The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility Challenge (2019 Chevrolet Blazer) for an adaptive cruise control system (ACC) which functions in on-road applications. Along with vehicles, pedestrians, and cyclists, the sensor fusion system deployed in the 2019 Chevrolet Blazer uses vehicle-to-everything (V2X) communication to communicate with infrastructure such as traffic lights to optimize and autonomously control vehicle acceleration through a connected corridor

Vehicular communication networks are essential to the development of intelligent navigation systems and improvement of road safety. Unlike most terrestrial networks of today, vehicular networks are characterized by stringent reliability and latency requirements. In order to design efficient networks to meet these requirements, it is important to understand the system-level performance of vehicular networks. Stochastic geometry has recently emerged as a powerful tool for the modeling and analysis of wireless communication networks. However, the canonical spatial models such as the 2D Poisson point process (PPP) does not capture the peculiar spatial layout of vehicular networks, where the locations of vehicular nodes are restricted to roadways. Motivated by this, we consider a doubly stochastic spatial model that captures the spatial coupling between the vehicular nodes and the roads and analyze the performance of vehicular communication networks. We model the spatial layout of roads by a Poisson line process (PLP) and the locations of nodes on each line (road) by a 1D PPP, thereby forming a Cox process driven by a PLP or Poisson line Cox process (PLCP). In this dissertation, we develop the theory of the PLCP and apply it to study key performance metrics such as coverage probability and rate coverage for vehicular networks under different scenarios. First, we compute the signal-to-interference plus noise ratio (SINR)-based success probability of the typical communication link in a vehicular ad hoc network (VANET). Using this result, we also compute the area spectral efficiency (ASE) of the network. Our results show that the optimum transmission probability that maximizes the ASE of the network obtained for the Cox process differs significantly from that of the conventional 1D and 2D PPP models. Second, we calculate the signal-to-interference ratio (SIR)-based downlink coverage probability of the typical receiver in a vehicular network for the cellular network model in which each receiver node connects to its closest transmitting node in the network. The conditioning on the serving node imposes constraints on the spatial configuration of interfering nodes and also the underlying distribution of lines. We carefully handle these constraints using various fundamental distance properties of the PLCP and derive the exact expression for the coverage probability. Third, building further on the above mentioned works, we consider a more complex cellular vehicle-to-everything (C-V2X) communication network in which the vehicular nodes are served by roadside units (RSUs) as well as cellular macro base stations (MBSs). For this setup, we present the downlink coverage analysis of the typical receiver in the presence of shadowing effects. We address the technical challenges induced by the inclusion of shadowing effects by leveraging the asymptotic behavior of the Cox process. These results help us gain useful insights into the behavior of the networks as a function of key network parameters, such as the densities of the nodes and selection bias. Fourth, we characterize the load on the MBSs due to vehicular users, which is defined as the number of vehicular nodes that are served by the MBS. Since the limited network resources are shared by multiple users in the network, the load distribution is a key indicator of the demand of network resources. We first compute the distribution of the load on MBSs due to vehicular users in a single-tier vehicular network. Building on this, we characterize the load on both MBSs and RSUs in a heterogeneous C-V2X network. Using these results, we also compute the rate coverage of the typical receiver in the network. Fifth and last, we explore the applications of the PLCP that extend beyond vehicular communications. We derive the exact distribution of the shortest path distance between the typical point and its nearest neighbor in the sense of path distance in a Manhattan Poisson line Cox process (MPLCP), which is a special variant of the PLCP. The analytical framework developed in this work allows us to answer several important questions pertaining to transportation networks, urban planning, and personnel deployment. / Doctor of Philosophy / Vehicular communication networks are essential to the development of intelligent transportation systems (ITS) and improving road safety. As the in-vehicle sensors can assess only their immediate environment, vehicular nodes exchange information about critical events, such as accidents and sudden braking, with other vehicles, pedestrians, roadside infrastructure, and cellular base stations in order to make critical decisions in a timely manner. Considering the time-sensitive nature of this information, it is of paramount importance to design efficient communication networks that can support the exchange of this information with reliable and high-speed wireless links. Typically, prior to actual deployment, any design of a wireless network is subject to extensive analysis under various operational scenarios using computer simulations. However, it is not viable to rely entirely on simulations for the system design of highly complex systems, such as the vehicular networks. Hence, it is necessary to develop analytical methods that can complement simulators and also serve as a benchmark. One of the approaches that has gained popularity in the recent years for the modeling and analysis of large-scale wireless networks is the use of tools from stochastic geometry. In this approach, we endow the locations of wireless nodes with some distribution and analyze various aspects of the network by leveraging the properties of the distribution. Traditionally, wireless networks have been studied using simple spatial models in which the wireless nodes can lie anywhere on the domain of interest (often a 1D or a 2D plane). However, vehicular networks have a unique spatial geometry because the locations of vehicular nodes are restricted to roadways. Therefore, in order to model the locations of vehicular nodes in the network, we have to first model the underlying road systems. Further, we should also consider the randomness in the locations of vehicles on each road. So, we consider a doubly stochastic model called Poisson line Cox process (PLCP), in which the spatial layout of roads are modeled by random lines and the locations of vehicles on the roads are modeled by random set of points on these lines. As is usually the case in wireless networks, multiple vehicular nodes and roadside units (RSUs) operate at the same frequency due to the limited availability of radio frequency spectrum, which causes interference. Therefore, any receiver in the network obtains a signal that is a mixture of the desired signal from the intended transmitter and the interfering signals from the other transmitters. The ratio of the power of desired signal to the aggregate power of the interfering signals, which is called as the signal-to-interference ratio (SIR), depends on the locations of the transmitters with respect to the receiver. A receiver in the network is said to be in coverage if the SIR measured at the location of the receiver exceeds the required threshold to successfully decode the message. The probability of occurrence of this event is referred to as the coverage probability and it is one of the fundamental metrics that is used to characterize the performance of a wireless network. In our work, we have analytically characterized the coverage probability of the typical vehicular node in the network. This was the first work to present the coverage analysis of a vehicular network using the aforementioned doubly stochastic model. In addition to coverage probability, we have also explored other performance metrics such as data rate, which is the number of bits that can be successfully communicated per unit time, and spectral efficiency. Our analysis has revealed interesting trends in the coverage probability as a function of key system parameters such as the density of roads in a region (total length of roads per unit area), and the density of vehicles on the roads. We have shown that the vehicular nodes in areas with high density of roads have lower coverage than those in areas with sparsely distributed roads. On the other hand, the coverage probability of a vehicular node improves as the density of vehicles on the roads increases. Such insights are quite useful in the design and deployment of network infrastructure. While our research was primarily focused on communication networks, the utility of the spatial models considered in these works extends to other areas of engineering. For a special variant of the PLCP, we have derived the distribution of the shortest path distance between an arbitrary point and its nearest neighbor in the sense of path distance. The analytical framework developed in this work allows us to answer several important questions pertaining to infrastructure planning and personnel deployment.

With the continuous progress on autonomous vehicle and remote drivingtechniques, connection quality demands are changing compared withconventional quality of service. Vehicle to everything communication, asthe connectivity basis for these applications, has been built up on LongTerm Evolution basis, but due to various ethical and environmental issues,few implementations have been made in reality. Therefore simulation approachesare believed to provide valuable insights.To fully model an LTE vehicular network, in this work we first providea comparison study to select the preferable LTE simulator. Aimingto integrate communication nodes with mobility, a solution for simulationframework is developed based on a state-of-art comparison study on theexisting simulator frameworks. We then further develop the network simulator,and complement it with hybrid wireless channel modeling, channeland quality of service aware scheduler, and admission control strategies. Interms of instant optimization of the network, real-time access is emulatedfor external devices to communicate with the simulator. In this thesis,the evaluation of the framework performance considers two aspects: theperformance of the simulator in LTE V2X use case and the feasibility ofthe service, specifically, remote driving, under realistic network capacity.For our framework, the results indicate that it is feasible to realize remotedriving in an LTE urban scenario, but, as an example, we show that foran area of Kista, five vehicles could be hold by a base-station with guaranteedservice at most. / Med kontinuerliga framstegen p°a autonomt fordon och fj¨arrkontrollteknikf¨or¨andras kravet p°a anslutningskvalitet i j¨amf¨orelse med konventionell servicekvalitet.Fordon till allting (V2X) kommunikation, som anslutningsgrundf¨or dessa applikationer, har byggts upp p°a basis av Long TermEvolution (LTE) system, men p°a grund av olika etiska och milj¨om¨assigaproblem har f°a implementeringar gjorts i verkligheten. D¨arf¨or antas simuleringsmetoderge v¨ardefulla insikter.Att fullt ut modellera ett LTE-fordon n¨atverk, i det h¨ar arbetet ger vif¨orst en j¨amf¨orelsestudie f¨or att v¨alja den f¨oredragna LTE-simulatorn.I syfte att integrera kommunikationsnoder med r¨orlighet utvecklas enl¨osning f¨or ett simuleringsramverk baserat p°a en j¨amf¨orelsestudie p°a befintligasimulatorramar. Vi utvecklar sedan n¨atverkssimulatorn ytterligare,och kompletterar den med hybrid tr°adl¨os kanalmodellering, kanal ochservicekvalitetmedvetna schemal¨aggning och antagningskontrollstrategier.N¨ar det g¨aller direkt n¨atverksoptimering, emuleras realtidsanslutningav externa enheter f¨or att kommunicera med simulatorn. I denna avhandlingutv¨arderas ramverken i tv°a aspekter: simulatorns prestanda i LTEV2X-anv¨andningsomr°adet och genomf¨orbarheten av tj¨ansten, s¨arskilt fj¨arrk¨orning,under realistisk n¨atkapacitet. In v°ara ramverk visar resultaten att det ¨arm¨ojligt att realisera fj¨arrk¨orning i ett LTE-urbana scenario, men som exempelvisar vi att f¨or ett omr°ade i Kista skulle som mest fem fordon kunnask¨otas av en basstation med garanterad service.

This thesis consists of two projects focusing on how 5G can be used to make vehicles safer. The first project focuses on conceptualizing near-future use cases of how Advanced Driver Assistance Systems (ADAS) can be enhanced through 5G technology. Four concepts were developed in collaboration with various industry partners. These concepts were successfully demonstrated in a proof-of-concept at the 5G Automotive Association (5GAA) “The 5G Path of Vehicle-to-Everything Communication: From Local to Global” conference in Turin, Italy. This proof-of-concept was the world’s first demonstration of such a system. The second project focuses on a futuristic use case, namely remote operation of semi-autonomous vehicles (sAVs). As part of this work, it was explored if augmented reality (AR) can be used to warn remote operators of dangerous events. It was explored if such augmentations can be used to compensate during critical events. These events are defined as occurrences in which the network conditions are suboptimal, and information provided to the operator is limited. To evaluate this, a simulator environment was developed that uses eye- tracking technology to study the impact of such scenarios through user studies. The simulator establishes an extendable platform for future work. Through experiments, it was found that AR can be beneficial in spotting danger. However, it can also be used to directly affect the scanning patterns at which the operator views the scene and directly affect their visual scanning behavior. / Denna avhandling består av två projekt med fokus på hur 5G kan användas för att göra fordon säkrare. Det första projektet fokuserar på att konceptualisera användningsfall i närmaste framtid av hur Advanced Driver Assistance Systems (ADAS) kan förbättras genom 5G-teknik. Fyra koncept utvecklades i samarbete med olika branschpartner. Dessa koncept demonstrerade i ett proof-of- concept på 5G Automotive Association (5GAA) “5G Path of Vehicle to to Everything Communication: From Local to Global” -konferensen i Turin, Italien. Detta bevis-of-concept var världens första demonstration av ett sådant system. Det andra projektet fokuserar på ett långt futuristiskt användningsfall, nämligen fjärrstyrning av semi-autonoma fordon (sAVs). Som en del av detta arbete undersöktes det om augmented reality (AR) kan användas för att varna fjärroperatörer om farliga händelser. Det undersöktes om sådana förstärkningar kan användas för att kompensera under kritiska händelser. Dessa händelser definieras som händelser där nätverksförhållandena är suboptimala och information som tillhandahålls till operatören är begränsad. För att utvärdera detta utvecklades en simulatormiljö som använder ögonspårningsteknologi för att studera effekterna av sådana scenarier genom en användarstudie. Simulatorn bildar en utdragbar plattform för framtida arbete. Genom experiment fann man att AR kan vara fördelaktigt när det gäller att upptäcka fara. Men det kan också användas för att direkt påverka skanningsmönstret där operatören tittar på scenen och direkt påverka deras visuella skanningsbeteende.

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