Rozprawy doktorskie na temat „Sécurité des piétons”
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Pécot, Marion. "Analyse du respect de la priorité piétonne et de l’environnement de huit passages pour piétons à Montréal". Mémoire, Université de Sherbrooke, 2018. http://hdl.handle.net/11143/11907.
Pełny tekst źródłaSolt, Jordan. "La navigation urbaine des enfants-piétons : approche développementale et ergonomique". Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0398.
Pełny tekst źródłaEach year, lots of pedestrian children get injured by vehicles, in spite of efforts made to improve vehicles and safety infrastructures.These improvements have drastically reduced damages on casualties, though the study of pedestrian behaviour remains crucial since most collisions are caused by pedestrian behaviour themselves. In order to understand mental processes and behaviours involved during movement in an urban context, four types of studies dealing with pedestrian children behaviours were analysed : (1) studies about accident-prone circumstances and factors, (2) studies about most likely key-moment for accidents to occur, (3) studies about key competencies needed by pedestrians to move safely in urban traffic, and finally (4), most recent studies about the perception of risk. With the aim of having a comprehensive approach, attention was also drawn on mechanisms that could improve pedestrians' skills.Therefore, this thesis' goals are multiple. First, to define what a children would look at when moving across urban traffic. Second, to understand how behaviours toward the search for information vary. Finally, to measure inter- and intra-individual differences during the decision-making process of pedestrian children. The empirical approach of this thesis relies on three complementary studies, mixing both empirical and in-the-field approach. The first study involved 125 7-to-8 year old children, who were attenting a road-awareness-day. Children were asked to answer a question with a drawing. The purpose of this first study was to gather qualitative data about how pedestrian children perceive the urban environment. The second study was done on 62 attendees, including 21 adults and 41 3-to-11 year old children. The protocol consisted in showing attendees photographs, and asking them do decide to cross the street or not. The purpose of this second study was to collect eye-based and decision-making-time data, in order to highlight the link between visual exploration and decision-making process. The thirs study focused specifically on pedestrian children's decision-making process, using mental chronometry. An experimentation was led on 255 5-to-11 year old participants. The protocol was also about asking attendees to make a decision based on photographs; but this time with a varying informational density. All results of the studies mentioned above will be summarized in 3 main topics which are : pedestrians' inhibition mechanisms, information sources (including other people), and finally, training techniques aimed for pedestrian children
Mansouri, Nabila. "Approche automatique à base de traitement d'images pour l'analyse comportementale de piétons âgés lors de la traversée d'une rue". Thesis, Valenciennes, 2017. http://www.theses.fr/2017VALE0034/document.
Pełny tekst źródłaRoad traffic has become more and more intense. Such as situation with thelack of attention of pedestrians are the two major causes of the increase in road accidents. In France, 16% of road accidents in 2016 involve at least one pedestrian and each year about 800 pedestrians are killed in a traffic accident. In addition, the proportion of pedestrian deaths having over 65 years old is up to 13% between 2014 and 2016. In fact, this thesis proposes a probabilistic approach to recognize pedestrians’ behavior (risky or secure) when crossing the street. This approach consists of two main layers: a low layer, based on computer vision techniques, for collecting pedestrian and traffic parameters and a high layer, based on the Bayesian Network, for behavior prediction. Several contributions and improvements are proposed for the construction of such an approach, whether at the level of the low layer (detection and tracking process) or at the level of the upper layer (management of the uncertainties of the vision sensors and the correlation of heterogeneous and varied parameters)
Hamdoun, Omar. "Détection et ré-identification de piétons par points d'intérêt entre caméras disjointes". Phd thesis, École Nationale Supérieure des Mines de Paris, 2010. http://pastel.archives-ouvertes.fr/pastel-00566417.
Pełny tekst źródłaAh-Tchine, Emeline. "Education et objets innovants : études proactives des préconceptions des piétons, des décisions de traversée et des systèmes d’interaction des voitures autonomes". Thesis, Université Grenoble Alpes, 2020. https://thares.univ-grenoble-alpes.fr/2020GRALH019.pdf.
Pełny tekst źródłaAcademic syllabi need to be constantly restructured to accommodate controversial topics emerging in everyday life. These subjects are gathered under the concept of “education of…”. Socially acute questions is a field of research which identifies potential subjects which may fit under the label of “education of…”. Regarding road safety education, the development of the autonomous car is appropriate to these socially acute questions. In order to consider this new object in road safety education and to provide recommendations, the objective of this thesis is to understand the interaction with this object and observe the behaviour towards the object. Four empirical studies took place in order to gain knowledge of the interaction with this object. In the first study, the objective was to explore the preconceptions on the nature and functionalities of the autonomous car. One hundred eighty participants were recruited to answer a three parts questionnaire. Five profiles were found and recommendations were given for each profile. In the second study, the goal was to study the influence of the type of car on road crossing decisions and the feeling of safety of pedestrians. Forty-five participants took part in a road crossing task composed of three street scenes with four configurations of pedestrian road infrastructures (zebra crossings and pedestrian traffic lights). Results showed a lower percentage of positive road crossing decisions in front of autonomous cars when taking into account trustworthiness. In a third study, in focus groups, the objective was to create interaction systems with autonomous car. Two systems were selected, the first informs pedestrians on the speed of the car and the latter gives advice to the pedestrian on appropriate behaviour using pedestrian traffic lights. We evaluated the comprehension of these interaction systems with 200 participants. The two systems were shown either as static pictures or as dynamic video clips, and comprehension was assessed with open-ended and multiple choice questions. Both systems purposefully conveyed the intended message, however the inform system led to more alternative explanations. The advice system is the most relevant for pedestrian rule compliance for road crossing decision. Then, in a last study, using virtual reality, 84 participants made road-crossing decisions in front of an autonomous car equipped with either an information, an advice or no communication system. The advice system induced less road crossing decision especially when no zebra nor pedestrian light were available. Each study answer a specific question which allows us to characterize the interaction between pedestrians and autonomous car before its implementation. The results for each study is discussed and theoretical and practical implications are provided
Leyrit, Laetitia. "Reconnaissance d'objets en vision artificielle : application à la reconnaissance de piétons". Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2010. http://tel.archives-ouvertes.fr/tel-00626492.
Pełny tekst źródłaAbramson, Yotam. "AdaBoost/GA et filtrage particulaire: La vision par ordinateur au service de la sécurité routière". Phd thesis, École Nationale Supérieure des Mines de Paris, 2005. http://pastel.archives-ouvertes.fr/pastel-00001606.
Pełny tekst źródłaHamdane, Hedi. "Improvement of pedestrian safety : response of detection systems to real accident scenarios". Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4091.
Pełny tekst źródłaThe scope of this research concerns pedestrian active safety. Several primary safety systems have been developed for vehicles in order to detect a pedestrian and to avoid an impact. These systems analyse the forward path of the vehicle through the processing of images from sensors. If a pedestrian is identified on the vehicle trajectory, these systems employ emergency braking and some systems may potentially employ emergency steering. Methods for assessing the effectiveness of these systems have been developed. But, it appears difficult to determine the relevance of these systems in terms of pedestrian protection. The general objective of this research was to test the response of these systems in many accident configurations.The methodology consisted of coupling the vehicle dynamic behaviour with a primary safety system in order to confront these systems to real accident configurations. The relevance of these systems is studied by verifying the feasibility of deploying an autonomous emergency manoeuvre during the timeline of the accident and according to the vehicle dynamic capabilities: i.e. verifying the possibilities in terms of crash avoidance. From these accident reconstructions and simulation, factors relevant to the primary safety of pedestrians were deduced
Zhao, Xiaoyuan. "Assessing pedestrian decision making in the presence of automated vehicles : mitigating risks for safer urban environment". Electronic Thesis or Diss., Université Paris Cité, 2023. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=6155&f=67686.
Pełny tekst źródłaEach year, around 1.35 million fatalities occur on roads worldwide. Of particular concern is the fact that over a quarter of these fatalities comprise vulnerable road users, notably pedestrians and cyclists. The advancement of Automated vehicles (AVs) technology, particularly with full automation, is envisioned to reduce the number of crashes by eliminating human errors in driving. However, the introduction of these vehicles into the existing traffic system necessitates their harmonious coexistence with human road users, including pedestrians. Consequently, the integration of AVs may introduce a new set of road safety concerns originating from potential human errors/violations in interactions with this emergent technology. To increase the likelihood of achieving safe and efficient interactions between AVs and pedestrians, the function of this system must be optimized by identifying and addressing human factor related risks and challenges. At the center of the human factors-related challenges concerning pedestrian-AV interaction is underlined by the fact that pedestrian behavior is extremely flexible and influenced by a multitude of contextual factors such as built environment, as well as psychological factors such as risk perception. Moreover, it is reasonable to expect that pedestrians may adapt to new behavior patterns in response to the introduction of AVs. For these reasons, it is essential to understand pedestrians' perceptions about AVs and behavioral responses when interacting with them within diverse road contexts, all while considering the underlying psychological mechanisms at play. This nuanced understanding is a prerequisite for the design of safe, trustworthy, and acceptable AVs, thereby facilitating harmonious road sharing between pedestrians and these vehicles. This PhD work, therefore, focuses on the interactions between AVs and pedestrians from the perspective of pedestrians. It includes three studies, each focusing on different contexts in which pedestrian-AV interactions take place. Using an online survey, the first study seeks to understand pedestrians' perceptions and beliefs about AVs as influential factors motivating their intention to take risks when crossing road in front of AVs, particularly in time-sensitive situations. The second study explores utilizes a video-based experiment to assess the influence of external Human-Machine Interfaces (eHMIs) on pedestrians' decision-making process, specifically under conditions of high mental workload, during interactions with AVs. The last study performs a virtual reality (VR) experiment to further investigate the process of which pedestrians acquire knowledge and skills to interact with AVs, potentially influenced by other pedestrians. Collectively, findings of the three studies show that AVs and their interaction strategies (i.e. eHMIs) may have the potential to lead pedestrians to make decisions that are less safe or less appropriate in specific contexts. These findings shed light on the potential risks and challenges associated with the deployment of AVs and eHMI systems in real-world traffic scenarios
Fayad, Fadi. "Gestion de la confiance dans un système de fusion multisensorielle : application à la détection de piétons en situations routières". Compiègne, 2009. http://www.theses.fr/2009COMP1795.
Pełny tekst źródłaThis study is a contribution to the advanced driver assistance systems (ADAS), mainly in the domain of road obstacles detection. Using data provided by one or more sensors embarked on a road vehicle, we're trying to identify and track mobile obstacles, thus allowing an automatic assistance which is adapted to the situation. For such data fusion system, the reliability of objects detection and recognition is very important; this is why we propose to manage the confidence in different stages of the process: detection, recognition and tracking. While tracking objects, we propose a technique to update the confidence in detection and recognition using belief functions. Pedestrian detection, which is the heart of the project LOVe (Logiciel d'Observation des Vulnérables), represents a particular case of this study for which a real time embedded system is developed to detect, identify and track pedestrians. The system is integrated in CARMEN, the experimental vehicle of HEUDIASYC laboratory
Caffier, Delphine. "La traversée de rue : anticipation chez le piéton âgé et perturbation de l'initiation". Thesis, Valenciennes, 2018. http://www.theses.fr/2018VALE0038.
Pełny tekst źródłaRésumé en anglais non disponible
Pecol, Philippe. "Modélisation 2D discrète du mouvement des piétons : application à l'évacuation des structures du génie civil et à l'interaction foule-passerelle". Phd thesis, Université Paris-Est, 2011. http://pastel.archives-ouvertes.fr/pastel-00674774.
Pełny tekst źródłaDelzenne, Julie. "La traversée de rue chez le piéton sénior : conception d'un simulateur, étude biomécanique et comportementale". Phd thesis, Université de Valenciennes et du Hainaut-Cambresis, 2013. http://tel.archives-ouvertes.fr/tel-00977405.
Pełny tekst źródłaAbakar, Issakha Souleymane. "Algorithms for the detection and localization of pedestrians and cyclists using new generation automotive radar systems". Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S159.
Pełny tekst źródłaIn response to the persistently high number of deaths provoked by road crashes, the automotive industry has promoted safety as a major topic in their global activity. Automotive radars have been transformed from being simple sensors for comfort vehicle, to becoming essential elements of safety standard. The design of new generations automotive radars has to face various constraints and generally proposes a compromise between reliability, robustness, manufacturability, high-performance and low cost. The main objective of this PhD thesis is to design algorithms for the detection and localization of pedestrians and cyclists using new generation automotive radars. We propose an optimal non-uniform antenna array architecture and some high resolution spectral estimation methods to accurately estimate the position of objects from the direction of arrival (DOA) of their responses to the radar. These techniques are adapted to the proposed antenna array architecture and the performance is evaluated using both simulated and real automotive radar data, acquired in the frame of specific scenarios. We propose a collision target detector, based on the orthogonality of angle-Doppler subspaces, whose main goal is to identify lateral targets, whose trajectory features represent potentially a danger of collision. A target attribute calculation method is also developed and classification algorithm is proposed to classify pedestrian, cyclists and vehicles. This classification algorithm is evaluated and validated using real automotive radar data with several scenarios
Merdrignac, Pierre. "Système coopératif de perception et de communication pour la protection des usagers vulnérables". Thesis, Paris, ENMP, 2015. http://www.theses.fr/2015ENMP0037/document.
Pełny tekst źródłaCooperative intelligent transportation systems (C-ITS) have the opportunity to enhance road safety, especially the safety of vulnerable road users (VRU), e.g., pedestrians and cyclists. Road accidents are mainly due to vehicles' and VRUs' inability to detect the danger before a collision cannot be avoided.We introduce a perception system based on laser and camera sensors to estimate the state of VRUs located around the vehicle. A multi-class classification of road obstacles based on laser data has been developed using statistical machine learning and Bayesian estimation.We propose an architecture for vehicles-to-pedestrians (V2P) communication which considers the weak energy resources of the devices carried by pedestrians such as smartphones. Our solution is relying on the standards defined by ETSI ITS architecture for vehicular communication and proposes geographical dissemination for V2P communication.A cooperative perception/communication system can deal with scenarios which are becoming more and more complex by combining the ability of perception to estimate the dynamic state of detected obstacles and the ability of communication to exchange a rich content between distant users. We introduce a multi-hypotheses fusion between perception and communication information and a smartphone application dedicated to protect VRUs from road danger.The solutions proposed during this thesis are evaluated on real data. We carried out real experiments on INRIA campus demonstrating the assets of a cooperative system for the protection of vulnerable road users
Jalew, Esubalew Alemneh. "Fog Computing based traffic Safety for Connected Vulnerable Road Users". Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCK057/document.
Pełny tekst źródłaAnnually, 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
Phan, Minh Tien. "Estimation of driver awareness of pedestrian for an augmented reality advanced driving assistance system". Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2280/document.
Pełny tekst źródłaAugmented reality (AR) can potentially change the driver’s user experience in significant ways. In contrast of the AR applications on smart phones or tablets, the Head-Up-Displays (HUD) technology based on a part or all wind-shield project information directly into the field of vision, so the driver does not have to look down at the instrument which maybe causes to the time-critical event misses. Until now, the HUD designers try to show not only basic information such as speed and navigation commands but also the aids and the annotations that help the driver to see potential dangers. However, what should be displayed and when it has to be displayed are still always the questions in critical driving context. In another context, the pedestrian safety becomes a serious society problem when half of traffic accidents around the world are among pedestrians and cyclists. Several advanced Pedestrian Collision Warning Systems (PCWS) have been proposed to detect pedestrians using the on-board sensors and to inform the driver of their presences. However, most of these systems do not adapt to the driver’s state and can become extremely distracting and annoying when they detect pedestrian. For those reasons, this thesis focuses on proposing a new concept for the PCWS using AR (so called the AR-PCW system). Firstly, for the «When» question, the display decision has to take into account the driver’s states and the critical situations. Therefore, we investigate the modelisation of the driver’s awareness of a pedestrian (DAP) and the driver’s unawareness of a pedestrian (DUP). In order to do that, an experimental approach is proposed to observe and to collect the driving data that present the DAP and the DUP. Then, the feature-based algorithms, the data-driven models based on the discriminative models (e.g. Support Vector Machine) or the generative models (e.g. Hidden Markov Model) are proposed to recognize the DAP and the DUP. Secondly, for the «What» question, our proposition is inspired by the state-of-the-art on the AR in the driving context. The dynamic bounding-box surrounding the pedestrian and the static danger panel are used as the visual aids. Finally, in this thesis, we study experimentally the benefits and the costs of the proposed AR-PCW system and the effects of the aids on the driver. A fixed-based driving simulator is used. A limited display zone on screen is proposed to simulate the HUD. Twenty five healthy middle-aged licensed drivers in ambiguous driving scenarios are explored. Indeed, the heading-car following is used as the main driving task whereas twenty three pedestrians appear in the circuit at different moment and with different behaviors. The car-follow task performance and the awareness of pedestrian are then accessed through the driver actions. The objective results as well as the subjective results show that the visual aids can enhance the driver’s awareness of a pedestrian which is defined with three levels: perception, vigilance and anticipation. This work has been funded by a Ministry scholarship and was carried out in the framework of the FUI18 SERA project, and the Labex MS2T which is funded by the French Government, through the program ”Investments for the future” managed by the National Agency for Research (Reference ANR-11-IDEX-0004-02)
Ngako, Pangop Estelle. "Approche bayésienne de fusion d'informations pour la reconnaissance d'objets routiers : application au cas du piéton". Clermont-Ferrand 2, 2009. http://www.theses.fr/2009CLF21927.
Pełny tekst źródłaZhou, Dingfu. "Vision-based moving pedestrian recognition from imprecise and uncertain data". Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP2162/document.
Pełny tekst źródłaVision-based Advanced Driver Assistance Systems (ADAS) is a complex and challenging task in real world traffic scenarios. The ADAS aims at perceiving andunderstanding the surrounding environment of the ego-vehicle and providing necessary assistance for the drivers if facing some emergencies. In this thesis, we will only focus on detecting and recognizing moving objects because they are more dangerous than static ones. Detecting these objects, estimating their positions and recognizing their categories are significantly important for ADAS and autonomous navigation. Consequently, we propose to build a complete system for moving objects detection and recognition based on vision sensors. The proposed approach can detect any kinds of moving objects based on two adjacent frames only. The core idea is to detect the moving pixels by using the Residual Image Motion Flow (RIMF). The RIMF is defined as the residual image changes caused by moving objects with compensated camera motion. In order to robustly detect all kinds of motion and remove false positive detections, uncertainties in the ego-motion estimation and disparity computation should also be considered. The main steps of our general algorithm are the following : first, the relative camera pose is estimated by minimizing the sum of the reprojection errors of matched features and its covariance matrix is also calculated by using a first-order errors propagation strategy. Next, a motion likelihood for each pixel is obtained by propagating the uncertainties of the ego-motion and disparity to the RIMF. Finally, the motion likelihood and the depth gradient are used in a graph-cut-based approach to obtain the moving objects segmentation. At the same time, the bounding boxes of moving object are generated based on the U-disparity map. After obtaining the bounding boxes of the moving object, we want to classify the moving objects as a pedestrian or not. Compared to supervised classification algorithms (such as boosting and SVM) which require a large amount of labeled training instances, our proposed semi-supervised boosting algorithm is trained with only a few labeled instances and many unlabeled instances. Firstly labeled instances are used to estimate the probabilistic class labels of the unlabeled instances using Gaussian Mixture Models after a dimension reduction step performed via Principal Component Analysis. Then, we apply a boosting strategy on decision stumps trained using the calculated soft labeled instances. The performances of the proposed method are evaluated on several state-of-the-art classification datasets, as well as on a pedestrian detection and recognition problem.Finally, both our moving objects detection and recognition algorithms are tested on the public images dataset KITTI and the experimental results show that the proposed methods can achieve good performances in different urban scenarios
Morency, Patrick. "Potentiel d’une approche populationnelle orientée vers la reconfiguration des environnements urbains pour améliorer la sécurité des piétons". Thèse, 2010. http://hdl.handle.net/1866/4449.
Pełny tekst źródłaINTRODUCTION: In an urban environment, improving pedestrian safety is a public health challenge. For every death attributable to road injuries, there are hundreds of injured people and, in richer countries, decreases in the number of pedestrian deaths may reflect a reduction of walking as a mode of transportation. The predominant preventive strategies have limited or no effect on traffic volume, which is the most important predictor of the number of pedestrians injured by motor vehicles. Moreover, environmental interventions are usually limited to sites that have had the greatest number of deaths or injuries. The purpose of this thesis is to describe the contribution of environmental factors such as traffic volume, local walking practices and street geometry, on the number and the distribution of pedestrian injuries in an urban setting. METHOD: The design of the study is descriptive and cross-sectional. The main data sources were Urgences-santé ambulance service records (road injuries), the Origin-Destination survey (traffic volume), the Geobase for the Montreal road network (street geometry) and the census of Canada (local walking practices, socioeconomic status). The descriptive analyses included map locations (x, y coordinates) for all collision sites. Multi-level regression models nested intersections in census sectors and in boroughs. RESULTS: The descriptive analyses showed a great deal of dispersion of collision sites within neighbourhoods. The multivariate analyses showed the significant effects, independent of traffic volume, of the presence of an artery and of a fourth leg at the intersection, and of pedestrian volume in the neighbourhood, on the number of pedestrian injuries at intersections. The multi-level analysis showed extensive spatial variation in the effect of traffic volume. This spatial variation in the number of casualties, and the socioeconomic gradient observed, were in large part explained by traffic volume, the presence of an artery and of a fourth leg at the intersection. DISCUSSION: The great dispersion of collision sites supports an approach which is not limited to sites with the highest number of injured pedestrians. This thesis suggests that preventive strategies based on environmental and population approaches could considerably reduce the number of injured pedestrians , as well as road injury inequalities across urban neighbourhoods.
Cloutier, Marie-Soleil. "Les accidents de la route impliquant des enfants piétons : analyse spatiale des risques potentiels et des risques perçus pour une meilleure prévention". Thèse, 2008. http://hdl.handle.net/1866/6520.
Pełny tekst źródłaHamdane, Hédi. "Improvement of pedestrian safety : response of detection systems to real accident scenarios". Thesis, 2016. http://www.theses.fr/2016AIXM4091.
Pełny tekst źródłaThe scope of this research concerns pedestrian active safety. Several primary safety systems have been developed for vehicles in order to detect a pedestrian and to avoid an impact. These systems analyse the forward path of the vehicle through the processing of images from sensors. If a pedestrian is identified on the vehicle trajectory, these systems employ emergency braking and some systems may potentially employ emergency steering. Methods for assessing the effectiveness of these systems have been developed. But, it appears difficult to determine the relevance of these systems in terms of pedestrian protection. The general objective of this research was to test the response of these systems in many accident configurations.The methodology consisted of coupling the vehicle dynamic behaviour with a primary safety system in order to confront these systems to real accident configurations. The relevance of these systems is studied by verifying the feasibility of deploying an autonomous emergency manoeuvre during the timeline of the accident and according to the vehicle dynamic capabilities: i.e. verifying the possibilities in terms of crash avoidance. From these accident reconstructions and simulation, factors relevant to the primary safety of pedestrians were deduced