Detecting Non-Line of Sight to Prevent Accidents in Vehicular Ad hoc Networks

There are still many challenges in the field of VANETs that encouraged researchers to conduct further investigation in this field to meet these challenges. The issue pertaining to routing protocols such as delivering the warning messages to the vehicles facing Non-Line of Sight (NLOS) situations without causing the storm problem and channel contention, is regarded as a serious dilemma which is required to be tackled in VANET, especially in congested environments. This requires the designing of an efficient mechanism of routing protocol that can broadcast the warning messages from the emergency vehicles to the vehicles under NLOS, reducing the overhead and increasing the packet delivery ratio with a reduced time delay and channel utilisation. The main aim of this work is to develop the novel routing protocol for a high-density environment in VANET through utilisation of its high mobility features, aid of the sensors such as Global Positioning System (GPS) and Navigation System (NS). In this work, the cooperative approach has been used to develop the routing protocol called the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle under NLOS issue; this also increases the packet delivery ratio, detection of NLOS and resolution of NLOS by delivering the warning message successfully to the vehicle under NLOS, thereby causing a direct impact on the reduction of collisions between vehicles in normal mode and emergency mode on the road near intersections or on highways. The cooperative approach adopted for warning message dissemination reduced the rebroadcast rate of messages, thereby decreasing significantly the storm issue and the channel contention. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other in order to collect data and take the decisions based on the sensed circumstances. The proposed architecture has been divided into three main phases: sensing, processing and acting. The results obtained from the validation of the proposed CVP protocol using the simulator EstiNet under specific conditions and parameters showed that performance of the proposed protocol is better than that of the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead and latency. It is also successfully shown that the proposed CVP could detect the NLOS situation and solves it effectively and efficiently for both the intersection scenario in urban areas and the highway scenario

Cooperative Volunteer Protocol to Detect Non-Line of Sight Nodes in Vehicular Ad hoc Networks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. CTIA vehicular Ad hoc Network (VANET) is a special type of Mobile Ad hoc Network (MANET) application that impacts wireless communications and Intelligent Transport Systems (ITSs). VANETs are employed to develop safety applications for vehicles to create a safer and less cluttered environment on the road. The many remaining challenges relating to VANETs have encouraged researchers to conduct further investigation in this field to meet these challenges. For example, issues pertaining to routing protocols, such as the delivery of warning messages to vehicles facing Non-Line of Sight (NLOS) situations without causing a broadcasting storm and channel contention are regarded as a serious dilemma, especially in congested environments. This prompted the design of an efficient mechanism for a routing protocol capable of broadcasting warning messages from emergency vehicles to vehicles under NLOS conditions to reduce the overhead and increase the packet delivery ratio with reduced time delay and channel utilisation. This work used the cooperative approach to develop the routing protocol named the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle experiencing an NLOS situation. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other to collect data and make decisions based on the sensed circumstances. The simulation results showed that the proposed protocol outperformed the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead, and latency. The results also showed that the proposed CVP could successfully detect NLOS situations and solve them effectively and efficiently for both the intersection scenario in urban areas and the highway scenario

Multi-directional Warning Message Dissemination Protocol Based on Motion Vector Clustering for VANETs

Problem. Most broadcast suppression protocols in vehicular ad hoc networks (VANET) mainly focus on one-dimensional message dissemination model for both highway and urban scenarios. Due to the non-line-of-sight (NLOS) problem occuring frequently in urban scenario, protocols mostly rely on either infrastructure or the vehicle that is passing through the intersection to forward the message in multiple directions manner. However, these one-dimensional message dissemination models fail to take into account realistic road topologies and traffic distribution. As a result, they tend to miss some possible dissemination directions. Method. Vehicles travelling on the same road share similar motion pattern due to the constraint of road topology. Each motion pattern represents a road topology as well as a potential dissemination direction. By identifying motion pattern of one-hop neighbors, the proposed motion vector protocol (MVP) enables a vehicle not only to identify potential dissemination directions without the support from infrastructure or a road map but also to make suppression decisions without any additional information from periodic beacons. Results. The total number of transmissions for simple flooding (each node broadcasts once) compared with MVP ranges respectively as follows: 90.2-269.7 and 40.6-72.3. Also, the number of saved rebroadcasts for simple flooding compared with MVP ranges respectively as follows: 0%-0% and 57%-73%. In the case of reachability, the simple flooding compared with MVP ranges 100%-100% and 100%-100% respectively. Finally, the average latency of the entire dissemination for simple flooding and MVP ranges 0.01446-0.01286s and 0.1127-0.1565s respectively. Conclusions. The experimental results show that MVP achieves high reachability, while still significantly reducing rebroadcast redundancy. One distinctive feature of MVP is that it is capable of operating on complex road topology such as a roundabout, curve road, branch road, etc., with multi-directional traffic in it

Reliability and Efficiency of Vehicular Network Applications

The DSRC/WAVE initiative is forecast to enable a plethora of applications, classified in two broad types of safety and non-safety applications. In the former type, the reliability performance is of tremendous prominence while, in the latter case, the efficiency of information dissemination is the key driving factor. For safety applications, we adopt a systematic approach to analytically investigate the reliability of the communication system in a symbiotic relationship with the host system comprising a vehicular traffic system and radio propagation environment. To this aim, the¬ interference factor is identified as the central element of the symbiotic relationship. Our approach to the investigation of interference and its impacts on the communication reliability departs from previous studies by the degree of realism incorporated in the host system model. In one dimension, realistic traffic models are developed to describe the vehicular traffic behaviour. In a second dimension, a realistic radio propagation model is employed to capture the unique signal propagation aspects of the host system. We address the case of non-safety applications by proposing a generic framework as a capstone architecture for the development of new applications and the efficiency evaluation of existing ones. This framework, while being independent from networking technology, enables accurate characterization of the various information dissemination tasks that a node performs in cooperation with others. As the central element of the framework, we propose a game theoretic model to describe the interaction of meeting nodes aiming to exchange information of mutual or social interests. An adaptive mechanism is designed to enable a mobile node to measure the social significance of various information topics, which is then used by the node to prioritize the forwarding of information objects

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

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Secure Localization Topology and Methodology for a Dedicated Automated Highway System

Localization of nodes is an important aspect in a vehicular ad-hoc network (VANET). Research has been done on various localization methods. Some are more apt for a specific purpose than others. To begin with, we give an overview of a vehicular ad-hoc network, localization methods, and how they can be classified. The distance bounding and verifiable trilateration methods are explained further with their corresponding algorithms and steps used for localization. Distance bounding is a range-based distance estimation algorithm. Verifiable trilateration is a popular geometric method of localization. A dedicated automated highway infrastructure can use distance bounding and/or trilateration to localize an automated vehicle on the highway. We describe a highway infrastructure for our analysis and test how well each of the methods performs, according to a security measure defined as spoofing probability. The spoofing probability is, simply put, the probability that a given point on the highway will be successfully spoofed by an attacker that is located at any random position along the highway. Spoofing probability depends on different quantities depending on the method of localization used. We compare the distance bounding and trilateration methods to a novel method using friendly jamming for localization. Friendly jamming works by creating an interference around the region whenever communication takes place between a vehicle and a verifier (belonging to the highway infrastructure, which is involved in the localization process using a given algorithm and localization method). In case of friendly jamming, the spoofing probability depends both on the position and velocity of the attacker and those of the target vehicle (which the attacker aims to spoof). This makes the spoofing probability much less for friendly jamming. On the other hand, the distance bounding and trilateration methods have spoofing probabilities depending only on their position. The results are summarized at the end of the last chapter to give an idea about how the three localization methods, i.e. distance bounding, verifiable trilateration, and friendly jamming, compare against each other for a dedicated automated highway infrastructure. We observe that the spoofing probability of the friendly jamming infrastructure is less than 2% while the spoofing probabilities of distance bounding and trilateration are 25% and 11%, respectively. This means that the friendly jamming method is more secure for the corresponding automated transportation system (ATS) infrastructure than distance bounding and trilateration. However, one drawback of friendly jamming is that it has a high standard deviation because the range of positions that are most vulnerable is high. Even though the spoofing probability is much less, the friendly jamming method is vulnerable to an attack over a large range of distances along the highway. This can be overcome by defining a more robust infrastructure and using the infrastructure\u27s resources judiciously. This can be the future scope of our research. Infrastructures that use the radio resources in a cost effective manner to reduce the vulnerability of the friendly jamming method are a promising choice for the localization of vehicles on an ATS highway

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

[no abstract

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information

A trust model using edge nodes and cuckoo filter for securing vanet under nlos conditions

Trust, as a key element of security, has a vital role in securing vehicular ad-hoc networks (VANETs). Malicious and selfish nodes by generating inaccurate information, have undesirable impacts on the trustworthiness of the VANET environment. Obstacles also have a negative impact on data trustworthiness by restricting direct communication between nodes. In this study, a trust model based on plausibility, experience, and type of vehicle is presented to cope with inaccurate, incomplete and uncertainty data under both line of sight (LoS) and none-line of sight (NLoS) conditions. In addition, a model using the k-nearest neighbor (kNN) classification algorithm based on feature similarity and symmetry is developed to detect the NLoS condition. Radio signal strength indicator (RSSI), packet reception rate (PDR) and the distance between two vehicle nodes are the features used in the proposed kNN algorithm. Moreover, due to the big data generated in VANET, secure communication between vehicle and edge node is designed using the Cuckoo filter. All obtained results are validated through well-known evaluation measures such as precision, recall, overall accuracy, and communication overhead. The results indicate that the proposed trust model has a better performance as compared to the attack-resistant trust management (ART) scheme and weighted voting (WV) approach. Additionally, the proposed trust model outperforms both ART and WV approaches under diffierent patterns of attack such as a simple attack, opinion tampering attack, and cunning attack. Monte-Carlo simulation results also prove validity of the proposed trust model

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS