Communications par Lumière Visible et Radio pour la Conduite Coopéraive Autonome: application à la conduite en convois.

By realizing both low-cost implementationand dual functionality, VLC has becomean outstanding intriguing supportivetechnology by using the vehicular existedinfrastructure.This thesis aims to contribute to theautonomous vehicular communicationand urban mobility improvements. Thework addresses the main radio-basedV2V communication limitations and challengesfor ITS hard-safety applicationsand intends to deploy the vehicular lightingsystem as a supportive communicationsolution for platooning of IVCenabledautonomous vehicles. The ultimateobjectives of this Ph.D. researchare to integrate the VLC system withinthe existing C-ITS architecture by developinga VLC prototype, together withsufficient hand-over algorithms enablingVLC, RF, and perception-based solutionsin order to ensure the maximumsafety requirements and the continuousinformation exchange between vehicles.The feasibility and efficiency of thesystem implementation and hand-overalgorithms were subjects to deep investigationsusing computer simulators andtest-bed that considers applications ofautomated driving. In addition to the improvementin road capacity when platoonformations are used. The carried outsimulations followed-up by experimentalresults proved that the integration of VLCwith the existed RF solutions lead to adefinite benefit in the communicationchannel quality and safety requirementsof a platooning system when a properhand-over algorithm is used.La communication par lumière visibleVLC est devenue une technologie attractivevu qu’elle assure une implémentationà faible coût et une doublefonctionnalité. En effet, elle permetd’utiliser l’infrastructure déjà existantesur le véhicule à savoir les lampesd’arrière et frontales comme des unitésde transmission. Cette thèse s’intéresseà rendre plus efficace les communicationsdes véhicules autonomes ainsi quela gestion de la mobilité urbaine. Nousnous intéressons tout d’abord aux principaleslimitations des communicationsradio sans fil dans le contexte des applicationsde sécurité routière à hautes exigences.Nous nous concentrons ensuiteau déploiement d’un système d’éclairagesur les véhicules dans le but de fournir unmoyen de communication de soutien auxcommunications radio pour l’applicationde peloton. L’objectif primordial decette thèse est d’intégrer la technologieVLC dans l’architecture de communicationITS en implémentant un prototypede communication VLC et en concevantde nouveaux algorithmes de handoverpermettant une transition transparenteentre différents moyens de communicationinter-véhiculaires (VLC, communicationsans fil et techniques de perception).Le but est d’assurer les exigencesde sécurité requises par les applicationset l’échange continue de l’informationentre véhicules. L’efficacité de ces algorithmesa été validée à travers de nombreusessimulations et test-bed réels aucours desquels nous avons considérél’application de conduite automatisée.Ces différentes méthodes de validationont démontré que l’intégration de la technologieVLC avec les solutions de communicationsradio permet d’améliorer laqualité du canal de transmission ainsique la satisfaction des exigences de sécuritérelatives à l’application de peloton

Safety-critical scenarios and virtual testing procedures for automated cars at road intersections

This thesis addresses the problem of road intersection safety with regard to a mixed population of automated vehicles and non-automated road users. The work derives and evaluates safety-critical scenarios at road junctions, which can pose a particular safety problem involving automated cars. A simulation and evaluation framework for car-to-car accidents is presented and demonstrated, which allows examining the safety performance of automated driving systems within those scenarios. Given the recent advancements in automated driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual testing environments or on real-world test tracks. Since it is unrealistic to cover all possible combinations of traffic situations and environment conditions, the challenge is to find the key driving situations to be evaluated at junctions. Against this background, a novel method to derive critical pre-crash scenarios from historical car accident data is presented. It employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1,056 junction crashes in the UK, which were exported from the in-depth On-the-Spot database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions. As a follow-up to the scenario generation, the thesis further presents a novel, modular framework to transfer the derived collision scenarios to a sub-microscopic traffic simulation environment. The software CarMaker is used with MATLAB/Simulink to simulate realistic models of vehicles, sensors and road environments and is combined with an advanced Monte Carlo method to obtain a representative set of parameter combinations. The analysis of different safety performance indicators computed from the simulation outputs reveals collision and near-miss probabilities for selected scenarios. The usefulness and applicability of the simulation and evaluation framework is demonstrated for a selected junction scenario, where the safety performance of different in-vehicle collision avoidance systems is studied. The results show that the number of collisions and conflicts were reduced to a tenth when adding a crossing and turning assistant to a basic forward collision avoidance system. Due to its modular architecture, the presented framework can be adapted to the individual needs of future users and may be enhanced with customised simulation models. Ultimately, the thesis leads to more efficient workflows when virtually testing automated driving at intersections, as a complement to field operational tests on public roads

Collaborative Sensing in Automotive Scenarios : Enhancement of the Vehicular Electronic Horizon through Collaboratively Sensed Knowledge

Modern vehicles are equipped with a variety of advanced driver assistance systems that increase driving comfort, economy and safety. Respective information sources for these systems are local sensors, like cameras, radar or lidar. However, the next generation of assistant systems will require information above the local sensing range. An extension of the local perception can be provided by the use of appro- priate communication mechanisms. Hence, other vehicles can serve as an informa- tion source by providing their local perception data, but also any other information source, such as cloud services. Required communication can take place directly be- tween vehicles via mobile ad-hoc communication or via a backend by the use of cellu- lar communication. The appropriate technology depends on the respective use case, that determines information content, granularity and tolerated latency. Based on liter- ature, we derived a categorization of use case dependent information demands, with respect to communication. The resulting three zones, namely safety zone, awareness zone and information zone, refer to the tolerated latency between the occurrence of an information and the point in time the information has to be processed at the receiver side. While communication mechanisms for the safety zone, i. e., the ego-vehicle’s di- rect surroundings with a remaining driving time of less than 2 − 5 seconds, have been focus in research and standardization in the past, respective mechanisms for larger distances have not been sufficiently considered. In this thesis, we examine in- formation distribution mechanisms in context of the previously mentioned use case categories. As the first key contribution, we consider the gathering of vehicular sensed data with regard to the information zone, i. e., more than 30 seconds remaining driving time to the point of the information origin. We developed a probabilistic data collection model that is able to reduce data traffic up to 85 % compared to opportunistic trans- mission and still sticks to certain quality metrics, e. g., a maximum detection latency. A central adaption of transmission probabilities to the density of transmitting vehi- cles is applicable for cellular use and copes with sparse traffic situations. Moreover, we have extended this approach by hybrid communication, i. e., the parallel use of cellular and mobile ad-hoc communication. This allows to further reduce cellular based data traffic, in particular in case of dense traffic. As the second key contribution, we examine the efficient distribution of the pre- viously gathered information. Information is structured and prioritized according to the most probable driving path, as so-called electronic horizon. The transmission towards the vehicles is performed in small data packets, according to the given pri- orities. The aim is to transmit only information relevant for road segments that will be used. Concerning this, we developed a mechanism for most probable travel path estimation and a data structure for efficient mapping of the electronic horizon. As the third key contribution, we examine the information exchange in the aware- ness zone, an area between the safety zone and the information zone with about 5 to 30 seconds remaining driving time to the point of the information origin. Derived from the respective use cases, this data is not directly safety relevant, but it is still about dynamic position information of neighboring vehicles. Due to the relatively long distance, direct vehicle to vehicle communication is not possible. Respective data has to be forwarded by intermediate vehicles. However, position beacons with- out data forwarding can already cause channel congestion in dense traffic situations. The use of cellular networks would require absolute total network coverage with permanent free channel resources. To enable forwarding of dynamic vehicle infor- mation anyhow, we developed at first a mechanism to reduce the channel load for position beacons. Next, we use the freed-up bandwidth to forward dynamic informa- tion about neighboring vehicle positions. With this mechanism, we are able to more than double the range of vehicular perception, with respect to moving objects. In extension to standardized communication mechanisms for the safety relevant direct proximity, our three mentioned contributions provide the means to complete the long range vehicular perception for future advanced driver assistance systems

Intelligent Mobility in Smart Cities

Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the problem, the integration of systems for efficiency gains may compromise the resilience of an urban system. This all needs to be taken into consideration when thinking about Smart Cities. The transportation field must also apply the principles and concepts mentioned above. This cannot be understood without considering its links and effects on the other components of an urban system. New technologies allow for new means of travel to be built, and new business models allow for existing ones to be utilized. This Special Issue puts together papers with different focuses, but all of them tackle the topic of smart mobility

Contextual information aided target tracking and path planning for autonomous ground vehicles

Recently, autonomous vehicles have received worldwide attentions from academic research, automotive industry and the general public. In order to achieve a higher level of automation, one of the most fundamental requirements of autonomous vehicles is the capability to respond to internal and external changes in a safe, timely and appropriate manner. Situational awareness and decision making are two crucial enabling technologies for safe operation of autonomous vehicles. This thesis presents a solution for improving the automation level of autonomous vehicles in both situational awareness and decision making aspects by utilising additional domain knowledge such as constraints and influence on a moving object caused by environment and interaction between different moving objects. This includes two specific sub-systems, model based target tracking in environmental perception module and motion planning in path planning module. In the first part, a rigorous Bayesian framework is developed for pooling road constraint information and sensor measurement data of a ground vehicle to provide better situational awareness. Consequently, a new multiple targets tracking (MTT) strategy is proposed for solving target tracking problems with nonlinear dynamic systems and additional state constraints. Besides road constraint information, a vehicle movement is generally affected by its surrounding environment known as interaction information. A novel dynamic modelling approach is then proposed by considering the interaction information as virtual force which is constructed by involving the target state, desired dynamics and interaction information. The proposed modelling approach is then accommodated in the proposed MTT strategy for incorporating different types of domain knowledge in a comprehensive manner. In the second part, a new path planning strategy for autonomous vehicles operating in partially known dynamic environment is suggested. The proposed MTT technique is utilized to provide accurate on-board tracking information with associated level of uncertainty. Based on the tracking information, a path planning strategy is developed to generate collision free paths by not only predicting the future states of the moving objects but also taking into account the propagation of the associated estimation uncertainty within a given horizon. To cope with a dynamic and uncertain road environment, the strategy is implemented in a receding horizon fashion

Connecting Vehicles to the Internet - Strategic Data Transmission for Mobile Nodes using Heterogeneous Wireless Networks

With the advent of autonomous driving, the driving experience for users of connected vehicles changes, as they may enjoy their travel time with entertainment, or work productively. In our modern society, both require a stable Internet access. However, future mobile networks are not expected to be able to satisfy application Quality of Service (QoS) requirements as needed, e.g. during rush hours. To address this problem, this dissertation investigates data transmission strategies that exploit the potential of using a heterogeneous wireless network environment. To this end, we combine two so far distinct concepts, firstly, network selection and, secondly, transmission time selection, creating a joint time-network selection strategy. It allows a vehicle to plan delay-tolerant data transmissions ahead, favoring transmission opportunities with the best prospective flow-network matches. In this context, our first contribution is a novel rating model for perceived transmission quality, which assesses transmission opportunities with respect to application QoS requirement violations, traded off by monetary cost. To enable unified assessment of all data transmissions, it generalizes existing specialized rating models from network selection and transmission time selection and extends them with a novel throughput requirement model. Based on that, we develop a novel joint time-network selection strategy, Joint Transmission Planning (JTP), as our second contribution, planning optimized data transmissions within a defined time horizon. We compare its transmission quality to that of three predominant state-of-the-art transmission strategies, revealing that JTP outperforms the others significantly by up to 26%. Due to extensive scenario variation, we discover broad stability of JTP reaching 87-91% of the optimum. As JTP is a planning approach relying on prediction data, the transmission quality is strongly impaired when executing its plans under environmental changes. To mitigate this impact, we develop a transmission plan adaptation as our third contribution, modifying the planned current transmission online in order to comply with the changes. Even under strong changes of the vehicle movement and the network environment, it sustains 57%, respectively 36%, of the performance gain from planning. Finally, we present our protocol Mobility management for Vehicular Networking (MoVeNet), pooling available network resources of the environment to enable flexible packet dispatching without breaking connections. Its distributed architecture provides broad scalability and robustness against node failures. It complements control mechanisms that allow a demand-based and connection-specific trade-off between overhead and latency. Less than 9 ms additional round trip time in our tests, instant handover and 0 to 4 bytes per-packet overhead prove its efficiency. Employing the presented strategies and mechanisms jointly, users of connected vehicles and other mobile devices can significantly profit from the demonstrated improvements in application QoS satisfaction and reduced monetary cost

Radio shadowing in vehicle-to-vehicle communication at urban intersections : a measurement and simulation-based evaluation

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