The older adult population and the number of older adults who rely primarily on driving as their means of transportation in later life are increasing. Older adults experience changes due to aging and age-related diseases that may put them at increased risk of crashes and other unsafe driving behaviours. Considerable evidence has demonstrated that some older adults compensate for their declining abilities by voluntarily restricting their own driving to limit exposure to risky driving situations or by stopping driving altogether. Since mobility is critical for maintaining the independence and quality of life of the older adult, it is important to examine factors that influence driving behaviours of older adults and to promote their safe driving for as long as possible. It has been suggested that driving cessation might occur in discrete stages of driving restriction culminating in driving cessation. Yet, the application of TM to older driver behaviour has not been explored in detail. Thus, the purpose of this research was to explore older adults’ perceptions and experiences of the process of older driver behaviour change within the TM framework. Drivers and former drivers (both men and women) aged 71-94 years of age completed a health and demographic questionnaire and participated in either a digitally recorded semi-structured individual interview or a group discussion. Participants were asked a series of pre-determined questions and probes tailored for either current or former drivers to examine this process. The recordings were transcribed and reviewed for themes related to driving behaviour change. The participants exhibited a wide variety of perceptions and experiences related to the process of driving behaviour change in aging. Their driving behaviour in aging could be divided into 2 general classes: those who changed their driving with age and those who did not. The spectrum of experiences ranged from those who gradually imposed restrictions on their driving with age (“the gradual restrictors”) or made plans for stopping (“the preparers”) to those who always employed driving restrictions throughout their driving history (“the consistent”) or those who made no or only minor changes to their driving behaviour with age (“the non-changers”). Some preliminary support for TM within the driving context was found and recommendations for extensions to the TM model were suggested. Further exploration of driving behaviour change within the TM framework is warranted. The findings from this study may be appropriate for use in designing educational strategies and interventions aimed at helping older adults remain on the road safely longer or stop driving, if needed.

The older adult population and the number of older adults who rely primarily on driving as their means of transportation in later life are increasing. Older adults experience changes due to aging and age-related diseases that may put them at increased risk of crashes and other unsafe driving behaviours. Considerable evidence has demonstrated that some older adults compensate for their declining abilities by voluntarily restricting their own driving to limit exposure to risky driving situations or by stopping driving altogether. Since mobility is critical for maintaining the independence and quality of life of the older adult, it is important to examine factors that influence driving behaviours of older adults and to promote their safe driving for as long as possible. It has been suggested that driving cessation might occur in discrete stages of driving restriction culminating in driving cessation. Yet, the application of TM to older driver behaviour has not been explored in detail. Thus, the purpose of this research was to explore older adults’ perceptions and experiences of the process of older driver behaviour change within the TM framework. Drivers and former drivers (both men and women) aged 71-94 years of age completed a health and demographic questionnaire and participated in either a digitally recorded semi-structured individual interview or a group discussion. Participants were asked a series of pre-determined questions and probes tailored for either current or former drivers to examine this process. The recordings were transcribed and reviewed for themes related to driving behaviour change. The participants exhibited a wide variety of perceptions and experiences related to the process of driving behaviour change in aging. Their driving behaviour in aging could be divided into 2 general classes: those who changed their driving with age and those who did not. The spectrum of experiences ranged from those who gradually imposed restrictions on their driving with age (“the gradual restrictors”) or made plans for stopping (“the preparers”) to those who always employed driving restrictions throughout their driving history (“the consistent”) or those who made no or only minor changes to their driving behaviour with age (“the non-changers”). Some preliminary support for TM within the driving context was found and recommendations for extensions to the TM model were suggested. Further exploration of driving behaviour change within the TM framework is warranted. The findings from this study may be appropriate for use in designing educational strategies and interventions aimed at helping older adults remain on the road safely longer or stop driving, if needed.

It was not that long ago, just in the first half on the 1990s, when mobile phones were first introduced, being big and expensive. All you could do with them was to make phone calls. Since then mobile devices have experienced a great technological advance: we carry smartphones in our pockets that provide Internet access, having accelerometers that can measure acceleration, a gyroscope that can provide orientation information, different wireless interfaces such as Bluetooth connections, and above all, great computing power. On the other hand, the automobile industry has evolved significantly during the last 10 years. One of the most exciting advances in vehicle development is vehicle-to-vehicle V2V communication, which allows cars to communicate with each other over a dedicated Wi-Fi band, and share information about vehicle speed, route direction, traffic flow, and road and weather conditions. An example of such a system is GM's (General Motors) OnStar, introduced in 1996, and that provides automatic response in case of an accident, stolen-vehicle recovery, remote door unlock, and vehicle diagnostics. Also, the standard On Board Diagnosis (OBD-II), available for several years, allows us to connect to the Electronic Control Unit (ECU) via a Bluetooth OBD-II connector. This connection interface allows connectivity between the smartphone and the vehicle, and can be purchased for just over 15 euros. The spectrum of possibilities that arise when combining the car and the smartphone is unlimited, such as performing the diagnosis of the car by assuming the tasks performed by the car's On Board Unit (OBU), or sending the collected data to a platform where the diagnosis or maintenance of the system can be realized in order to detect possible faults, help you to save gas and reduce environment pollution, and notify you of your car's problems, among other features. The general objective pursued with this doctoral thesis is to help drivers to correct bad habits in their driving. To achieve this we promote the combination between smartphones and vehicular networks to design and develop a platform able to offer useful tips to achieve safer driving and greater fuel economy. It is well-known that intelligent driving can lead to lower fuel consumption, with the consequent positive impact on the environment. The proposal that has been carried out in this doctoral thesis begins with the data capture from the vehicles' OBD-II port and data analysis through the use of graphs, maps, and statistics, both, on the server itself and in the smartphone's application developed. We applied data mining techniques and neural networks to analyze, study and generate a classiffication on driving styles based on the analysis of the characteristics of each specific route used for testing. In a second phase, we demostrate the relationship between fuel consumption and driving style. To achieve that goal, the first thing that we had to realize was how to apply different algorithms for the instantaneous consumption calculation (this parameter cannot be obtained directly from the vehicle ECU). Later, we studied and analyzed all data that was collected from the drivers who shared their monitored data with the server. Although drivers do not recognize themselves as being in a state of anxiety while driving, they are more stressed than in any other daily activity, for example, when trying to stay in the right lane, keeping the car at a certain speed, and starting and stopping the vehicle. In general, drivers are more concentrated than they think, which causes an increase in the heart rate. Many factors influence heart rate while at rest, e.g. stress, medications, medical conditions, even genes play a role. In our study we also investigate how stress and the driving behavior influence the heart rate. So, in the last phase, we demostrate the correlation between heart rate and driving style, showing how the driving style can make the heart rate vary by 3 %. / No hace mucho tiempo, tan sólo en la primera mitad en la década de los 90, cuando los teléfonos móviles aparecieron, eran grandes y caros, todo lo que se podía hacer con ellos era realizar llamadas telefónicas. Desde entonces los dispositivos móviles han experimentado un gran avance tecnológico, llevamos teléfonos inteligentes en el bolsillo con acceso a Internet, acelerómetros que calculan la aceleración instantánea, giroscopios que proporcionan información de orientación, diferentes conexiones inalámbricas como Bluetooth, y sobre todo, gran capacidad de computación. Por otro lado, la industria del automóvil ha evolucionado mucho durante los últimos 10 años. Uno de los avances más interesantes en el desarrollo de vehículos ha sido la conectividad, V2V, o comunicación vehículo a vehículo, permite a los automóviles comunicarse mediante Wi-Fi y compartir información sobre la velocidad del vehículo, la dirección de la ruta actual, el tráfico, así como las condiciones de la carretera y las condiciones ambientales. Por otra parte, el estándar On Board Diagnosis (OBD-II), disponible desde hace varios años, permite conectarnos de forma sencilla a la ECU (Electronic Control Unit) mediante un conector Bluetooth OBD-II. Este interfaz de conexión permite la conectividad entre el dispositivo móvil y el vehículo, se puede adquirir por poco más de 15 euros. El espectro de posibilidades que surgen al combinar el automóvil y el Smartphone es amplísimo, como por ejemplo realizar el diagnóstico del coche a través del móvil asumiendo las tareas que hace la unidad On Board Unit (OBU) del coche, o bien enviar los datos recogidos a una plataforma donde se pueda realizar el diagnóstico o mantenimiento del sistema, detectando posibles fallos puede ayudar a ahorrar en el consumo de combustible, notificar los problemas del coche en tiempo real, entre otras características. El objetivo general que se persigue con esta tesis doctoral es ayudar al conductor a corregir malos hábitos en su forma de conducción. Conseguimos esto mediante la combinación entre smartphones y las redes vehiculares, diseñamos y desarrollamos una plataforma capaz de ofrecer consejos útiles para conseguir una conducción más segura y un mayor ahorro de combustible. Es conocido que una conducción inteligente puede llevarnos a un menor consumo de combustible, con el consiguiente impacto positivo que ello conlleva sobre el medio ambiente. La propuesta que se ha llevado a cabo en esta tesis doctoral comienza con la obtención de los datos desde el OBD-II del coche y su presentación y análisis mediante el uso de gráficas, mapas, estadísticas, tanto en el propio servidor como en la aplicación móvil desarrollada para la obtención de datos recibidos desde la ECU. Se aplicaron técnicas de minería de datos y redes neuronales para analizar, estudiar y generar una clasificación sobre los estilos de conducción en base al análisis de las características de la vía sobre la que ha realizado la ruta. En una segunda fase se demostró la relación entre el consumo de combustible con el estilo de conducción, para ello lo primero que tuvimos que realizar fue aplicar diversos algoritmos para el cálculo del consumo instantáneo, este parámetro no es posible obtenerlo directamente de la ECU del vehículo. Posteriormente se realizó el estudio y el análisis de todos los datos que se recogieron de los conductores que se prestaron a la realización del estudio enviando los datos al servidor. Muchos factores influyen en la frecuencia cardíaca en reposo, por ejemplo, el estrés, los medicamentos, las condiciones médicas, incluso los genes tienen su influencia, el envejecimiento tiende a acelerarlo, y el ejercicio regular tiende a ralentizarlo. En nuestro estudio también investigamos cómo el estrés y el comportamiento en la conducción influyen en la frecuencia cardíaca. En la última fase vemos la correlación existente entre el ri / No fa molt de temps, tan sols en la primera mitat en la dècada dels 90, quan els telèfons mòbils van aparéixer, eren grans i cars, tot el que es podia fer amb ells era realitzar telefonades. Des de llavors els dispositius mòbils han experimentat un gran avanç tecnològic, portem telèfons intel_ligents en la butxaca amb accés a Internet, acceleròmetres que calculen l'acceleració instantània, giroscopis que proporcionen informació d'orientació, diferents connexions sense _ls com Bluetooth, i sobretot gran capacitat de computació. D'altra banda, la indústria de l'automòbil ha evolucionat molt durant els últims 10 anys. Un dels avanços més interessants en el desenrotllament de vehicles ha sigut la connectivitat, V2V, o comunicació vehicle a vehicle, permet als automòbils comunicar-se per mitjà de la banda de Wi-Fi i compartir información sobre la velocitat del vehicle, la direcció de la ruta actual, les condicions del trà_c, així com l'estat de la carretera i les condicions ambientals. D'altra banda l'estàndard On Board Diagnosi (OBD-II), disponible des de fa diversos anys, permet connectar-nos de forma senzilla a l'ECU (Electronic Control Unit) per mitjà d'un connector Bluetooth OBD-II. Esta interfície de connexió permet la connectivitat entre el dispositiu mòbil i el vehicle, es pot adquirir per poc més de 15 euros. L'espectre de possibilitats que sorgixen al combinar l'automòbil i el Smartphone és il_limitat, com per exemple realitzar el diagnòstic del cotxe a través del móvil assumint les tasques que fa la unitat On Board Unit (OBU) del cotxe, o bé enviar les dades arreplegades a una plataforma on es puga realitzar el diagnòstic o manteniment del sistema, detectant possibles fallades, ajuda a estalviar en el consum de combustible, noti_car els problemes del cotxe en temps real, entre altres característiques. L'objectiu general que es perseguix amb esta tesi doctoral és ajudar al conductor a corregir mals hàbits en la seua forma de conducció. Aconseguim açò mitjançant de la combinació entre smartphones i les xarxes vehiculares, dissenyem i desenrotllem una plataforma capaç d'oferir consells útils per a aconseguir una conducció més segura i un major estalvi de combustible. És conegut que una conducció intel_ligent pot emportar-nos a un menor consum de combustible, amb el consegüent impacte positiu que això comporta sobre el medi ambient. La proposta que s'ha dut a terme en esta tesi doctoral comença amb l'obtenció de les dades des de l'OBD-II del cotxe i la seua presentació i anàlisi per mitjà de l'ús de grà_ques, mapes, estadístiques, tant en el propi servidor, com en l'aplicació mòbil desenrotllada per a l'obtenció de dades rebudes des de l'ECU. S'apliquen tècniques de mineria de dades i xarxes neuronals per a analitzar, estudiar i generar una classi_cació sobre els estils de conducció basant-se en l'anàlisi de les característiques de la via sobre la qual ha realitzat la ruta. En una segona fase es va a demostrar la relació entre el consum de combustible amb l'estil de conducció, per a això la primera cosa que vam haver de realizar va ser aplicar diversos algorismes per al càlcul del consum instantani, este paràmetre no és possible obtindre-ho directament de l'ECU del vehicle. Posteriorment es va realitzar l'estudi i l'anàlisi de totes les dades que es van arreplegar dels conductors que es van prestar a la realització de l'estudi enviant les dades al servidor. Molts factors in_ueixen en la freqüència cardíaca en repòs, per exemple, l'estrès, els medicaments, les condicions mèdiques, _ns i tot els gens tenen la seua in_uència, l'envelliment tendeix a accelerar-ho, i l'exercici regular tendeix a ralentir-ho. En el nostre estudi només estem interessats en com l'estrès i el comportament en la conducció in_ueixen en la freqüència cardíaca. En l'última fase vam veure la correlació existent entre el ritme cardíac i l'estil de conducci / Meseguer Anastasio, JE. (2017). A novel framework to promote eco-driving through smartphone-vehicle integration [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/84287 / TESIS

This dissertation deals with issues concerning driver education and driver training courses. It first deals with driver education in Czech schools and its representation in RVP.A comparison of driver education in the Czech Republic with driver education in foreign countries is presented in accordance with the results of research project Q F 44L/058/050. It also deals with the preparation of teachers for driver education in terms of a university study. The text attempts to highlight the importance of driver education throughout the entire lifetime of drivers. It covers driver education in the family, preschool, grammar school and high school education as well as preventive driving campaigns and training courses, and also in driving schools. The work also deals with differences between various ways of driving, and more specifically, those between defensive and cooperative driving. It attempts to find a delineation between these concepts in a non-uniform community of specialists. A significant part of the work deals with investigative research, which is primarily centered in interviews with transportation specialists, observation of participants in defensive driving courses and the analysis of documents. Keywords: traffic education, traffic prevention, defensive driving, cooperative driving, course of...

Abgelenktes Fahren gehört zu den Hauptursachen von Verkehrsunfällen und kann auf visuelle, manuelle oder kognitive Ablenkungsquellen zurückgeführt werden. Jede dieser Ablenkungsquellen wurde bereits mit negativen Effekten auf die Fahrerleistung in Zusammenhang gebracht. Obschon ein weitgehender Konsens über negative Auswirkungen von visueller/visuell-manueller Ablenkung besteht, sind die Wirkungen kognitiver Ablenkung auf Fahrfehler und Unfälle noch immer umstritten. Viele experimentelle Studien haben negative Auswirkungen kognitiver Ablenkung auf die Fahrerleistung berichtet. Demgegenüber stehen jedoch die Ergebnisse der Mehrzahl vorliegender „naturalistic driving studies“, die kein erhöhtes Unfallrisiko oder sogar protektive Effekte in diesem Zusammenhang fanden. Die aktuelle Entwicklung hin zu Mensch-Fahrzeug-Schnittstellen, die die Bedienung diverser Anwendungen mittels Sprachsteuerung ermöglichen, führt zu einem Anstieg von kognitiver Beanspruchung beim Fahren. Es ist daher von entscheidender Bedeutung, die Auswirkungen kognitiver Ablenkung auf die Fahrerleistung zu erfassen, um den Verantwortungsträgern in der Gesellschaft, den Regierungen und der Industrie eine Risikoabschätzung dieser Funktionen zu ermöglichen und die Sicherheit von Mensch-Fahrzeug-Schnittstellen zu erhöhen. Das Hauptziel dieser Dissertation bestand darin, die Effekte von kognitiver Ablenkung auf die Fahrerleistung zu untersuchen. Verschiedene Arten kognitiver Ablenkung, die sich beim Fahren unter realen Bedingungen häufig auf die Fahrer auswirken, wurden in dieser Arbeit kodiert und analysiert: kognitiv ablenkende Nebenaufgaben (z.B. telefonieren, singen), Fahreremotionen (z.B. Freude, Wut/Frustration, Traurigkeit) und Kombinationen von Fahreremotionen und Nebenaufgaben (z.B. Streit mit dem Beifahrer oder am Telefon). Bei der Untersuchung von Effekten kognitiver Ablenkung auf das Fahren sind Umwelt-, Situations- und Personenfaktoren zu berücksichtigen, da sie Mediator- und Moderatorvariablen bei der Erfassung des relativen Risikos von Ablenkung beim Fahren im Straßenverkehr darstellen. Daher folgte diese Dissertation dem ganzheitlichen Ansatz, so viele relevante Variablen wie möglich zu betrachten, die mit der Ausführung kognitiv ablenkender Tätigkeiten interagieren. Zu diesem Zweck wurden Daten der derzeit umfangreichsten „naturalistic driving study“ (the second Strategic Highway Research Program, SHRP 2) kodiert und analysiert, um möglichst viele Situationen, in denen eine kognitive Beanspruchung die Fahrerleistung potenziell beeinflusste, umfassend zu bewerten. Gleichzeitig wurde eine große Zahl von Mediator- und Moderatorvariablen betrachtet, die beim Fahren im realen Straßenverkehr auftreten (z.B. Einfluss von Kreuzungen, Wetter, etc.). Dieser Ansatz sollte das Verständnis und die externe Validität der Ergebnisse erhöhen und stellt einen wichtigen Schritt hin zu einem vollständigen Modell jener Variablen dar, die entweder zu unangemessen Verhaltensweisen und Unfällen beitragen oder sie reduzieren. Im Rahmen der Dissertation wurden vier Studien durchgeführt, die auf der Grundlage von zwei SHRP 2 Datensätzen die Zusammenhänge zwischen kognitiven und anderen Ablenkungsquellen, Umwelt-, Situations- und Personenfaktoren und Fahrerleistung untersuchten. Weiterhin wurden Kausalfaktoren in 315 vom Fahrer verursachten Unfällen und Beinaheunfällen, die mit Fahrerablenkung, Fahrerbeeinträchtigung oder keinem dieser Faktoren assoziiert waren, analysiert. Die erste Studie untersuchte die Auswirkungen von Wut beim Fahren und Streit mit dem Beifahrer oder jemandem am Telefon auf die Fahrerleistung. Wut beim Fahren ging mit einer Häufung aggressiver Verhaltensweisen einher, jedoch nicht mit einer Erhöhung von Fahrfehlern. Streitgespräche mit dem Beifahrer oder einer Person am Telefon (das heißt, wenn mutmaßlich das höchste Maß an kognitiver Ablenkung vorlag), schienen darüber hinaus mit keiner Form von unangemessenen Verhaltensweisen im Zusammenhang zu stehen. Die zweite Studie untersuchte, wie sich kognitive, visuelle und manuelle Fahrerablenkung, emotionale Beeinträchtigung sowie Umwelt-, Situations- und Persönlichkeitsfaktoren auf die Fahrerleistung auswirken. Ein Zusammenhang zwischen kognitiver Ablenkung und einer Verschlechterung der Fahrerleistung konnte nicht festgestellt werden. Die dritte Studie replizierte und erweiterte Ergebnisse der zweiten Untersuchung auf der Grundlage eines größeren Datensatzes, bestehend aus Fahrsegmenten, die Unfällen, Beinaheunfällen und Baselines vorausgingen und weder emotionale noch andere Fahrerbeeinträchtigungen enthielten. In Übereinstimmung mit den Ergebnissen der ersten und zweiten Studie, wurde keine Assoziation zwischen kognitiver Ablenkung und einer verschlechterten Fahrerleistung festgestellt. Bei der vierten Studie handelte es sich um eine vergleichende Analyse von Risikofaktoren für Unfälle/ Beinaheunfälle, die mit verschiedenen Arten von Ablenkung, Beeinträchtigung oder keinem von beiden, assoziiert waren. Unfälle, denen eine kognitive Ablenkung vorausgegangen war, waren vor allem mit von Ablenkung unabhängigen Fahrfehlern verbunden - genau wie die Unfälle, denen keine beobachtbare Nebentätigkeit vorausgegangen war. Dieses Ergebnis lässt vermuten, dass in früheren „naturalistic driving studies“, das Unfallrisiko von kognitiv ablenkenden Nebentätigkeiten eventuell sogar überschätzt wurde. Zusammenfassend legen die Ergebnisse die Schlussfolgerung nahe, dass kognitive Ablenkung durch beobachtbare emotionale Beeinträchtigung, (überwiegend) kognitiv ablenkende Nebenaufgaben oder die Kombination dieser beiden Faktoren, nicht mit sichtbaren negativen Auswirkungen auf die Fahrerleistung im tatsächlichen Straßenverkehr assoziiert werden kann. Im Gegensatz dazu hatten ablenkende Tätigkeiten, die zu Blickabwendungen von der Straße führen, und solche, die mit einem besonders hohen Unfallrisiko assoziiert werden, die größte Wahrscheinlichkeit Fahrfehler und Unfälle zu verursachen. / Driver distractions are among the leading causes of motor vehicle accidents. Such distractions can stem from competing visual, manual, or cognitive resources, all of which have been associated with detrimental effects on driving performance. Although the negative impacts of visual/visual-manual distraction are widely agreed upon, the effects of cognitive load on driving errors and crash risk are still debated. On the one hand, numerous experimental studies have shown adverse effects of cognitive distraction on driving performance. In contrast, most existing naturalistic driving studies have either not revealed increased crash/near-crash risk due to cognitive distraction, or have even reported a safety benefit. The number of in-vehicle tasks placing cognitive load on the driver is increasing in recent years due to the development of auditory human–machine interfaces such as voice control for several functions. This has enhanced the need to assess how cognitive distraction affects driving performance. These results are necessary to provide society, government, and industry with valid risk estimates, which will affect decision making regarding how to enhance the safety of using in-vehicle human-machine interfaces while driving. Therefore, the main objective of this thesis was to investigate how cognitive distraction affects driving performance. Different types of cognitive distraction that commonly affect most drivers in naturalistic conditions were coded and analyzed in the present thesis, including: cognitively distracting secondary tasks (e.g., talking on the phone, singing), driver emotion (e.g., happiness, anger/frustration, sadness), and combinations of driver emotion and secondary task demand (e.g., arguing with a passenger or with someone on the phone). Environmental, situational, and individual factors cannot be ignored when investigating the effects of cognitive distraction on driving performance, as they are mediating and moderating variables for estimating distraction relative risk in naturalistic driving. Therefore, a holistic approach guided this thesis towards incorporating as many important variables as possible that interact with the engagement in cognitively distracting activities. Data from the largest naturalistic driving study ever conducted (the second Strategic Highway Research Program, SHRP 2) were coded and analyzed to comprehensively assess many situations in which cognitive load potentially affected driving performance. Further, the goal was to simultaneously consider many possible mediating and moderating variables existent in real-world traffic (such as intersection influences, weather, etc.). This approach should increase understanding and external validity of the results, as well as represent an important step towards building a complete model depicting variables that contribute to or mitigate aberrant driving behaviors and crash risk. Four different analyses focused on two SHRP 2 data subsets to assess the relationship between cognitive and other distraction sources, environmental, situational, and individual factors, as well as driving performance. In addition, contributing factors in 315 at-fault crash and near-crash events associated with driver distraction, driver impairment, or neither of the two were analyzed. The first study examined driving performance in relation to driving anger as well as arguing with a passenger or with someone on the phone. Results showed that driving anger was associated with more frequent aggressive driving behaviors without increasing driving error frequency. Furthermore, when a conflict arose with a passenger or with someone on the phone (i.e., when the level of cognitive distraction was expected to be highest), there did not appear to be a link to any type of aberrant driving behavior. The second study analyzed driving performance based on cognitive, visual, and manual driver distraction, emotional impairment, as well as environmental, situational, and individual factors. Cognitive distraction was not associated with any decline in driving performance. The purpose of the third analysis was to replicate and extend the second study’s effects based on a larger data sample of driving segments preceding crashes, near-crashes, and matched baselines, of drivers not exhibiting emotional or other impairment types. Corroborating the first and second study’s results, there was no association between cognitive distractions and impaired driving performance. Finally, the fourth study compared the risk factors of crashes/near-crashes associated with either different driver distraction types, impairment, or neither. Crashes preceded by cognitive distraction were mainly associated with driving errors unrelated to the secondary task demands, as were the crashes preceded by no observable secondary task. This finding suggests that previous studies analyzing naturalistic driving data may have even overestimated the crash risk of cognitively distracting secondary task engagement. In summary, this thesis provides compelling evidence that cognitive distraction, either through observable emotional impairment, (mainly) cognitively distracting secondary tasks, or the combination of both, has no apparent relation with poorer driving performance observable in real-world traffic. On the contrary, distracting activities requiring the driver’s gaze to move away from the forward roadway and those associated with a particularly high crash risk had the highest chances of causing driving errors and crashes.

Modern cars have a multitude of driver assistance functions that aim to support the driver in his/her everyday driving. One part of this is the Adaptive Cruise Control (ACC) that aims to keep a driver-specified speed. However, this set speed might be perceived as too high for some curves and as a result the driver will interrupt the system and take control again. To avoid this, a Curve Speed Adaptation (CSA) system aims to adapt the speed for an upcoming curve. Such a system should aim to mimic a driver and take into consideration how the driver would behave if he/she were to drive. This work aims to find a set of so-called Driving Modes that can describe how drivers with different driving styles drive through curves with different road properties by analysing recorded manual driving. A nested clustering approach is tested to divide curves into groups based on the driving style they were driven at and their road properties. The results show that this approach is able to capture different driving behaviours through curves. The road type and speed limit of a curve seem thereby to have the main influence on the driving behaviour. Clustering curves first by their driving style followed by the road properties yields thereby the more distinguishable Driving Modes. However, further improvements of the clustering methods are necessary to improve the obtained Driving Modes. The results of this thesis can form the basis for the development of a Curve Speed Adaptation system that adjusts for both the individual driver as well as particular road properties to improve the driver's comfort. / Moderna bilar har en mängd förarstödsystemer som syftar till att stödja föraren i sin dagligakörning. En av dem är Adaptive Cruise Control (ACC) som syftar till att hålla en hastighetspecificerad av föraren. Men denna hastighet kan uppfattas som för hög för vissa kurvoroch som resultat tar föraren kontrollen igen själv. För att undvika detta ska ett Curve SpeedAdaptation (CSA) system anpassa hastigheten för en kommande kurva. Ett sådant systembör sträva efter att efterlikna en förare och ta hänsyn till hur föraren skulle köra själv. Dethär examensarbetet syftar till att hitta så kallade körlägen som kan beskriva hur förare medolika körstilar kör genom kurvor med olika omständigheter genom att analysera manuellakörningar. En nestad klustringsmetod testas för att dela upp kurvor i grupper baserat påkörstilen som de kördes på och deras vägegenskaper. Resultaten visar att denna metod kanfånga olika körningsbeteenden genom kurvor. Vägtypen och hastighetsbegränsningen fören kurva verkar därmed ha huvudinverkan på körbeteendet. Att dela kurvorna först efterderas körstil följt av vägegenskaper ger bättre körlägena. Men ytterligare förbättringar avklustringsmetoderna är nödvändig för att förbättra de erhållna körningsmetoderna. Resul-taten av detta examensarbetet kan utgöra grunden för utvecklingen av ett kurvhastighetsanpassningssystem som anpassar både för den enskilda föraren och speciella vägegenskaperför att förbättra förarens komfort.

The impact of driving cycle on exhaust emissions of buses in Hanoi was presented in this article. A typical driving cycle of buses in Hanoi was developed based on the real-world driving data, and it also was assessed that has a good conformity with the real-world driving data. The typical driving cycle and European Transient Cycle part 1 (ETC-part1) were used to estimate vehicle emission according to different driving cycles. The obtained results showed that emissions level of CO, VOC, PM, CO2 and NOx of the buses were very different between two driving cycles, especially CO2 and NOx. This paper, therefore, reconfirms the necessity of the development of the typical driving cycle before conducting the emission inventory for mobile sources. / Tóm tắt: Tác động của chu trình lái tới sự phát thải của xe buýt tại Hà Nội đã được trình bày trong bài báo này. Một chu trình lái đặc trưng của xe buýt Hà Nội đã được xây dựng dựa trên dữ liệu hoạt động ngoài thực tế của phương tiện, và chu trình lái này cũng đã được đánh giá có sự phù hợp rất cao với dữ liệu lái ngoài thực tế. Chu trình lái đặc trưng và chu trình thử ETC-part1 được sử dụng để đánh giá phát thải của phương tiện theo các chu trình lái khác nhau. Các kết quả đạt được cho thấy mức độ phát thải CO, VOC, PM, CO2 và NOx của xe buýt rất khác nhau giữa hai chu trình lái, đặc biệt là CO2 và NOx. Do đó, bài báo khẳng định sự cần thiết phải xây dựng chu trình lái đặc trưng trước khi thực hiện kiểm kê phát thải đối với nguồn động.

Seit dem Jahr 2004 wurde zur besseren Ausbildung junger Fahranfänger das Begleitete Fah-ren eingeführt, welches ein Erwerb des Führerscheins ab dem 17. Geburtstag erlaubt. Ge-dacht zum Aufbau von Fahrpraxis und zur Verbesserung der Sicherheit finden die ersten Fahrerfahrungen in Begleitung durch einen erfahrenen Erwachsenen statt. Bei Analyse der von der Bundesanstalt für Straßenwesen durchgeführten Evaluationen ist eine insgesamt sehr positive Einschätzung des Modells festzustellen. Dazu wurde eine Be-fragung von Teilnehmern des Begleiteten Fahrens durchgeführt. Ergänzend dazu erfolgt eine Ökonometrische Untersuchung der offiziellen Unfallstatistiken. Betrachtet wird die gesamte Altersklasse der 18- bis 21-jährigen und die Entwicklung ihrer Unfallanfälligkeit. Dabei ist ein seit der Jahrtausendwende fallender Verlauf der Unfallzah-len zu beobachten. Zum Zeitpunkt der Einführung des neuen Modells ist kein beschleunigtes oder verstärktes Absinken dieser Zahlen zu erkennen. Vielmehr ist ein langfristiger Trend zu erkennen. / Since its first introduction in 2004 the Accompanied Driving allows new drivers to obtain their driver’s license from the age of 17 on. The first year of driving is spent in the company of an experienced driver, thus enhancing the beginner’s driving experience and safety. The analysis of several reports by the German road authority, the “Bundesanstalt für Straßen-wesen”, leads to a mostly positive view of the new scheme. The reports are based on a survey among participants of the Accompanied Driving. In addition to those an econometrical analysis of the official road accident statistics has been conducted. The development of these numbers among the age group from 18 until 21 shows a decreasing accident rate since around the year 2000. The introduction of the new driver’s license model does not result in a significant acceleration of that decline. Instead of such influence a long-range trend can be observed.

Background: Drug use among the driving population is a major hazard to road safety and has been the subject of widespread research worldwide. In an attempt to detect and appropriately prosecute “drug-drivers”, the UK has made legislative changes and has introduced Field Impairment Tests (FIT) in the Railway and Transport Safety Act 2003. These FIT, which are identical to the Standardised Field Sobriety Tests (SFST), were devised in the USA in the 1970s to identify clinical signs of impairment due to alcohol intoxication, but were not designed or intended to identify drug-related driving impairment. Concerns have been expressed that FIT are too difficult for their stated function, and are also inappropriate tests, since although they have been validated for alcohol effects they have never been validated for the effects of drugs. This thesis has sought to clarify matters and has questioned the validity of FIT by testing two opposing hypotheses – 1) FIT are reliable and valid tests of drug-related impairment to drive - and drug-free individuals perform well on all tests. 2) FIT are not reliable and valid tests of drug-related impairment to drive - and are too difficult for some groups of drug-free individuals to perform. Methods: A questionnaire was designed and a postal survey was undertaken of 960 Forensic Medical Examiners (FMEs) who were asked to give their opinion on the Field Impairment Tests (FIT). The responses of the FMEs were analysed in detail (chapter 3). FIT were then carried out on three separate groups of 100 subjects in police custody who were all known to have used no drugs for a period of at least 8 hours prior to the testing process (chapter 4). Group A subjects were opiate dependent; Group B were subjects who received legally prescribed methadone; Group C individuals denied any form of drug use. All study groups were simultaneously examined using conventional psychomotor tests, and the results were compared using detailed statistical analysis with logistic regression and summative scores. Results: Returned FME questionnaires showed 63% of FMEs considered the tests “about right” but a significant number (p<0.0001) of 33% of FMEs stated FIT were “too difficult”. The studies on subjects in custody clearly showed 82% of group A; 44% of group B; and 19% of group C were unable to complete FIT satisfactorily, although only 12% of group A; 2% of group B; and 3% of group C were unable to successfully perform conventional psychomotor and cognitive tests. These findings clearly supported the assertions held by 33% of FMEs surveyed that FIT were too difficult for their stated purpose and that poor performance in FIT could not be regarded as definitive evidence of drug-related impairment in driving ability. VII Conclusions: The results of the research studies conducted have provided very strong support in favour of hypothesis 2) FIT are not reliable and valid tests of drug-related impairment to drive - and are too difficult for some groups of drug-free individuals to perform. In an attempt to overcome the problems in respect of FIT, specific proposals have been offered including the introduction of a new battery of more relevant clinical tests of impairment (CTI); a change in the method and manner in which the proposed new tests are applied; and possible legislative and administrative measures which might be introduced to more appropriately and effectively tackle this on-going hazard to road safety.

Many cities across the globe are working to facilitate cycling as a sustainable transportation mode through changes to public policy and investments in infrastructure. Examining the costs and benefits of both driving and cycling using the cost benefit analysis (CBA) framework developed in Copenhagen provides an opportunity to identify private and social costs associated with these modes of transport with respect to environmental, social, and economic impacts. This paper outlines the methods used to calculate the per-kilometre costs of driving and cycling in Calgary, Canada, utilizing real-world data and methods from Canadian and global best-practice with the Copenhagen CBA framework as a guide. Transportation costs were calculated for travel time, vehicle ownership, health, collisions, air pollution, climate change, noise, roadway degradation, congestion, and winter maintenance for both driving and cycling. When the costs borne by both individuals and society are calculated for Calgary (in 2015 Canadian dollars) driving costs $0.83 per kilometre and cycling costs $0.08 per kilometre. When the social costs of transport are isolated, the cost of driving one kilometre is $0.10, while cycling one kilometre generates a net social benefit of $0.35. The results of this research show that the Copenhagen CBA framework can be applied in jurisdictions outside Denmark to calculate environmental, social, and economic costs of driving and cycling.