FACTS - Founded in July 2008 - Meanwhile about to 250 employees. The team structure is characterized by a big number of very experienced engineers - AVL Software and Functions GmbH creates prototyping and serial solutions (software and hardware) for different applications in the fields of for example passenger cars, racing, two wheelers, light and heavy duty vehicles - AVL Software and Functions is the globally responsible competence center for software development inside theAVL group. - 100% integrated into the worldwide AVL network

Cette dissertation modélise et analyse les flux de trafic hétérogènes, avec une attention particulière portée à la circulation de voitures et de deux-roues. L'augmentation du nombre de congestions de trafic a forcé les personnes désirant se déplacer à se diriger vers les le deux-roues (appelé ici PTWs = powered two wheelers), comme les motos, les mopeds et les scooters, du fait de leur facilité de manoeuvre et leur efficacité dans l'espace. L'augmentation du nombre de PTWs combinée au caractère unique de certaines de leurs fonctionnalités a résulté en un trafic complexe, donc les particularités sont difficiles à recréer avec les approches de modélisation existantes. Nous développerons ici un modele analytique permettant de reproduire de manière pertinente les particularités d'un flux de véhicules mêlant à la fois les voitures et les deux-roues. Le trafic se décompose en deux classes de véhicules : les PTWs et les voitures. Les propriétés fondamentales sont déduites en employant une approche "porous flow". On suppose que la vitesse d'un véhicule d’une certaine classe est dictée par les propriétés physiques et motrices du véhicule, ainsi que la distribution d'espace vide sur la route. Nous proposons une méthode d'approximation pour dériver la distribution d'espace vide. Dans le but d'explorer plus largement les caractéristiques du flux de trafic notamment requis par les applications de système de transport intelligent (ITS), nous formulons le modèle dans les cadres lagrangien et eulérien. Puis, nous feront appel à une méthode numérique pour la discrétisation du modèle mathématique. Se basant sur le modèle développé nous analyserons les caractéristiques du flux de trafic pour en identifier les propriétés les plus importantes qui nous permettrons de prédire de futures ITS applications et d'organisations du trafic. La possibilité d'appliquer le modèle pour les différentes ITS applications est illustrée par des exemples. Finalement, le modèle développé est validé à l'aide de l'outil de microsimulation. / This dissertation models and analyzes heterogeneous traffic flow, with a particular focus on mixed traffic flow consisting of cars and two-wheelers. The increase in traffic congestion induces commuters to switch to powered two wheelers (PTWs), i.e. motorcycle, mopeds and scooters, because of their high maneuverability and space efficiency. The growth in number of PTWs, combined with their unique mobility features, results in complex traffic characteristics which are difficult to recreate with the existing modeling approaches. We develop an analytical model that can accurately reproduce the traffic features in a mixed flow of cars and PTWs. The traffic stream is decomposed into two vehicle classes, PTWs and cars. The fundamental properties are derived by employing a porous flow approach. It is assumed that the speed of a vehicle class is dictated by the physical and motion properties of the vehicle class, and the distribution of free spaces on the road. We propose an approximation method to derive the free-space distribution. In order to explore broader aspects of the traffic flow characteristics, notably required by intelligent transport system (ITS) applications, we formulate the model in the Lagrangian and the Eulerian frameworks. Further, we provide a numerical method for the discretization of the mathematical model. We analyze the flow characteristics of mixed PTWs and cars traffic and identify important properties, which give insights for future ITS solutions and traffic policy makers. The applicability of the model for different ITS applications is illustrated. Finally, the developed model is validated using a microsimulation tool.

FACTS - Founded in July 2008 - Meanwhile about to 250 employees. The team structure is characterized by a big number of very experienced engineers - AVL Software and Functions GmbH creates prototyping and serial solutions (software and hardware) for different applications in the fields of for example passenger cars, racing, two wheelers, light and heavy duty vehicles - AVL Software and Functions is the globally responsible competence center for software development inside theAVL group. - 100% integrated into the worldwide AVL network

Contexte : les deux-roues motorisés (2RM) sont en forte évolution et la vulnérabilité de leurs usagers est de plus en plus manifeste. En 2013, dans le monde, les usagers de 2RM ont compté pour 23 % de la mortalité routière, devant les piétons (22 %). Dans ce contexte, la sécurité des usagers de 2RM est devenue une préoccupation sérieuse dans la plupart des pays. Contrairement à beaucoup de problèmes de santé publique, les principaux facteurs de l'insécurité routière en 2RM sont connus. L'enjeu d'aujourd'hui est surtout de quantifier leur effet sur la survenue d'accidents et d'évaluer les effets des quelques dispositifs de protection disponibles. Les objectifs de cette thèse sont de mieux connaitre les problèmes d'interaction entre les conducteurs de 2RM et les automobilistes selon différentes situations accidentelles (en particulier en intersection), de quantifier les effets des facteurs à l'origine de la survenue des accidents issus de la perte de contrôle du 2RM, et de mesurer l'efficacité des dispositifs de protection portés par les usagers de 2RM (casque intégral, blouson de moto, pantalon de moto, gants, bottes ou chaussures montantes et protection dorsale). Données : la réalisation des objectifs de la thèse s'appuie sur les données du projet VOIESUR, les données du Registre des accidents de la circulation du Rhône et les données recueillies au moyen d'une enquête postale réalisée auprès de 7 148 usagers de 2RM accidentés entre 2010 et 2014 identifiés par le Registre du Rhône. Résultats : Le problème de détectabilité des motos au niveau des intersections est confirmé. Dans la même situation d'interaction entre deux véhicules en intersection, un automobiliste a plus de difficulté à détecter une moto qu'à détecter un véhicule léger. Les facteurs suivants sont associés à la survenue des accidents de type perte de contrôle : alcool, type de moto, jour de l'accident, sinuosité de la route, adhérence de la route et vitesse. Nous soulignons le fait qu'une mauvaise adhérence de la route augmente considérablement le risque de perte de contrôle, en particulier lorsque la dégradation de l'adhérence est inattendue pour les motocyclistes en raison de la présence de gravillons, de corps gras, de nids de poule, etc. sur la route. En cas d'accident, les vêtements dédiés à la moto protègent les usagers des blessures. Ils sont efficaces pour éviter les dermabrasions et les plaies cutanées, mais ne semblent pas protéger des blessures plus graves telles que fracture, luxation ou entorse, sauf pour les bottes ou chaussures montantes qui réduisent le risque de fracture de la cheville ou du pied. Concernant les plaques dorsales, aucune efficacité n'a été montrée. Les casques intégraux protègent mieux le visage de l'usager du 2RM comparés aux non-intégraux, alors qu'aucune différence de protection du crâne ou du cerveau n'est mise en évidence entre les deux types de casques. Conclusion : Nos résultats mettent en évidence le problème de détectabilité d'un 2RM par les automobilistes en intersection et l'importance de l'état de la chaussée dans les accidents associés à une perte de contrôle du 2RM par son conducteur. Il est fortement recommandé pour les automobilistes de bien faire attention aux véhicules prioritaires venant de la gauche ou d'en face avant de tourner à gauche, particulièrement aux 2RM venant d'en face. L'amélioration de l'état de la chaussée et une signalisation adaptée représentent aussi un enjeu fort pour la sécurité des usagers de 2RM. Nos résultats soutiennent la recommandation faite par les organismes de sécurité routière du port plus systématique des équipements vestimentaires chez les usagers de 2RM. Enfin, nos résultats encouragent l'utilisation d'un casque intégral chez les usagers de 2RM afin de mieux protéger le visage / Background: Motorized two-wheelers (MTW) are evolving rapidly and the vulnerability of their users is becoming more obvious. MTW users were the most vulnerable road users, accounting for 23 % of all road traffic fatalities worldwide in 2013, in front of pedestrians (22 %). In this context, the safety of MTW users has become a serious concern in most countries. In contrast to many public health problems, the main factors of MTW road safety have been identified. The issue today is to quantify their effects on the occurrence of accidents and to measure the effects of protective devices. The present thesis aims to better understand the interaction problems between MTW drivers and automobilists according to different accident configurations (in particular at intersection), to identify and assess the effect of critical factors on the risk of MTW loss-of-control crashes, and to measure the effectiveness of protective clothing (motorcycle jacket, trousers, gloves, knee-high or ankle boots, back protection) for MTW users. Data: This study used MTW accident data collected in a French project VOIESUR, injury data from the Rhône Registry, plus data collected by means of a postal survey which was conducted among 7148 MTW riders injured between 2010 and 2014 and identified in the Rhône Registry. Results: We confirmed the problem of motorcycle detection for other road users. In the similar conditions, the motorists have more difficulty to detect a motorcycle than a car oncoming, in particular at intersections. The following factors are associated with the occurrence of motorcycle loss-of-control accidents: alcohol use, motorcycle type, weekend vs. weekday, road alignment, road adhesion and traveling speed. We emphasize that poor road adhesion significantly increases the risk of losing control, especially when deteriorated road adhesion is encountered unexpectedly, due to the presence of loose gravel, ice, oil, potholes, etc. on the roadway. In case of accident, motorcycle clothing protects users from injury. It can protect riders against injuries such as dermabrasion and laceration, but not against more serious injuries, such as fracture and sprain, except for boots, which reduce foot-and-ankle fracture risk. No effect of dorsal protectors was shown. Full-face helmets provide significantly greater protection against facial injury than do other helmets. However, no significant difference of protection against skull or brain injury is found between the two types of helmets. Conclusion: Our results highlight the problem of MTW detection for motorists at intersections and the important role of road conditions in the occurrence of accidents resulting from loss of control of MTW. It is recommended for motorists to pay extra attention to priority vehicles oncoming from their left or the opposite direction, before turning left at an intersection, especially to MTW. Regular road maintenance and immediate installment of appropriate warning signs concerning road deterioration are also highly recommended in consideration of MTW safety. Finally, our results support road safety organizations’ recommendation that protective clothing be worn: this should be more systematic for MTW users, the same for the use of full-face helmets

The safety of Powered Two Wheelers (PTWs) is important for public authorities and roadadministrators around the world. Recent official figures show that PTWs are estimated to represent only 2% of the total traffic but represent 30% of total deaths on French roads. However, as these estimated figures are obtained by simply counting the number plates registered, they do not give a true picture of the PTWs on the road at any given moment. This dissertation comes under the project METRAMOTO and is a technical applied research work and deals with two problems: detection of PTWsand the use of a laser scanner to count PTWs in the traffic. Traffic generally contains random vehicles of unknown nature and behaviour such as speed,vehicle interaction with other users on the road etc. Even though there are several technologies that can measure traffic, for example radars, cameras, magnetometers etc, as the PTWs are small-sized vehicles, they often move in between lanes and at quite a high speed compared to the vehicles moving in the adjacent lanes. This makes them difficult to detect. the proposed solution in this research work is composed of the following parts: a configuration to install the laser scanner on the road is chosen and a data coherence method is introduced so that the system is able to detect the road verges and its own height above the road surface. This is validated by simulator. Then the rawd ata obtained is pre-processed and is transform into the spatial temporal domain. Following this, an extraction algorithm called the Last Line Check (LLC) method is proposed. Once extracted, the objectis classified using one of the two classifiers either the Support Vector Machine (SVM) or the k-Nearest Neighbour (KNN). At the end, the results given by each of the two classifiers are compared and presented in this research work. The proposed solution in this research work is a propototype that is intended to be integrated in a real time system that can be installed on a highway to detect, extract, classify and counts PTWs in real time under all traffic conditions (traffic at normal speeds, dense traffic and even traffic jams).

In today’s fast moving world, automobiles are facing challenges in terms of having to survive road accidents, increasing traffic, bad road-conditions and high/express ways. Brake systems play a vital role in controlling the vehicle speed while avoiding road accidents. The conventional brake systems consist of basically an actuator, transmission and frictional parts. This system is difficult for manipulated control by the driver during emergency and panic braking situations. In particular road and environmental conditions, it requires certain skill to have safe and effective brake control, which is always not possible from all drivers. Wheel locking is a predominant phenomenon during panic braking and this will cause vehicle skidding resulting in injuries and road accidents. In the case of a two-wheeler, being a single-track vehicle, skidding is one of the major causes for fatal road accidents due to loss in lateral balance. As the road safety regulations are becoming more stringent, the anti-lock brake systems (ABS) will replace the conventional brake systems in all road vehicles to avoid accidents and to improve vehicle safety. Early ABS systems, developed in the last 100-years, use intermittent and cyclic brake pressure control by sensing the wheel speed or wheel-slip as one of the major control inputs. Regulating the brake pressure with a preset threshold value is another method. These ABS systems have used electronics, or hydraulics or pure mechanical control. However, such ABS are not widely used in two-wheelers and other low cost vehicles till now, because of several limitations identified as follows: High cost, power supply needed for its operation in the case of intermittent and cyclic brake control, susceptibility to failure in the electronics system, interference from RF signals (from cell-phones for example), uneasiness to drivers from pedal pulsations with pedal noise, heavier weight, increased vehicle vibrations and failure modes of wheels due to torsional vibrations. The present research work is carried out to develop a new mechanical ABS concept, which will address most of the above problems. During braking, the change in rider-input force will change wheel reactions. This change is made proportional to the change in rider input force only upto wheel locking. Such a principle is used to develop the new mechanical ABS. The new concept regulates the output force from the ABS, by sensing the dynamic wheel reactions with increase in rider-response. The ABS output force is regulated by one of the following ways: (a) Slipping-down the lever-ratio or (b) preventing the excessive brake input force. Based on the parameters like less number of parts, least weight, simplicity, reliability, efficiency, durability, time-response, etc., the second method (of preventing the excessive brake input force) has been chosen. Further a new concept of ABS interconnecting system is proposed for usage between the front and rear wheels of the vehicle. This interconnecting system will ensure that the two mechanical ABS systems function at any kind of braking-balance between the front and rear applications. An analytical vehicle model has been developed with several input parameters like mass, geometry, inertia, aerodynamic properties, frictions of road and bearing-supports, road gradients, etc. From this analytical model, the dynamic wheel reactions and limiting adhesion of each tyre for various braking conditions are determined and the results are used to design the mechanical ABS. The same analytical model is used to predict the brake performance like stopping distance, vehicle deceleration and the vehicle speed variation for ideal braking conditions. The new ABS is modelled in Pro-E using the inputs from the analytical model. To evaluate the concept, a functional proto-type is built and fitted on a motorcycle. The ABS is evaluated for its functionality and performance at different road (level surface, up-gradients and down gradients) and environmental conditions (dry and wet road conditions). Using the VBOX II, proximate sensors and load-cells fitted on the vehicle, the vehicle stopping distance, wheel slip and pedal force are measured. The results show that wheel locking does not occur under panic driving conditions, which is the primary objective. In addition, the results show a good agreement with the predicted stopping distance and vehicle deceleration from the analytical model. As there is good scope for this new mechanical ABS for use in two-wheelers and other low cost vehicles, further research is needed to make this system work in curvilinear motion & banked surfaces.

La sécurité des deux-roues motorisés (2RM) constitue un enjeu essentiel pour les pouvoirs publics et les gestionnaires routiers. Si globalement, l’insécurité routière diminue sensiblement depuis 2002, la part relative des accidents impliquant les 2RM a tendance à augmenter. Ce constat est résumé par les chiffres suivants : les 2RM représentent environ 2 % du trafic et 30 % des tués sur les routes.On observe depuis plusieurs années une augmentation du parc des 2RM et pourtant il manque des données et des informations sur ce mode de transport, ainsi que sur les interactions des 2RM avec les autres usagers et l'infrastructure routière. Ce travail de recherche appliquée est réalisé dans le cadre du projet ANR METRAMOTO et peut être divisé en deux parties : la détection des2RM et la détection des objets routiers par scanner laser. Le trafic routier en général contient des véhicules de nature et comportement inconnus, par exemple leurs vitesses, leurs trajectoires et leurs interactions avec les autres usagers de la route. Malgré plusieurs technologies pour mesurer le trafic,par exemple les radars ou les boucles électromagnétiques, il est difficile de détecter les 2RM à cause de leurs petits gabarits leur permettant de circuler à vitesse élevée et ce même en interfile. La méthode développée est composée de plusieurs sous-parties: Choisir une configuration optimale du scanner laser afin de l’installer sur la route. Ensuite une méthode de mise en correspondance est proposée pour trouver la hauteur et les bords de la route. Le choix d’installation est validé par un simulateur. A ces données brutes, la méthode de prétraitement est implémentée et une transformation de ces données dans le domaine spatio-temporel est faite. Après cette étape de prétraitement, la méthode d’extraction nommée ‘Last Line Check (LLC)’ est appliquée. Une fois que le véhicule est extrait, il est classifié avec un SVM et un KNN. Ensuite un compteur est mis en œuvre pour compter les véhicules classifiés. A la fin, une comparaison de la performance de chacun de ces deux classifieurs est réalisée. La solution proposée est un prototype et peut être intégrée dans un système qui serait installé sur une route au trafic aléatoire (dense, fluide, bouchons) pour détecter, classifier et compter des 2RM en temps réel. / The safety of Powered Two Wheelers (PTWs) is important for public authorities and roadadministrators around the world. Recent official figures show that PTWs are estimated to represent only 2% of the total traffic but represent 30% of total deaths on French roads. However, as these estimated figures are obtained by simply counting the number plates registered, they do not give a true picture of the PTWs on the road at any given moment. This dissertation comes under the project METRAMOTO and is a technical applied research work and deals with two problems: detection of PTWsand the use of a laser scanner to count PTWs in the traffic. Traffic generally contains random vehicles of unknown nature and behaviour such as speed,vehicle interaction with other users on the road etc. Even though there are several technologies that can measure traffic, for example radars, cameras, magnetometers etc, as the PTWs are small-sized vehicles, they often move in between lanes and at quite a high speed compared to the vehicles moving in the adjacent lanes. This makes them difficult to detect. the proposed solution in this research work is composed of the following parts: a configuration to install the laser scanner on the road is chosen and a data coherence method is introduced so that the system is able to detect the road verges and its own height above the road surface. This is validated by simulator. Then the rawd ata obtained is pre-processed and is transform into the spatial temporal domain. Following this, an extraction algorithm called the Last Line Check (LLC) method is proposed. Once extracted, the objectis classified using one of the two classifiers either the Support Vector Machine (SVM) or the k-Nearest Neighbour (KNN). At the end, the results given by each of the two classifiers are compared and presented in this research work. The proposed solution in this research work is a propototype that is intended to be integrated in a real time system that can be installed on a highway to detect, extract, classify and counts PTWs in real time under all traffic conditions (traffic at normal speeds, dense traffic and even traffic jams).

Electrification is widely considered as a viable strategy for reducing the oil dependency and environmental impacts of road transportation. In pursuit of this strategy, most attention has been paid to electric cars. However, substantial, yet untapped, potentials could be realized in urban areas through the large-scale introduction of electric two-wheelers. Here, we review the environmental, economic, and social performance of electric two-wheelers, demonstrating that these are generally more energy efficient and less polluting than conventionally-powered motor vehicles. Electric two-wheelers tend to decrease exposure to pollution as their environmental impacts largely result from vehicle production and electricity generation outside of urban areas. Our analysis suggests that the price of e-bikes has been decreasing at a learning rate of 8%. Despite price differentials of 5000 ± 1800 EUR2012 kW h−1 in Europe, e-bikes are penetrating the market because they appear to offer an apparent additional use value relative to bicycles. Mid-size and large electric two-wheelers do not offer such an additional use value compared to their conventional counterparts and constitute niche products at price differentials of 700 ± 360 EUR2012 kW−1 and 160 ± 90 EUR2012 kW−1, respectively. The large-scale adoption of electric two-wheelers can reduce traffic noise and road congestion but may necessitate adaptations of urban infrastructure and safety regulations. A case-specific assessment as part of an integrated urban mobility planning that accounts, e.g., for the local electricity mix, infrastructure characteristics, and mode-shift behavior, should be conducted before drawing conclusions about the sustainability impacts of electric two-wheelers.

L’accidentalité des conducteurs de 2RM est au cœur des préoccupations de sécurité routière. Ce travail de thèse vise à apporter des connaissances sur les différences de sexe et de conformité aux stéréotypes de sexe au sein de cette communauté très masculine. Il a été montré que les femmes motocyclistes avaient des taux d’accidents corporels ou mortels bien inférieurs à ceux des hommes. Les résultats montrent que les comportements à risque accidentels des hommes et des femmes motocyclistes sont proches, hormis pour les comportements les plus risqués. Il a aussi été montré que le type de motocyclette avait un effet plus important que le sexe sur les comportements à risques accidentels. De plus, il a été montré que les motocyclistes se conforment aux stéréotypes de sexe qui leurs sont associés et que la masculinité renforce la prise de risque et la transgression des règles, cette relation étant expliquée par les motivations à conduire un 2RM. Enfin, ce travail a montré que les stéréotypes de sexe associés à la conduite d’une motocyclette existent déjà chez les adolescents dès 11 ans. Ce travail de thèse montre donc des différences significatives entre hommes et femmes conducteurs de 2RM, autant au niveau de leur accidentalité que de leurs prises de risque. De plus, des stéréotypes de sexe existent bien pour cette population spécifique d’usagers de la route. Ces travaux permettent d’avoir une connaissance plus fine des comportements des conducteurs de 2RM, et d’enrichir la réflexion sur des actions possibles en matière d’éducation routière, en ciblant les sous-populations les plus à risque chez les conducteurs de 2RM. / The powered two-wheelers (PTW) riders’ accidentality is at the heart of road safety issues. This PhD thesis is part of a comprehensive approach to generate knowledge on sex differences and sex stereotypes conformity within this very masculine stereotyped community. It first showed that female motorcyclists have much lower injury crashes and fatalities rates than males. A first study showed that males declared more intentional risky behaviors and female more non-intentional risky behaviors. A second study showed that the PTW type chosen had a more important effect on the aberrant behaviors than sex. A third study showed that individuals who conformed to masculine stereotypes declared more violations than those who conformed to feminine stereotypes (declared more lapses), whatever their sex. Motivations to ride a PTW explaining this relation. Finally, this work showed that sex stereotypes associated with motorcycle riding already existed on the adolescent population, from the age of 11, even if they are themselves moped riders or if at least one of their parents is a rider. As a conclusion, significant differences between male and female PTW riders were revealed, in terms of accidentology and risk taking. These differences are linked to the riders’ conformity to their sex group and to the effects of this conformity on their motivations to ride a PTW. Moreover, it also showed that sex stereotypes exist for this specific road users’ population. This work led to a more detailed understanding of PTW riders’ aberrant behaviors, and to enrich the thinking for actions with regard to road safety education and prevention.

L'objectif de cette thèse est de développer des outils d'analyse de données recueillies sur les deux roues motorisés (2RMs). Dans ce cadre, des expérimentations sont menées sur des motos instrumentés dans un contexte de conduite réelle incluant à la fois des conduites normales dites naturelles et des conduites à risques (presque chute et chute). Dans la première partie de la thèse, des méthodes d'apprentissage supervisé ont été utilisées pour la classification de situations de conduite d'un 2RM. Les approches développées dans ce contexte ont montré l'intérêt de prendre en compte l'aspect temporel des données dans la conduite d'un 2RM. A cet effet, nous avons montré l'efficacité des modèles de Markov cachés. La seconde partie de cette thèse porte sur le développement d'outils de détection et de classification hors ligne des évènements critiques de conduite, ainsi que, la détection en ligne des situations de chute d'un 2RM. L'approche proposée pour la détection hors ligne des évènements critiques de conduite repose sur l'utilisation d'un modèle de mélange de densités gaussiennes à proportions logistiques. Ce modèle sert à la segmentation non supervisée des séquences de conduite. Des caractéristiques extraites du paramètre du modèle de mélange sont utilisées comme entrées d'un classifieur pour classifier les évènements critiques. Pour la détection en ligne de chute, une méthode simple de détection séquentielle d'anomalies basée sur la carte de contrôle MCUSUM a été proposée. Les résultats obtenus sur une base de données réelle ont permis de montrer l'efficacité des méthodologies proposées à la fois pour la classification de situations de conduite et à la détection des évènements critiques de conduite / This thesis aims to develop framework tools for analyzing and understanding the riding of Powered Two Wheelers (PTW). Experiments are conducted using instrumented PTW in real context including both normal (naturalistic) riding behaviors and critical riding behaviors (near fall and fall). The two objectives of this thesis are the riding patterns classification and critical riding events detection. In the first part of this thesis, a machine-learning framework is used for riding pattern recognition problem. Therefore, this problem is formulated as a classification task to identify the class of riding patterns. The approaches developed in this context have shown the interest to take into account the temporal aspect of the data in PTW riding. Moreover, we have shown the effectiveness of hidden Markov models for such problem. The second part of this thesis focuses on the development of the off-line detection and classification of critical riding events tools and the on-line fall detection. The problem of detection and classification of critical riding events has been performed towards two steps: (1) the segmentation step, where the multidimensional time of data were modeled and segmented by using a mixture model with quadratic logistic proportions; (2) the classification step, which consists in using a pattern recognition algorithm in order to assign each event by its extracted features to one of the three classes namely Fall, near Fall and Naturalistic riding. Regarding the fall detection problem, it is formulated as a sequential anomaly detection problem. The Multivariate CUmulative SUM (MCUSUM) control chart was applied on the data collected from sensors mounted on the motorcycle. The obtained results on a real database have shown the effectiveness of the proposed methodology for both riding pattern recognition and critical riding events detection problems