high level of tension and a low level of vigilance can provoke performance impairments through the increase of workload, which characterizes an overload of the driver. This should be early observed for novices who had a traditional learning, then for early-trained novices, then for drivers arriving at the end of the probationnary period, and then for the most experienced ones. A first experiment, carried out on subjective data, has confirmed the links beween the levels of workload, tenion and vigilance depending on situation complexity. A second experiment, carried out on subjective and physiological data, has also confirmed the links between the levels of workload, tension and vigilance, with an underestimation of the pysiological level by the traditionally trained novices. The results establishing the links between the driving situation's characteristics and the individuals' characteristics leading to road accidents will allow adapting the awareness actions and the modules of driving trainings.

Automated vehicles (AVs) have been developing at a rapid pace over the past few years. However, many difficulties still remain for achieving full Level-5 AVs. This signifies that AVs still require human operators to intervene or assist, such as taking over control of AVs or selecting their routes. Therefore, teleoperation can be seen as a subsystem of AVs that can remotely control and supervise a vehicle when needed. However, teleoperated driving conditions are largely different from real-life driving, so remote drivers may experience different driving feedback. In such a situation, therefore, the driving behaviour and performance of remote drivers can also be impacted. The following three studies were conducted to investigate these points. First, a seamless comparative study was carried out between teleoperated and real-life driving. Driving behaviour and performance were compared in two scenarios: slalom and lane following. Significant differences in driving behaviour and performance between them were found in the study. The lane following deviation during teleoperated driving is much greater than that of real-life driving. In addition, remote drivers are more likely to drive slower and make more steering corrections in lane following manoeuvres. Second, three types of steering force feedback (SFF) modes were compared separately in both teleoperated and real-life driving to investigate the effect of SFF on driving experience. The three SFF modes consist of Physical model-based steering force Feedback (PsF), Modular model-based steering force Feedback (MsF), and No steering force Feedback (NsF). The difference between PsF and MsF is that the main forces come from different sources, namely the estimated tyre force and steering motor current, respectively. As expected, the experimental results indicate that NsF would significantly reduce the driving experience in both driving conditions. In addition, remote drivers were found to require reduced steering feedback force and returnability. Finally, the influence of motion-cueing, sound, and vibration feedback on driving behaviour and experience was studied in a virtual teleoperation platform based on the IPG CarMaker environment. The prototype of a teleoperated driving station (TDS) with motion-cueing, sound, and vibration feedback was first developed to study human factors in teleoperated driving. Then, the low-speed disturbance scenario and high-speed dynamic scenario were used separately to investigate how these factors affect driving. Experimental results indicate that sound and vibration feedback can be an important factor in speed control by providing remote drivers a sense of speed. In the low-speed disturbance scenario, motion-cueing feedback can help with road surface perception and improve the driving experience. However, it did not significantly improve driving performance in the high-speed dynamic scenario. The research conducted reveals how driving behaviour may change in teleoperated driving and how different driving feedback influences it. These results could provide guidance for improving teleoperated driving in future research and serve as a guide for policymaking related to teleoperation. / Självkörande fordon (AV) har utvecklats i snabb takt de senaste åren. Men det finns fortfarande många utmaningar innan man når  helt självkörande fordon. Följaktligen krävs fortfarande säkerhetsförare när AV-enheter är i drift och i framtida drift kan AV-enheter stöta på oväntade problem som en människa behöver lösa. Fjärrövervakning kan därför ses som ett  backupsystem, som kan fjärrstyra och övervaka fordonet när det inte fungerar. Men situationen  vid fjärrstyrning är helt annorlunda än för körning i verkligheten, där fjärroperatörer kan uppleva olik återkoppling  och känslor jämfört med körning i verkligheten. Därför kan även fjärroperatörernas körbeteende och prestanda ändras i denna situation. För att undersöka detta utfördes följande tre studier. För det första genomfördes en sömlös jämförelsestudie mellan fjärrstyrning och verklig körning. Körbeteende och prestanda jämfördes i två scenarier, nämligen slalom och linjeföljning. Signifikanta skillnader i körbeteende och prestanda hittades mellan fjärrstyrning och körning i verkligheten. Avvikelse från linjeföljning vid fjärrstyrning är betydligt större än för körning i verkligheten. Dessutom är det mer sannolikt att fjärroperatörer kör i lägre hastigheter och gör fler styrkorrigeringar vid fjärrstyrning.  För det andra jämfördes tre typer av styrkraftsåterkopplingsmodeller (SFF) separat i både fjärrstyrning och verklig körning för att undersöka SFF:s inverkan på körupplevelsen. De tre SFF-modellerna inkluderar en  modell för fysisk återkoppling (PsF), modell för modulär återkoppling (MsF) och ingen återkoppling (NsF). Skillnaden mellan PsF och MsF är att huvudkrafterna härrör från olika källor, nämligen respektive från den matematiskt uppskattade däckkraften och från styrmotorströmmen. Som förväntat tyder resultaten av experimentet på att NsF avsevärt skulle minska körupplevelsen vid både fjärrstyrning och körning i verkligheten. Vid fjärrstyrning upptäcktes också  att operatörer kräver minskad styråterkopplingskraft och returförmåga.  Slutligen studerades påverkan av rörelsestyrning, ljud och vibrationsfeedback på körbeteende och upplevelse. Prototypen av fjärrkontrolltorn  med rörelsestyrning, ljud och vibrationsfeedback utvecklades först för att studera mänskliga faktorer vid fjärrstyrning. Sedan användes ett låghastighetsscenario med störningar och det dynamiska höghastighetsscenariot separat för att undersöka hur dessa faktorer påverkar körning vid fjärrstyrning. Resultaten av experimentet indikerar att ljud- och vibrationsåterkoppling kan vara till stor hjälp för att reglera  hastigheten genom att ge operatörerna medvetenhet om hastighet. I låghastighetsscenariot kan återkoppling  från rörelsestyrning underlätta uppfattningen av vägytan och förbättra körupplevelsen. Den ökade dock inte nämnvärt dynamisk körprestanda  i hög hastighet.  Denna forskning undersöker hur körbeteendet kan förändras vid fjärrstyrning och hur olika återkopplingar till operatör påverka körning på distans. Dessa resultat kan  ge vägledning om hur man kan förbättra fjärrstyrning i framtida forskning och fungera som en referens för skapande av regler kopplat till fjärrövervakning och fjärrstyrning. / <p>QC 230504</p>

La sécurité et le confort dans une tâche de conduite automobile sont des facteurs clés qui intéressent plusieurs acteurs (constructeurs, urbanistes, départements de transport), en particulier dans le contexte actuel d’urbanisation croissante. Il devient dès lors crucial d'évaluer l'état affectif du conducteur lors de la conduite, en particulier son niveau de stress qui influe sur sa prise de décision et donc sur ses performances de conduite. Dans cette thèse, nous nous concentrons sur l'étude des changements de niveau de stress ressenti durant une expérience de conduite réelle qui alterne ville, autoroute et repos. Les méthodes classiques sont basées sur des descripteurs proposés par des experts, appliquées sur des signaux physiologiques. Ces signaux sont prétraités, les descripteurs ad-hoc sont extraits et sont fusionnés par la suite pour reconnaître le niveau de stress. Dans ce travail, nous avons adapté une méthode de sélection de variables fonctionnelles, basée sur les forêts aléatoires, avec élimination récursive des descripteurs (RF-RFE). En effet, les biosignaux, considérés comme variables fonctionnelles, sont tout d’abord projetés sur une base d’ondelettes. L’algorithme RF-RFE est ensuite utilisé pour sélectionner les groupes d’ondelettes, correspondant aux variables fonctionnelles, selon un score d’endurance. Le choix final de ces variables est basé sur ce score proposé afin de quantifier la capacité d’une variable à être sélectionnée et dans les premiers rangs. Dans une première étape, nous avons analysé la fréquence cardiaque (HR), électromyogramme (EMG), fréquence respiratoire (BR) et activité électrodermale (EDA), issus de 10 expériences de conduite menées à Boston, de la base de données du MIT, drivedb. Dans une seconde étape, nous avons conduit 13 expériences in-vivo similaires, en alternant conduite dans la ville et sur autoroute dans la région de Grand Tunis. La base de données résultante, AffectiveROAD contient -comme dans drivedb- les biosignaux tels que le HR, BR, EDA mais aussi la posture. Le prototype de plateforme de réseau de capteurs développé, a permis de collecter des données environnementales à l’intérieur du véhicule (température, humidité, pression, niveau sonore et GPS) qui sont également inclues dans AffectiveROAD. Une métrique subjective de stress, basée sur l’annotation d’un observateur et validée a posteriori par le conducteur au vu des enregistrements vidéo acquis lors de l’expérience de conduite, complète cette base de données. Nous définissons ici la notion de stress par ce qui résume excitation, attention, charge mentale, perception de complexité de l'environnement par le conducteur. La sélection de variables fonctionnelles dans le cas de drivedb a révélé que l'EDA mesurée au pied est l'indicateur le plus révélateur du niveau de stress du conducteur, suivi de la fréquence respiratoire. La méthode RF-RFE associée à des descripteurs non experts, conduit à des performances comparables à celles obtenues par la méthode basée sur les descripteurs sélectionnés par les experts. En analysant les données d’AffectiveROAD, la posture et l’EDA mesurée sur le poignet droit du conducteur ont émergé comme les variables les plus pertinentes. Une analyse plus approfondie de l'EDA a par la suite été menée car ce signal a été retenu, pour les deux bases de données, parmi les variables fonctionnelles sélectionnées pour la reconnaissance du niveau de stress. Ceci est cohérent avec diverses études sur la physiologie humaine qui voient l’EDA comme un indicateur clé des émotions. Nous avons ainsi exploré le caractère fractal de ce biosignal à travers une analyse d'auto-similarité et une estimation de l'exposant de Hurst basée sur les ondelettes. L'analyse montre un comportement d’auto-similarité des enregistrements de l'EDA pour les deux bases de données, sur une large gamme d’échelles. Ceci en fait un indicateur potentiel temps réel du stress du conducteur durant une expérience de conduite réelle. / The safety and comfort in a driving task are key factors of interest to several actors (vehicle manufacturers, urban space designers, and transportation service providers), especially in a context of an increasing urbanization. It is thus crucial to assess the driver’s affective state while driving, in particular his state of stress which impacts the decision making and thus driving task performance. In this thesis, we focus on the study of stress level changes, during real-world driving, experienced in city versus highway areas. Classical methods are based on features selected by experts, applied to physiological signals. These signals are preprocessed using specific tools for each signal, then ad-hoc features are extracted and finally a data fusion for stress-level recognition is performed. In this work, we adapted a functional variable selection method, based on Random Forests Recursive Feature Elimination (RF-RFE). In fact, the biosignals considered as functional variables, are first decomposed using wavelet basis. The RF-RFE algorithms are then used to select groups of wavelets coefficients, corresponding to the functional variables, according to an endurance score. The final choice of the selected variables relies on this proposed score that allows to quantify the ability of a variable to be selected and this, in first ranges. At a first stage, we analyzed physiological signals such as: Heart Rate (HR), Electromyogram (EMG), Breathing Rate (BR), and the Electrodermal Activity (EDA), related to 10 driving experiments, extracted from the open database of MIT: drivedb, carried out in Boston area. At a second stage, we have designed and conducted similar city and highway driving experiments in the greater Tunis area. The resulting database, AffectiveROAD, includes, as in drivedb, biosignals as HR, BR and EDA and additional measurement of the driver posture. The developed prototype of the sensors network platform allowed also to gather data characterizing the vehicle internal environment (temperature, humidity, pressure, sound level, and geographical coordinates) which are included in AffectiveROAD database. A subjective stress metric, based on driver video-based validation of the observer’s annotation, is included in AffectiveROAD database. We define here the term stress as the human affective state, including affect arousal, attention, mental workload, and the driver’s perception of the environment complexity. The functional variable selection, applied to drivedb, revealed that the EDA captured on foot followed by the BR, are relevant in the driver’s stress level classification. The RF-RFE method along with non-expert based features offered comparable performances to those obtained by the classical method. When analyzing the AffectiveROAD data, the posture and the EDA captured on the driver’s right wrist emerged as the most enduring variables. For both databases, the placement of the EDA sensor came out as an important consideration in the stress level assessment. A deeper analysis of the EDA was carried out since its emergence as a key indicator in stress level recognition, for the two databases. This is consistent with various human physiology studies reporting that the EDA is a key indicator of emotions. For that, we investigated the fractal properties of this biosignal using a self-similarity analysis of EDA measurements based on Hurst exponent (H) estimated using wavelet-based method. Such study shows that EDA recordings exhibits self-similar behavior for large scales, for the both databases. This proposes that it can be considered as a potential real-time indicator of stress in real-world driving experience.

Das Risiko, im Straßenverkehr getötet zu werden, ist für Motorrad-Aufsassen vielfach höher als für andere Verkehrsteilnehmer. Dabei spielt das Verhalten der Motorradfahrer eine zent-rale Rolle. In Abhängigkeit von ihrer Fahrkompetenz können Fahrer durch entsprechendes Agieren und Reagieren kritische Situationen und Unfälle vermeiden. Zur Analyse des Fahrerverhaltens in Situationen individuell unterschiedlicher Kritikalität wurden Versuchs-fahrten mit Motorradfahrern unterschiedlicher Fahrerfahrung auf einem abgesperrten Test-gelände und im öffentlichen Straßenverkehr durchgeführt. Dazu wurde ein Versuchsmotor-rad mit Messtechnik ausgestattet, um detaillierte Informationen zum Fahrer, zum Fahrzeug und zur Umgebung zu erfassen. Die Probanden wiesen große Unterschiede im Fahrerverhal-ten auf, was in den meisten Fällen auf die unterschiedlichen Fahrerfahrungen der Teilneh-mer zurückzuführen ist. Durch detaillierte Analysen des Fahrerverhaltens konnten fahrer-spezifische Defizite festgestellt und entsprechende Verbesserungsmöglichkeiten aufgezeigt werden. Auf Basis dieser Erkenntnisse wurden Konzepte zur Unterstützung des Fahrers bei der Erweiterung seiner Fahrkompetenz beim Motorradfahren aufgestellt. Die Konzepte se-hen eine aus Standardmanövern und Realverkehrsfahrten kombinierte Schulung bzw. ein kombiniertes Training vor. Im Rahmen dessen werden dem Fahrer vor, während oder nach der Fahrt direkt oder indirekt (über eine Begleitperson) relevante Informationen im Hinblick auf entsprechende Verbesserungsmöglichkeiten zur Verfügung gestellt. Darüber hinaus wur-de ein kompakter Datenrekorder prototypisch entwickelt, womit die Grundlage für den prak-tischen Einsatz geschaffen wurde.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.