DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment

SCTSC: A Semicentralized Traffic Signal Control Mode With Attribute-Based Blockchain in IoVs

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordAssisting traffic control is one of the most important applications on the Internet of Vehicles (IoVs). Traffic information provided by vehicles is desired since drivers or vehicle sensors are sensitive in perceiving or detecting nuances on roads. However, the availability and privacy preservation of this information are critical while conflicted with each other in the vehicular communication. In this paper, we propose a semicentralized mode with attribute-based blockchain in IoVs to balance the tradeoff between the availability and the privacy preservation. In this mode, a method of control-by-vehicles is used to control signals of traffic lights to increase traffic efficiency. Users are grouped their attributes such as locations and directions before starting the communication. The users reach an agreement on determining a temporary signal timing by interacting with each other without leaking privacy. Final decisions are verifiable to all users, even if they have no a priori agreement and processes of consensus. The mode not only achieves the aim of privacy preservation but also supports responsibility investigation for historical agreements via ciphertext-policy attribute-based encryption (CP-ABE) and blockchain technology. Extensive experimental results demonstrated that our mode is efficient and practical.National Key R&D Program of ChinaNatural Science Foundation of ChinaFundamental Research Funds for the Central Universities of Chin

Vehicle Dynamics, Lateral Forces, Roll Angle, Tire Wear and Road Profile States Estimation - A Review

Estimation of vehicle dynamics, tire wear, and road profile are indispensable prefaces in the development of automobile manufacturing due to the growing demands for vehicle safety, stability, and intelligent control, economic and environmental protection. Thus, vehicle state estimation approaches have captured the great interest of researchers because of the intricacy of vehicle dynamics and stability control systems. Over the last few decades, great enhancement has been accomplished in the theory and experiments for the development of these estimation states. This article provides a comprehensive review of recent advances in vehicle dynamics, tire wear, and road profile estimations. Most relevant and significant models have been reviewed in relation to the vehicle dynamics, roll angle, tire wear, and road profile states. Finally, some suggestions have been pointed out for enhancing the performance of the vehicle dynamics models

Design of an adaptive congestion control protocol for reliable vehicle safety communication

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Information Fusion Methodology for Enhancing Situation Awareness in Connected Cars Environment

This dissertation introduces novel approaches to develop a comprehensive model to address situation awareness in the Internet of Cars, called Attention Assist Framework (AAF). The proposed framework utilizes both Low-Level Data Fusion (LLDF), and High-Level Information Fusion (HLIF) to implement traffic entity, situation, and impact assessment, as well as decision making. The Internet of Cars is the convergence of the Internet of Things and Vehicular Ad-hoc Networks (VANETs). In fact, VANETs are the communication platforms that make possible the implementation of the Internet of Cars, and has become an integral part of this research field due to its major role to improve vehicle and road safety, traffic efficiency, and convenience as well as comfort to both drivers and passengers. Significant amount of VANETs research work has been focused on specific areas such as safety, routing, broadcasting, Quality of Service (QoS), and security. Among them, road safety issues are deemed one of the most challenging problems of VANETs. Specifically, lack of proper situational awareness of drivers has been shown to be the main cause of road accidents which makes it a major factor in road safety. The traffic entity assessment relies on a LLDF framework that is able to incorporate various multi-sensor data fusion approaches with means of communication links in VANETs. This is used to implement a cooperative localization approach through fusing common data fusion methods, such as Extended Kalman Filter (EKF) and Unscented Transform (UT), and vehicle-to-vehicle communication in VANETs. Furthermore, traffic situation assessment is based on a fuzzy extension to the Multi-Entity Bayesian Networks (MEBNs), which exploit the expressiveness of first-order logic for semantic relations, and the strength of the Fuzzy Bayesian Networks in handling uncertainty, while tackling the inherent vagueness in the soft data created by human entities. Finally, the impact assessment and decision making is realized through incorporating notions of game theory into Fuzzy-MEBNs, and introducing Active Fuzzy-MEBN (ATFY-MEBN), which is capable in hypothesizing future situations by assessing the impact of the current situation upon taking the actions indicated by an optimal strategy. In fact, such strategies are achieved through solving the games that are generated through a novel situation-specific normal form games generation algorithm that aims to create games based on the given context. In general, ATFY-MEBN presents the concepts of players and actions, and includes new game components, along with a 2-tier architecture, to efficiently model impact assessment and decision making. To demonstrate the capabilities of the proposed framework, a collision warning system simulator is developed, which evaluates the likelihood of a vehicle being in a near-collision situation using a wide variety of both local and global information sources available in the VANETs environment, and suggests an optimal action by assessing the impact of the current situation through generating and solving situation-specific games. Accordingly, first, the entities that highly influence the safety aspect, as well as both their casual and semantic relationships are identified. Next, an ATFY-MEBN-based model is presented, which allows for modeling these entities along with their relationships in specific contexts, assessing the current states of the situations of interest, predicting their future states, and finally suggesting optimal decision. Therefore, if the likelihood of being in a near-collision situation is determined to be high, and if the relevant situation-specific game is generated, then the impact of deciding on different combinations of actions that the game players take are calculated through a pre-fixed payoff function. Finally, the completed game is solved by finding its dominant strategy, that subsequently, results in proposing the optimal action to the driver. Our experimental results are divided into three main sections, through which we evaluate the capabilities of the traffic entity, situation, and impact assessment methods. Accordingly, the performance of the proposed cooperative localization approach is assessed by comparing its results with the ground truth solution and that of the other localization methods in various driving test cases. Moreover, two distinct single-vehicle and multi-vehicles categories of driving scenarios, as well as a novel hybrid MEBN inference, demonstrate the capabilities of the proposed traffic assessment model to efficiently achieve situation and threat assessment on the road. Finally, the impact assessment and decision making models are evaluated through two different scenarios of driving in highway and intersection that are formed with various number of player vehicles, and their actions

An intelligent intrusion detection system for external communications in autonomous vehicles

Advancements in computing, electronics and mechanical systems have resulted in the creation of a new class of vehicles called autonomous vehicles. These vehicles function using sensory input with an on-board computation system. Self-driving vehicles use an ad hoc vehicular network called VANET. The network has ad hoc infrastructure with mobile vehicles that communicate through open wireless channels. This thesis studies the design and implementation of a novel intelligent intrusion detection system which secures the external communication of self-driving vehicles. This thesis makes the following four contributions: It proposes a hybrid intrusion detection system to protect the external communication in self-driving vehicles from potential attacks. This has been achieved using fuzzification and artificial intelligence. The second contribution is the incorporation of the Integrated Circuit Metrics (ICMetrics) for improved security and privacy. By using the ICMetrics, specific device features have been used to create a unique identity for vehicles. Our work is based on using the bias in on board sensory systems to create ICMetrics for self-driving vehicles. The incorporation of fuzzy petri net in autonomous vehicles is the third contribution of the thesis. Simulation results show that the scheme can successfully detect denial-of-service attacks. The design of a clustering based hierarchical detection system has also been presented to detect worm hole and Sybil attacks. The final contribution of this research is an integrated intrusion detection system which detects various attacks by using a central database in BusNet. The proposed schemes have been simulated using the data extracted from trace files. Simulation results have been compared and studied for high levels of detection capability and performance. Analysis shows that the proposed schemes provide high detection rate with a low rate of false alarm. The system can detect various attacks in an optimised way owing to a reduction in the number of features, fuzzification

Trajectory planning based on adaptive model predictive control: Study of the performance of an autonomous vehicle in critical highway scenarios

Increasing automation in automotive industry is an important contribution to overcome many of the major societal challenges. However, testing and validating a highly autonomous vehicle is one of the biggest obstacles to the deployment of such vehicles, since they rely on data-driven and real-time sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software, and they must be proven to be reliable and safe. For this reason, the verification, validation and testing (VVT) of autonomous vehicles is gaining interest and attention among the scientific community and there has been a number of significant efforts in this field. VVT helps developers and testers to determine any hidden faults, increasing systems confidence in safety, security, functional analysis, and in the ability to integrate autonomous prototypes into existing road networks. Other stakeholders like higher-management, public authorities and the public are also crucial to complete the VTT process. As autonomous vehicles require hundreds of millions of kilometers of testing driven on public roads before vehicle certification, simulations are playing a key role as they allow the simulation tools to virtually test millions of real-life scenarios, increasing safety and reducing costs, time and the need for physical road tests. In this study, a literature review is conducted to classify approaches for the VVT and an existing simulation tool is used to implement an autonomous driving system. The system will be characterized from the point of view of its performance in some critical highway scenarios.O aumento da automação na indústria automotiva é uma importante contribuição para superar muitos dos principais desafios da sociedade. No entanto, testar e validar um veículo altamente autónomo é um dos maiores obstáculos para a implantação de tais veículos, uma vez que eles contam com sensores, atuadores, algoritmos complexos, sistemas de aprendizagem de máquina e processadores potentes para executar softwares em tempo real, e devem ser comprovadamente confiáveis e seguros. Por esta razão, a verificação, validação e teste (VVT) de veículos autónomos está a ganhar interesse e atenção entre a comunidade científica e tem havido uma série de esforços significativos neste campo. A VVT ajuda os desenvolvedores e testadores a determinar quaisquer falhas ocultas, aumentando a confiança dos sistemas na segurança, proteção, análise funcional e na capacidade de integrar protótipos autónomos em redes rodoviárias existentes. Outras partes interessadas, como a alta administração, autoridades públicas e o público também são cruciais para concluir o processo de VTT. Como os veículos autónomos exigem centenas de milhões de quilómetros de testes conduzidos em vias públicas antes da certificação do veículo, as simulações estão a desempenhar cada vez mais um papel fundamental, pois permitem que as ferramentas de simulação testem virtualmente milhões de cenários da vida real, aumentando a segurança e reduzindo custos, tempo e necessidade de testes físicos em estrada. Neste estudo, é realizada uma revisão da literatura para classificar abordagens para a VVT e uma ferramenta de simulação existente é usada para implementar um sistema de direção autónoma. O sistema é caracterizado do ponto de vista do seu desempenho em alguns cenários críticos de autoestrad

Role of smart vehicles concept in reducing traffic congestion on the road

The aim of this simple qualitative review was to provide an overview of how smart vehicles concept facilitates reducing traffic congestion on the road. Google Scholar was searched for literature sources using the topic itself as the search term. The search yielded 40 usable papers for this review. Many elements of smart city are inter-mixed with the smart vehicles concept. On the other hand in the smart vehicle concept, enabling technologies like VANET, IoV, SDN, use of mobiles and even use of electric poles on the road as IoT gateway were tested in the different frameworks proposed by different researchers. Many other traffic management systems have also been tested especially in Japan and India. In general, two scenarios have been considered-one of current types of roads and the other automated highways. Understandably, the requirements and approaches are different for the two scenarios. Some limitations of this review have also been listed at the end. Maximum of works dealt with VANET technolog

Roteamento de tráfego veicular colaborativo e sem infraestrutura para sistemas de transportes inteligentes

Orientadores: Leandro Aparecido Villas, Edmundo Roberto Mauro MadeiraTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Devido à atual tendência mundial de urbanização, a sociedade moderna enfrenta, cada vez mais, sérios problemas de mobilidade urbana. Além disso, com o aumento constante do fluxo de tráfego veicular, as atuais soluções existentes para gerenciamento de tráfego se tornaram ineficientes. Com isso, para atender às crescentes necessidades dos sistemas de transporte, é necessário sistemas de transporte inteligentes (ITS). O desenvolvimento de ITS sustentável requer integração e interoperabilidade contínuas com tecnologias emergentes, tais como as redes veiculares (VANETs). As VANETs são consideradas uma tecnologia promissora que provê aplicações críticas de segurança e serviços de entretenimento, consequentemente melhorando a experiência de viagem do motorista e dos passageiros. Esta tese propõe um sistema de gerenciamento de tráfego de veículos sem a necessidade de uma infraestrutura de apoio. Para alcançar o sistema desejado foram necessários propor soluções intermediárias que contribuíram nesta tese. A primeira contribuição reside em uma solução que emprega conhecimento histórico dos padrões de mobilidade dos motoristas para obter uma visão global da situação da rede viária. Diferentemente de outras abordagens que precisam de troca constante de informações entre os veículos e o servidor central, nossa solução utiliza informações espaciais e temporais sobre padrões de mobilidade, além das informações específicas da infraestrutura viária, a fim de identificar congestionamentos no tráfego, permitindo, assim, o planejamento de roteamento de veículos. Como segunda contribuição, foi proposta uma solução distribuída para calcular a intermediação egocêntrica nas VANETs. Por meio da métrica egocêntrica foi proposto um mecanismo inovador de ranqueamento de veículos em redes altamente dinâmicas. As principais vantagens desse mecanismo para aplicações de VANETs são: (i) a redução do consumo de largura de banda e (ii) a superação do problema de topologias altamente dinâmicas. A terceira contribuição é uma solução de planejamento de rotas colaborativo com intuito de melhorar o gerenciamento do tráfego de veículos em cenários urbanos. Como última contribuição, esta tese integra as soluções descritas acima, propondo um sistema eficiente de gerenciamento de tráfego de veículos. As soluções propostas foram amplamente comparadas com outras soluções da literatura em diferentes métricas de avaliação de desempenho. Os resultados mostram que o sistema de gerenciamento de tráfego de veículos proposto é eficiente e escalável, qual pode ser uma boa alternativa para mitigar os problemas de mobilidade urbanaAbstract: Due to the current global trend of urbanization, modern society is facing severe urban mobility problems. In addition, considering the constant increase in vehicular traffic on roads, existing traffic management solutions have become inefficient. In order to assist the increasing needs of transport systems today, there is a need for intelligent transportation systems (ITS). Developing a sustainable ITS requires seamless integration and interoperability with emerging technologies such as vehicular ad-hoc networks (VANETs). VANETs are considered to be a promising technology providing access to critical life-safety applications and infotainment services, consequently improving drivers¿ and passengers¿ on-road experiences. This thesis proposes an infrastructure-less vehicular traffic management system. To achieve such a system, intermediate solutions that contributed to this thesis were proposed. The first contribution lies in a solution that employs historical knowledge of driver mobility patterns to gain an overall view of the road network situation. Unlike other approaches that need constant information exchange between vehicles and the central server, our solution uses space and temporal information about mobility patterns, as well as road infrastructure information, in order to identify traffic congestion, thus allowing for vehicle routing planning. Secondly, a distributed solution to calculate egocentric betweenness in VANETs was proposed. Through the egocentric metric, an innovative vehicle ranking mechanism in highly dynamic networks was proposed. The main advantages of this mechanism for VANETs applications are (i) reduced bandwidth consumption and (ii) overcoming the problem of highly dynamic topologies. The third contribution is a collaborative route planning solution designed to improve vehicle traffic management in urban settings. As the last contribution, this thesis integrates the solutions described above, proposing an efficient vehicle traffic management system. The proposed solutions were widely compared with other literature solutions on different performance evaluation metrics. The evaluation results show that the proposed vehicle traffic management system is efficient, scalable, and cost-effective, which may be a good alternative to mitigate urban mobility problemsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação2015/25588-6FAPES