In recent years, accidents between trucks and other vehicles have decreased while accidents be-tween trucks and vulnerable road-users have increased. The reason for this is unknown, which is why this Master’s Thesis project was initiated. The project is a co-operation between two students from two different universities, LTU and KTH, done for Volvo GTT in Gothenburg. A user study containing interviews and co-rides has been executed with truck drivers in the Gothenburg area during the autumn of 2017. A survey was also sent to different organizations for cyclists, motorcyclists, car drivers and to Facebook groups for the two universities. Critical situations mentioned by the truck drivers were chosen with the help of the survey answers from other road-users. Right hand turns with a truck that crosses a bike lane and intersections with a zebra crossing were the situations the project focused on, based on the Volvo Trucks Safety Report 2017 which stated those situations as the most dangerous. Serious accidents occurring when a truck turns right is when vulnerable road-users end up under the truck’s back wheels, which cuts corners. This made the project focus on trying to find a solution that could reduce this type of accident. The project also concentrated on increasing the commu-nication at intersections, based on the survey comments where it became clear that eye contact is insufficient, which led to focus on communication between trucks and fellow road-user instead. Through benchmarking, literature reviews and idea generation the final concept solution was cre-ated and developed after a workshop. The final concept solution is a turning projection that visualizes the dangerous area when a truck is turning and a light matrix in the front grille for increasing the understanding, visually, of the truck driver’s intentions of slowing down or speeding up. The final concept solution contains a zebra crossing projection in the front of the truck to facilitate the communication today, and in the future to even replace eye contact and gestures done between truck driver and fellow road-users at crossings. Further development of the concept solution includes choices and adaption of available technology and research concerning legislation for color usage on lights and projections to the front and sides of the trucks.

Vulnerable road users (VRUs) are overrepresented in the statistics on severe and deadly injuries in traffic accidents, most commonly involving the head. The finite element (FE) method presents the possibility to model complex interactions between the human body and vehicles in order to better understand the injury mechanisms. While the rapid development of computer capacity has allowed for increasingly detailed FE-models, there is always a benefit of reducing the studied problem. Due to its material properties, the brain is more sensitive to rotational motion than to purely linear, resulting in complex injury causation. When studying brain injuries caused by a direct impact to the head, simulations using an isolated head model significantly increases efficiency compared to using a complete human body model. Also evaluation of head protective systems uses isolated mechanical head representations. It is not, however, established the extent to which the boundary conditions of the head determine the outcome of brain injuries. FE models of both the entire human body and the isolated head were used in this thesis to study the effect of the body, as well as active neck muscle tension, on brain injury outcome in VRU accidents. A pediatric neck model was also developed to enable the study of age-specific effects. A vehicle windscreen model was developed to evaluate the necessity of capturing the failure deformation during pedestrian head impacts. It was shown that the influence of the neck and body on brain injury prediction is greater in longer duration impacts, such as pedestrian head-to-windscreen impacts with an average difference of 21%. In accidents with shorter duration impacts, such as head-to-ground bicycle accidents, the average influence was between 3-12%. The influence did not consistently increase or limit the severity, and was dependent on the degree of rotation induced by the impact, as well as the mode of deformation induced in the neck. It was also shown that the predicted brain injury severity is dependent on capturing the large deformations of fractured windscreen, with the greatest effect near the windscreen frame. The pediatric neck model showed a large effect of age-dependent anatomical changes on inertial head loading, making it a promising tool to study the age-dependent effects in VRU accidents. / <p>QC 20171013</p>

As the desire for deploying automated (“driverless”) vehicles increases, there is a need to understand how they might communicate with other road users in a mixed traffic, urban, setting. In the absence of an active and responsible human controller in the driving seat, who might currently communicate with other road users in uncertain/conflicting situations, in the future, understanding a driverless car’s behaviour and intentions will need to be relayed via easily comprehensible, intuitive and universally intelligible means, perhaps presented externally via new vehicle interfaces. This paper reports on the results of a questionnaire-based study, delivered to 664 participants, recruited during live demonstrations of an Automated Road Transport Systems (ARTS; SAE Level 4), in three European cities. The questionnaire sought the views of pedestrians and cyclists, focussing on whether respondents felt safe interacting with ARTS in shared space, and also what externally presented travel behaviour information from the ARTS was important to them. Results showed that most pedestrians felt safer when the ARTS were travelling in designated lanes, rather than in shared space, and the majority believed they had priority over the ARTS, in the absence of such infrastructure. Regardless of lane demarcations, all respondents highlighted the importance of receiving some communication information about the behaviour of the ARTS, with acknowledgement of their detection by the vehicle being the most important message. There were no clear patterns across the respondents, regarding preference of modality for these external messages, with cultural and infrastructural differences thought to govern responses. Generally, however, conventional signals (lights and beeps) were preferred to text-based messages and spoken words. The results suggest that until these driverless vehicles are able to provide universally comprehensible externally presented information or messages during interaction with other road users, they are likely to contribute to confusing and conflicting interactions between these actors, especially in a shared space setting, which may, therefore, reduce efficient traffic flow.

This thesis will research and evaluate the state of the current ETSI VAM standard. The thesis evaluates and discusses the means of improving the speed and response of ETSI VAM by reducing the load on the radio medium. The research looks to prove that fewer messages broadcasted improve VRU awareness. The thesis focuses mainly on the benefits of VRU clustering as a means of reducing radio medium load through numerical evaluation and physical implementation testing. Evaluation of basic and alternate cluster parameters is performed to find the most optimal ones; alternate clustering strategies are also discussed and proposed. The thesis aims to improve the standard by finding and evaluating alternate methods and parameters in order to propose improved options. / Projektet utvärderar och diskuterar sätten att förbättra hastigheten och responsen hos ETSI VAM genom att minska belastningen på radiomediet. Forskningen syftar till att bevisa att färre meddelanden som sänds förbättrar systemets VRU-medvetenhet. Fokuset ligger huvudsakligen på att utvärdera fördelarna med "VRU-klustring" som ett sätt att minska radiomediebelastningen genom numerisk utvärdering och fysisk testning. Utvärdering av grundläggande och alternativa klusterparametrar utförs för att hitta de mest optimala; alternativa klustringsstrategier diskuteras och föreslås också. Projektet syftar till att förbättra standarden genom att hitta och utvärdera alternativa metoder och parametrar för att föreslå förbättrade alternativ.

Automated vehicles (AVs) will be integrated into our society at some point in the future, but when is still up for debate. An extensive amount of research is being completed to understand the communication methods between AVs and other road users sharing the environment to prepare for this future. Currently, researchers are working to understand how different forms of external communication on the AVs will impact vulnerable road user (VRU) interaction. However, within the last 10 years, VRU casualty rates have continued to rise for all classifications of VRUs. Unfortunately, there is no suggestion that pedestrian fatality rates will ever decrease without some intervention. This dissertation aims at understanding the impacts of eHMI across real-world, complex scenarios with AVs and how researchers can apply those future findings to improve VRUs' judgments to today. A series of studies evaluated the necessity and impact of eHMI on AV–VRU interaction, assessed how the visual components of eHMI influenced VRU crossing decisions, and how variations in a real-world environment (multiple vehicles and scenario complexity) impact crossing decision behavior. Two studies examined how eHMI will impact future interactions between AVs and VRUs. Specifically, to understand how to advance the design of these future devices to avoid unintended consequences that may result. Results from these studies found that the presence and condition of eHMI did not influence participants' willingness to cross. Participants primarily relied on the speed and distance of the vehicle to make their crossing decision. It was difficult for participants to focus on the eHMI when multiple vehicles competed for their attention. Participants typically prioritized their focus on the vehicle that was nearest and most detrimental to their crossing path. Additionally, the type of scenario caused participants to make more cautious crossing decisions. However, it did not influence their willingness to cross. The last study applied the learnings from the first two studies to a foundational perception study for current legacy vehicles. These results showed a significant increase in judgment accuracies with a display. Through analysis across overall conclusions from the 3 studies, five critical findings were identified when addressing eHMI and 3 design recommendations, which are discussed in the penultimate section of this work. The results of this dissertation indicate that eHMI improved VRUs' accuracy of perception of change in vehicle speed. eHMI did not significantly impact VRUs crossing decisions. However, the complexity of the traffic scenarios affected the level of caution participants exhibited in their crossing behavior. / Doctor of Philosophy / An extensive amount of research is being completed to understand the communication methods between AVs and other road users sharing the environment to prepare for this future. Currently, researchers are working to understand how different forms of external communication on the AVs will impact vulnerable road user (VRU) interaction. However, within the last 10 years, VRU casualty rates have continued to rise for all classifications of VRUs. Unfortunately, there is no suggestion that pedestrian fatality rates will ever decrease without some intervention. This dissertation aims at understanding the impacts of eHMI across real-world, complex scenarios with AVs and how researchers can apply those future findings to improve VRUs' judgments to today. A series of studies evaluated the necessity and impact of eHMI on AV–VRU interaction, assessed how the visual components of eHMI influenced VRU crossing decisions, and how variations in a real-world environment (multiple vehicles and scenario complexity) impact crossing decision behavior.

Chaque année, des millions de personnes meurent et beaucoup d'autres subissent des séquelles graves à la suite d'accidents de la route. Malgré une multitude d’initiatives, le nombre de cas mortels et d'accidents graves augmente chaque année en engendrant des problèmes préoccupants à la fois sociaux, économiques et sanitaires. En raison de leur nombre élevé et de l'absence de protection personnelle, plus de la moitié de ces décès concerne les usagers vulnérables (en anglais, vulnerable road users - VRU) regroupant les piétons, cyclistes et motocyclistes. Les appareils mobiles, combinés à la technologie de Fog Computing (ou informatique géodistribuée, ou même informatique en brouillard), représentent une solution réaliste à court terme pour les protéger en les avertissant de l’imminence d'un accident de circulation. L’omniprésence des appareils mobiles et leurs capacités de calcul élevées font de ces appareils un élément important à considérer dans les solutions de sécurité routière. Le Fog Computing offre des fonctionnalités adaptées aux applications de sécurité routière, puisqu’il s’agit d’une extension du Cloud Computing permettant de rapprocher les services informatiques, le stockage et le réseau au plus près des utilisateurs finaux. Par conséquent, dans cette thèse, nous proposons une architecture réseau sans infrastructure supplémentaire (PV-Alert) pour des fins de sécurité routière et reposant uniquement sur les appareils mobiles des VRU et des conducteurs sur la route avec l’aide du concept de Fog Computing. Les données géographiques et cinématiques de ces appareils sont collectées et envoyées périodiquement au serveur fog situé à proximité. Le serveur fog traite ces données en exécutant un algorithme de calcul de risque d’accident de circulation et renvoie des notifications en cas d'accident imminent. L’évaluation de cette architecture montre qu’elle est capable de générer des alertes en temps réel et qu’elle est plus performante que d’autres architectures en termes de fiabilité, d’évolutivité et de latence. / Annually, millions of people die and many more sustain non-fatal injuries because of road traffic crashes. Despite multitude of countermeasures, the number of causalities and disabilities owing to traffic accidents are increasing each year causing grinding social, economic, and health problems. Due to their high volume and lack of protective-shells, more than half of road traffic deaths are imputed to vulnerable road users (VRUs): pedestrians, cyclists and motorcyclists. Mobile devices combined with fog computing can provide feasible solutions to protect VRUs by predicting collusions and warning users of an imminent traffic accident. Mobile devices’ ubiquity and high computational capabilities make the devices an important components of traffic safety solutions. Fog computing has features that suits to traffic safety applications as it is an extension of cloud computing that brings down computing, storage, and network services to the proximity of end user. Therefore, in this thesis, we have proposed an infrastructure-less traffic safety architecture that depends on fog computing and mobile devices possessed by VRUs and drivers. The main duties of mobile devices are extracting their positions and other related data and sending cooperative awareness message to a nearby fog server using wireless connection. The fog server estimates collision using a collision prediction algorithm and sends an alert message, if an about-to-occur collision is predicted. Evaluation results shows that the proposed architecture is able to render alerts in real time. Moreover, analytical and performance evaluations depict that the architecture outperforms other related road safety architectures in terms of reliability, scalability and latency. However, before deploying the architecture, challenges pertaining to weaknesses of important ingredients of the architecture should be treated prudently. Position read by mobile devices are not accurate and do not meet maximum position sampling rates traffic safety applications demand. Moreover, continuous and high rate position sampling drains mobile devices battery quickly. From fog computing’s point of view, it confronts new privacy and security challenges in addition to those assumed from cloud computing. For aforementioned challenges, we have proposed new solutions: (i) In order to improve GPS accuracy, we have proposed an efficient and effective two-stage map matching algorithm. In the first stage, GPS readings obtained from smartphones are passed through Kalman filter to smooth outlier readings. In the second stage, the smoothed positions are mapped to road segments using online time warping algorithm. (ii) position sampling frequency requirement is fulfilled by an energy efficient location prediction system that fuses GPS and inertial sensors’ data. (iii) For energy efficiency, we proposed an energy efficient fuzzy logic-based adaptive beaconing rate management that ensures safety of VRUs. (iv) finally, privacy and security issues are addressed indirectly using trust management system. The two-way subjective logic-based trust management system enables fog clients to evaluate the trust level of fog servers before awarding the service and allows the servers to check out the trustworthiness of the service demanders. Engaging omnipresent mobile device and QoS-aware fog computing paradigm in active traffic safety applications has the potential to reduce overwhelming number of traffic accidents on VRUs.

La conduite d’un véhicule industriel est une activité professionnelle complexe qui s’exerce dans un environnement dynamique en constante évolution. Elle nécessite un apprentissage spécifique et se situe dans un cadre réglementaire strict, qui relève aussi bien du code du travail que de la réglementation routière. A ces caractéristiques s’ajoutent de fortes contraintes spatio-temporelles qui imposent aux conducteurs le recours à des stratégies opératoires pour répondre à l’objectif principal de leur activité : le respect des délais de livraison dans des conditions optimales de sécurité, de sûreté et de productivité.Cette thèse traite de l'apport de la psychologie cognitive à la conception de systèmes d'assistance à la conduite de véhicules industriels. Les travaux sont destinés à intégrer, dès la conception des nouveaux systèmes, les contraintes du fonctionnement cognitif humain en situation réelle, ainsi que les besoins et attentes des conducteurs, afin que leur soient proposées des solutions technologiques adaptées et utilisables.La partie appliquée illustre deux dimensions majeures de l'activité de conduite d'un camion : la productivité, au travers de la problématique de l'assistance à l'éco-conduite (projet Conduite Economique Assistée, ADEME- RENAULT TRUCKS) ; la sécurité, au travers de la problématique de l'assistance à la détection et à la protection des usagers vulnérables de la route (projet VIVRE2, ANR-PREDIT05-LUTB).D’un point de vue scientifique, la thèse aboutit à la proposition d’un modèle du fonctionnement humain dans les activités finalisées, complété par un modèle adapté à l’activité de conduite d’un véhicule industriel. Les analyses effectuées en situations réelles enrichissent les connaissances, d’une part, sur les stratégies de conduite appliquées à la conduite rationnelle d’un poids lourd en environnement extra-urbain, et, d’autre part, sur les composantes de l’activité des conducteurs qui effectuent des livraisons en milieu urbain. De plus, les travaux effectués dans le cadre du projet VIVRE2 ont permis de préciser les représentations et les comportements à risque des usagers vulnérables vis-à-vis des camions en ville.D’un point de vue applicatif et ergonomique, les travaux sur simulateur dynamique de conduite ont permis l’évaluation d’une interface homme-machine innovante qui pourrait être adaptée à l’éco-conduite, ainsi que la proposition et l’évaluation de systèmes d’assistance pour garantir la sécurité des usagers vulnérables lors des manœuvres à basse vitesse en milieu urbain. / Driving a truck is a complex professional activity that takes place in a dynamic and constant changing environment. It needs a specific learning and it is set in a strict regulated framework including French labour code (Code du travail) as road regulation. Strong spatio-temporal pressure should be added to those characteristics. These constraints entail to drivers the use of operative strategies to achieve the main objective of their activity: respect of delivery time in optimal conditions of safety, security and productivity.This thesis deals with the contribution of cognitive psychology to the design of driving assistance systems for trucks. Works are intended to integrate, from the design of new systems, the demands of human cognitive functioning in real situation and the needs and expectations of drivers so that adapted and usable technological solutions could be proposed to them.Applied part shows two major dimensions of truck driving activity: productivity through the issue of the eco-driving assistance (“Conduite Economique Assistée, ADEME- RENAULT TRUCKS” project) and safety through the issue of the assistance to detection and protection of vulnerable road users (“VIVRE2, ANR-PREDIT05-LUTB” project).From a scientific point of view, the thesis ends with a proposal of a model of human functioning in finalized activities, of which is added an adapted model of the truck driving activity. The analysis performed in real environment enhance knowledge, on the one hand, on the applied driving strategies to the eco-driving of a truck in extra-urban environment and, on the other hand, on the components of the activity of drivers doing deliveries in urban environment. Moreover, works performed in VIVRE2 project allowed to specify representations and risky behaviours of vulnerable users with relation to trucks in town.From an applicative and ergonomic point of view, works on driving dynamic simulator allowed the evaluation of an innovative man-machine interface which could be adapted to eco-driving and the proposal as well as the evaluation of assistance systems to guarantee safety of vulnerable users during low speed manoeuvres in urban environment.