In recent years the use of advanced driving simulators has increased in the transportation engineering field especially in evaluating safety countermeasures. The driving simulator at UCF is a high fidelity simulator with six degrees of freedom. This research aims at validating the simulator in terms of speed and safety with the intention of using it as a test bed for high risk locations and to use it in developing traffic safety countermeasures. The Simulator replicates a real world signalized intersection (Alafaya trail (SR-434) and Colonial Drive (SR-50)). A total of sixty one subjects of age ranging from sixteen to sixty years were recruited to drive the simulator for the experiment, which consists of eight scenarios. This research validates the driving simulator for speed, safety and visual aspects. Based on the overall comparisons of speed between the simulated results and the real world, it was concluded that the UCF driving simulator is a valid tool for traffic studies related to driving speed behavior. Based on statistical analysis conducted on the experiment results, it is concluded that SR-434 northbound right turn lane and SR-50 eastbound through lanes have a higher rear-end crash risk than that at SR-50 westbound right turn lane and SR-434 northbound through lanes, respectively. This conforms to the risk of rear-end crashes observed at the actual intersection. Therefore, the simulator is validated for using it as an effective tool for traffic safety studies to test high-risk intersection locations. The driving simulator is also validated for physical and visual aspects of the intersection as 87.10% of the subjects recognized the intersection and were of the opinion that the replicated intersection was good enough or realistic. A binary logistic regression model was estimated and was used to quantify the relative rear-end crash risk at through lanes. It was found that in terms of rear-end crash risk SR50 east- bound approach is 23.67% riskier than the SR434 north-bound approach.

Driving simulators are used to conduct experiments on for example driver behavior, road design, and vehicle characteristics. The results of the experiments often depend on the traffic conditions. One example is the evaluation of cellular phones and how they affect driving behavior. It is clear that the ability to use phones when driving depends on traffic intensity and composition, and that realistic experiments in driving simulators therefore has to include surrounding traffic. This thesis describes a model that generates and simulates surrounding vehicles for a driving simulator. The proposed model generates a traffic stream, corresponding to a given target flow and simulates realistic interactions between vehicles. The model is built on established techniques for time-driven microscopic simulation of traffic and uses an approach of only simulating the closest neighborhood of the driving simulator vehicle. In our model this closest neighborhood is divided into one inner region and two outer regions. Vehicles in the inner region are simulated according to advanced behavioral models while vehicles in the outer regions are updated according to a less time-consuming model. The presented work includes a new framework for generating and simulating vehicles within a moving area. It also includes the development of enhanced models for car-following and overtaking and a simple mesoscopic traffic model. The developed model has been integrated and tested within the VTI Driving simulator III. A driving simulator experiment has been performed in order to check if the participants observe the behavior of the simulated vehicles as realistic or not. The results were promising but they also indicated that enhancements could be made. The model has also been validated on the number of vehicles that catches up with the driving simulator vehicle and vice versa. The agreement is good for active and passive catch-ups on rural roads and for passive catch-ups on freeways, but less good for active catch-ups on freeways.

Battery electric vehicles are becoming more common but still fall behind combustion engine cars in terms of driving range and charging time. The displayed driving range in electric vehicles' dashboard can be a volatile parameter suddenly dropping by 10-20\%, for instance when speed is increased. Which can result in a condition referred to as range anxiety . Hence it is interesting to observe more in detail how drivers behave and think in scenarios where range is important and the cars' available range can change drastically depending on the drivers driving style. Such scenarios are problematic to test in real traffic for practical and ethical reasons. In this article, without putting anyone at risk, we present a study using a VR driving simulator in a critical scenario with a substantial risk of running out of battery. Two separate groups (N=10) each drove on the same test track using two different range displays. One group had a typical range display showing the distance left to empty (out of battery) and the other group a novel and more transparent display. The novel display shows how speed is affecting the range. Both displays allow the driver to set a target driving range. The results indicate that the novel display allows for a more agile and adaptive driving style by changing between specific speeds rather than searching and "guessing" which speed is the most optimal as with typical range displays. Although, it can hide other affecting factors, such as acceleration and road height. Which was more prevalent amongst drivers who had to search and guess. / Batterielbilar blir allt vanligare men når inte riktigt upp till samma nivå som bilar med förbränningsmotorer när det handlar om räckvidd och laddtid. Den kvarstående körsträckan som visas i elbilars instrumentpanel kan vara en instabil variabel och plötsligt sjunka med 10-20%, när man till exempel ökar hastigheten. Vilket kan leda till ett tillstånd som kallas räckviddsångest . Därav intresset för att undersöka i detalj hur förare agerar och tänker i scenarier där räckvidd är extra viktigt och bilens kvarstående körsträcka kan ändras drastiskt beroende på körstil. Sådana scenarier är problematiska att testa ute i trafiken av både praktiska och etiska skäl. I denna artikel, utan att placera någon i en verklig riskfylld situation, presenterar vi en studie där en bilsimulator i VR används för att testa ett kritiskt scenario där risken för att strömmen tar slut är stor. Två separata grupper (N=10) körde samma sträcka fast med olika instrumentpaneler. Där den ena är mer konventionell och endast visar kvarstående körsträcka. Medan den andra är mer originell och visar hur hastighet påverkar kvarstående körsträcka. Båda instrumentpanelerna tillåter föraren att ställa in hur långt man vill köra. Resultaten indikerar på att den originella instrumentpanelen tillåter en mer agil och adaptiv körstil, genom att byta mellan specifika hastigheter istället för att leta och gissa vilken hastighet som är optimal, vilket skedde med den konventionella instrumentpanelen. Men den kan även dölja andra faktorer som påverkar körsträckan, såsom acceleration och höjdskillnader. Vilket  användare av den originella instrumentbrädan noterade i större utsträckning.

Nowadays, the Human Machine System (HMS) is considered to be a proven technology, and now plays an important role in various human activities. However, this system requires that only a human has an in-depth understanding of the machine operation, and is thus a one-way relationship. Therefore, researchers have recently developed Human Adaptive Mechatronics (HAM) to overcome this problem and balance the roles of the human and machine in any HMS. HAM is different compared to ordinary HMS in terms of its ability to adapt to changes in its surroundings and the changing skill level of humans. Nonetheless, the main problem with HAM is in quantifying the human skill level in machine manipulation as part of human recognition. Therefore, this thesis deals with a proposed formula to quantify and classify the skill of the human operator in driving a car as an example application between humans and machines. The formula is evaluated using the logical conditions and the definition of skill in HAM in terms of time and error. The skill indices are classified into five levels: Very Highly Skilled, Highly Skilled, Medium Skilled, Low Skilled and Very Low Skilled. Driving was selected because it is considered to be a complex mechanical task that involves skill, a human and a machine. However, as the safety of the human subjects when performing the required tasks in various situations must be considered, a driving simulator was used. The simulator was designed using Microsoft Visual Studio, controlled using a USB steering wheel and pedals, as was able to record the human ii path and include the desired effects on the road. Thus, two experiments involving the driving simulator were performed; 20 human subjects with a varying numbers of years experience in driving and gaming were used in the experiments. In the first experiment, the subjects were asked to drive in Expected and Guided Conditions (EGC). Five guided tracks were used to show the variety of driving skill: straight, circular, elliptical, square and triangular. The results of this experiment indicate that the tracking error is inversely proportional to the elapsed time. In second experiment, the subjects experienced Sudden Transitory Conditions (STC). Two types of unexpected situations in driving were used: tyre puncture and slippery surface. This experiment demonstrated that the tracking error is not directly proportional to the elapsed time. Both experiments also included the correlation between experience and skill. For the first time, a new skill index formula is proposed based on the logical conditions and the definition of skill in HAM.

La consommation de cannabis et la conduite sous l’influence du cannabis sont des préoccupations grandissantes dans la société d’aujourd’hui. Le but de la présente étude est d’examiner plus en profondeur la relation entre la fréquence de consommation de cannabis chez les jeunes adultes et la prise de risque sur la route. Les participants (n=48) sont tous des hommes âgés de 18 à 26 ans. Ils ont complété une batterie de questionnaires ainsi qu’une tâche sur simulateur de conduite. Les résultats indiquent que la fréquence de consommation de cannabis est associée positivement avec la prise de risque auto rapportée et suggèrent une tendance positive avec les comportements risqués observés lors de la simulation de conduite en laboratoire. Lorsque les différents groupes de consommateurs sont comparés, ceux qui font un usage quotidien ou multihebdomadaire de cannabis semblent prendre plus de risques au volant que ceux qui consomment une fois semaine et moins ou encore une fois par mois et moins. De plus, il semble que plus les individus consomment fréquemment de la marijuana, plus ils ont tendance à adopter des attitudes permissives en lien avec la conduite sous l’influence de cannabis. Les implications quant à l’intervention sont discutées. / Cannabis use and driving under the influence of cannabis have become a growing concern in today’s society. The aim of the present study was to further examine the relationship between the use frequency of cannabis among young adults and on-road risk taking. Participants (n=48) were all men aged between 18 and 26 years old who were asked to complete questionnaires and to perform in a simulation task. Results indicate that the use frequency of cannabis is positively associated with self-report of risky driving and suggest a trend with observed risk taking behaviour during the simulation. When comparing the different cannabis users, participants who consumed daily or multiple times a week seem to take more risk on the road than those who use cannabis once a week or less and less than monthly. Moreover, it seems that marijuana users who consume more frequently have a tendency of adopting more permissive attitudes toward smoking cannabis and taking the wheel. Implications for interventions are discussed.

The increase in the number of deaths due to ground traffic accidents is a global problem. In such context, the development of new vehicular technologies is considered an alternative to improve road safety. Within the field of new vehicle technologies, it is possible to find driver assistance systems. These systems interact in an active or passive way with the driver, reducing their workload by presenting information about their surroundings, which may imply the safer direction of a land vehicle. Taking into account that one of the main reasons for road traffic fatalities in the world is the lane change in a road, hereby we created a cooperative driver assistance system for the lane change, arising from the combination of a kinematic model and a probabilistic graphical one. By combining these two models, we try to improve the response in the assistance of the system, given the direct dependence of the system with a human. Due to the latter, the response of such systems cannot be deterministic in nature. One of the motivations to use probabilistic graphical models is the flexibility of this machines learning technique in modeling the problem addressed in this thesis. In addition to this contribution of applying a specific probabilistic graphical model in our assistance system, other contributions can be found in this thesis, including the development of a Driving simulation platform with a reconfigurable structure. The ability to reconfigure the structure of the driving simulator platform was of great importance for the development and evaluation of the assistance system hereby proposed in each of its stages. In addition, the decision to model a cooperative approach in our assistance system is due to the great potential of the vehicular communications with respect to improving transport safety and efficiency. The moderate cost that is being projected in vehicular communications is another relevant fact. Finally, the description and application of our assistance system model can be considered as a possibility in the area for the development of an application that needs a close response to the reality, based on the uncertainties present in the problem under consideration. / O aumento no número de mortes por causa de acidentes de tráfego terrestre é um problema global. No âmbito dessa problemática, o desenvolvimento de novas tecnologias veiculares é considerado uma alternativa para melhorar a segurança viária. Dentro do domínio das novas tecnologias veiculares, é possível encontrar sistemas de assistência ao motorista. Esses sistemas interagem de maneira ativa ou passiva com o motorista, conseguindo reduzir sua carga de trabalho, apresentando informações de seu entorno, o que pode implicar uma direção mais segura de um veículo terrestre. Levando em consideração que um dos principais motivos de mortes por acidentes de tráfego terrestre no mundo é a mudança de faixa em uma pista, neste trabalho, realizamos a tarefa de criar um sistema cooperativo de assistência ao motorista para a mudança de faixa, a partir da combinação de um modelo cinemático e de um modelo gráfico probabilístico. Mediante a combinação destes dois modelos, procuramos melhorar a resposta na assistência por parte do sistema, dada a dependência direta que o sistema tem dos humanos. Por essa última razão, a resposta deste tipo de sistemas não pode ser determinística por natureza. Uma das motivações para utilizar os modelos gráficos probabilísticos é a flexibilidade da técnica de machine learning em modelar o problema abordado nesta tese. Além dessa contribuição de aplicar um modelo gráfico probabilístico específico em nosso sistema de assistência, outras contribuições podem ser encontradas nesta tese, incluindo o desenvolvimento de uma plataforma de simulação para a condução, com uma estrutura reconfigurável. A capacidade de poder reconfigurar a estrutura da plataforma de simulação foi de grande importância para o desenvolvimento e avaliação do sistema de assistência proposto nesta tese, em cada uma de suas etapas. Além disso, a decisão de modelar um enfoque cooperativo, em nosso sistema de assistência, se deve ao grande potencial que tem as comunicações veiculares com respeito à melhora da segurança e da eficiência do transporte. O custo moderado que está sendo projetado nas comunicações veiculares é outro fato relevante. A descrição e aplicação de nosso modelo final podem ser considerados mais uma possibilidade na área para o desenvolvimento de uma aplicação, que precise de uma resposta próxima da realidade, a partir das incertezas presentes no problema considerado.

Les fauteuils roulants électriques (FRE) ont permis à nombre de personnes handicapés moteurs de retrouver une mobilité satisfaisante, ce qui a amélioré leur qualité de vie, un vaste champ d’activités leur étant devenu accessible. Lors de la prescription d’un FRE ou d’une phase d’apprentissage à la conduite il est cependant nécessaire d’évaluer les capacités de ces personnes à piloter un fauteuil. Dans ce contexte, notre objectif consiste à déterminer des paramètres pertinents permettant de décrire la qualité de la conduite d’un FRE pour des personnes ayant des déficiences motrices sévères. Tout d’abord, nous avons modélisé le système pilote-FRE par le modèle OPCM (Optimal Preview Control Model) de Sharp. Ce modèle est basé sur la distance anticipée (Dp) par l’utilisateur durant sa conduite du FRE. Cette distance a été estimée grâce à un système de suivi du regard combiné avec le simulateur 3D ViEW du laboratoire LCOMS. Un panel de 15 sujets valides a été recruté pour faire des tests de conduite sur simulateur et valider la modélisation OPCM. La distance Dp a permis de décrire le comportement du pilote. Ensuite, une analyse de la distance anticipée Dp en fonction de différentes zones du parcours (slalom serré, virage, slalom large), a montré que ce paramètre peut être utilisé pour différencier les différents comportements de conduite liées aux différentes situations du parcours. Ensuite nous avons comparé cette distance anticipée entre deux groupes, familiarisés et novices vis-à-vis de la conduite en FRE. L’analyse a montré que le groupe familiarisé présente une distance Dp plus importante que le groupe novice. Enfin, une dernière expérience a eu lieu au Centre de Réadaptation de Flavigny sur Moselle (54, France). Nous avons estimé la distance anticipée (Dp) pour des sujets à déficiences motrices sévères, afin de valider le paramètre Dp comme indicateur de performance. Une étude de cas a été établie portant sur 5 enfants en situation de handicap, en comparant leurs résultats à ceux obtenus précédemment sur un panel de personnes valides / The Powered wheelchairs (PW) allowed many people with motor disabilities to find a suitable mobility, which improved their quality of life. Hence, a vast field of activities has become accessible for them. When prescribing a PW or in a learning phase, however, it is necessary to evaluate the ability of these people to drive a wheelchair. In this context, our goal is to determine relevant parameters to describe the quality of driving on PW for people with disabilities. First, we modeled the pilot-PW system using the OPCM (Optimal Preview Control Model) model proposed by Sharp. This model is based on the preview distance (Dp) of the user during his driving. This distance has been estimated thanks to an eye-tracking system combined with the ViEW 3D simulator of the LCOMS laboratory. A panel of 15 healthy subjects was recruited to drive the PW on a 3D simulator and to validate the OPCM modeling. This distance Dp allows to describe the behavior of the pilot. If this distance is important, it guarantees the tracking trajectory of the OPCM model. Otherwise, the OPCM model diverges. This shows that if the user looks a long part of his future path, he will better anticipate the future control applied to the PW (change of direction, braking, etc.), which allows him to follow his path. In this situation the user has a tracking behavior. In the otherwise, the user’s behavior is rather compensatory. Then, an analysis of preview distance Dp with respect to the different zones of the path (tight slalom, turn, wide slalom), showed that the parameter Dp can be used to differentiate the different driving behaviors related to the different situations of the path. Next, we compared the preview distance between two groups, familiar and novice with regard to the PW driving. The analysis showed that the familiar group has a greater distance value than the novice group. Finally, a last experiment took place at the Rehabilitation Center of Flavigny sur Moselle (54, France). We estimated the preview distance (Dp) for subjects with severe motor impairment, in order to validate the parameter Dp as a performance indicator. A case study analysis was established on five children with disabilities comparing their results with those previously obtained with the healthy subjects

The increase in the number of deaths due to ground traffic accidents is a global problem. In such context, the development of new vehicular technologies is considered an alternative to improve road safety. Within the field of new vehicle technologies, it is possible to find driver assistance systems. These systems interact in an active or passive way with the driver, reducing their workload by presenting information about their surroundings, which may imply the safer direction of a land vehicle. Taking into account that one of the main reasons for road traffic fatalities in the world is the lane change in a road, hereby we created a cooperative driver assistance system for the lane change, arising from the combination of a kinematic model and a probabilistic graphical one. By combining these two models, we try to improve the response in the assistance of the system, given the direct dependence of the system with a human. Due to the latter, the response of such systems cannot be deterministic in nature. One of the motivations to use probabilistic graphical models is the flexibility of this machines learning technique in modeling the problem addressed in this thesis. In addition to this contribution of applying a specific probabilistic graphical model in our assistance system, other contributions can be found in this thesis, including the development of a Driving simulation platform with a reconfigurable structure. The ability to reconfigure the structure of the driving simulator platform was of great importance for the development and evaluation of the assistance system hereby proposed in each of its stages. In addition, the decision to model a cooperative approach in our assistance system is due to the great potential of the vehicular communications with respect to improving transport safety and efficiency. The moderate cost that is being projected in vehicular communications is another relevant fact. Finally, the description and application of our assistance system model can be considered as a possibility in the area for the development of an application that needs a close response to the reality, based on the uncertainties present in the problem under consideration. / O aumento no número de mortes por causa de acidentes de tráfego terrestre é um problema global. No âmbito dessa problemática, o desenvolvimento de novas tecnologias veiculares é considerado uma alternativa para melhorar a segurança viária. Dentro do domínio das novas tecnologias veiculares, é possível encontrar sistemas de assistência ao motorista. Esses sistemas interagem de maneira ativa ou passiva com o motorista, conseguindo reduzir sua carga de trabalho, apresentando informações de seu entorno, o que pode implicar uma direção mais segura de um veículo terrestre. Levando em consideração que um dos principais motivos de mortes por acidentes de tráfego terrestre no mundo é a mudança de faixa em uma pista, neste trabalho, realizamos a tarefa de criar um sistema cooperativo de assistência ao motorista para a mudança de faixa, a partir da combinação de um modelo cinemático e de um modelo gráfico probabilístico. Mediante a combinação destes dois modelos, procuramos melhorar a resposta na assistência por parte do sistema, dada a dependência direta que o sistema tem dos humanos. Por essa última razão, a resposta deste tipo de sistemas não pode ser determinística por natureza. Uma das motivações para utilizar os modelos gráficos probabilísticos é a flexibilidade da técnica de machine learning em modelar o problema abordado nesta tese. Além dessa contribuição de aplicar um modelo gráfico probabilístico específico em nosso sistema de assistência, outras contribuições podem ser encontradas nesta tese, incluindo o desenvolvimento de uma plataforma de simulação para a condução, com uma estrutura reconfigurável. A capacidade de poder reconfigurar a estrutura da plataforma de simulação foi de grande importância para o desenvolvimento e avaliação do sistema de assistência proposto nesta tese, em cada uma de suas etapas. Além disso, a decisão de modelar um enfoque cooperativo, em nosso sistema de assistência, se deve ao grande potencial que tem as comunicações veiculares com respeito à melhora da segurança e da eficiência do transporte. O custo moderado que está sendo projetado nas comunicações veiculares é outro fato relevante. A descrição e aplicação de nosso modelo final podem ser considerados mais uma possibilidade na área para o desenvolvimento de uma aplicação, que precise de uma resposta próxima da realidade, a partir das incertezas presentes no problema considerado.

Driving under distraction may lead drivers to wrong actions that can result in serious accidents. The objective of this thesis was to apply a driving simulator to verify variations in drivers\' behavior while driving. Behavior to drive on a curve was measured by variation in drivers\' speed profile in a virtualized highway. The comparison was performed between two identical simulations, one involving drivers distracted with a mental workload, and other in which they were full aware of driving task. 54 volunteer drivers took part in this study, which was divided into 4 stages. 17 drivers performed the distraction test known as PASAT, and results showed that distracted drivers did not recognize the beginning of the curve and drove through it at speeds higher than those when they were fully aware. Moreover, driving performance was increased when drivers were aware of driving, thereby hitting high speeds in tangents, but perceiving curves in advance to reduce acceleration. This study confirms that driving simulators are beneficial in discovering drivers\' behavior exposed to activities that could be highly risky if driving in real situations. / A distração durante a atividade de direção pode levar o condutor de veículos automotores a cometer falhas, que podem ocasionar até mesmo acidentes graves. Este estudo aborda a utilização de simuladores de direção para verificar variações no comportamento de motoristas ao realizar a atividade de direção, distraídos ou com plena atenção na condução do veículo. O comportamento é medido pela variação no perfil de velocidade dos condutores para desenvolver uma curva considerada perigosa em uma rodovia simulada em ambiente virtual. A variação de velocidade deste perfil é comparada entre duas simulações idênticas, onde em uma delas os condutores estão distraídos com um teste que proporciona estresse mental e, na outra, estão com plena atenção à direção. 54 condutores fizeram parte deste estudo dividido em 3 etapas. 17 participantes realizaram o teste de distração conhecido como PASAT, e a análise dos resultados mostram que, distraídos, os condutores não perceberam o início da curva e desenvolveram velocidades maiores durante seu trajeto. Além disso, quando estavam com plena atenção à atividade de direção, o desempenho dos condutores foi melhor, atingindo velocidades maiores nas tangentes, mas percebendo as curvas antecipadamente e reduzindo suas velocidades antes de iniciar esses trechos.

Ce travail de thèse a été centré sur l’analyse de l’impact d’un système d’alerte anticollision sur le traitement de l’information et le comportement du conducteur en conduite automobile simulée. Les objectifs de ce travail étaient 1) de déterminer l’impact d’un signal avertisseur associé à un système d’alerte anticollision sur le traitement de l’information à partir de potentiels évoqués ; 2) d’analyser l’efficacité d’un tel système en fonction de sa fiabilité ; 3) et en fonction de l’état attentionnel des conducteurs ; et 4) d’examiner l’adaptation comportementale au système au cours du temps. Grâce à une double approche comportementale et électrophysiologique, nous avons montré que le signal avertisseur agit au niveau de l’anticipation et de la préparation à la réponse ainsi qu’au niveau cognitif du traitement de l’information. Par ailleurs, nous avons confirmé que les systèmes anticollision ne nécessitent pas d’être complètement fiables pour être efficaces. Nous avons également observé que l’efficacité du signal avertisseur associé au système anticollision était moindre chez les sujets distraits, notamment lorsque la charge cognitive associée à la distraction était élevée. Ceci suggère que le signal avertisseur nécessite des ressources attentionnelles pour être traité et, donc, pour être efficace. Concernant l’adaptation comportementale au système, les principaux résultats ont montré, d’une part, que l’introduction immédiate du système a eu un effet positif sur le comportement de conduite et, d’autre part, que le processus d’adaptation au système à plus long terme peut être affecté si les conducteurs sont distraits par des tâches secondaires coûteuses en ressources attentionnelles. / This thesis was focused on the analysis of the impact of a collision warning system on information processing and driver behaviour in simulated driving. The objectives of this work were 1) to determine the impact of a warning signal associated with a collision warning system on the processing of information using evoked potentials, 2) to analyse the effectiveness of such a system according to its reliability, 3) and according to the drivers’ attentional state, 4) to examine the behavioural adaptation to the system over time. Using an electrophysiological and behavioural dual approach, we showed that the warning signal acts at the level of anticipation and response preparation and at the level of cognitive processing. Moreover, we confirmed that collision warning systems do not need to be completely reliable to be effective. We also observed that the effectiveness of the warning signal associated with the collision warning system was lower in distracted subjects, especially when the cognitive load associated with the distraction was high. This suggests that the warning signal requires attentionnal resources in order to be processed and, therefore, to be effective. Concerning behavioural adaptation to the system, the main results showed firstly that the immediate introduction of the system had a positive effect on the driving behaviour and secondly that the process of adaptation of the system at the longer term may be affected if drivers are distracted by high demanding secondary tasks.