The aim of platooning is to enable several vehicles to drive in a convoy while each vehicle is controlled autonomously in longitudinal direction. All vehicles in the platoon are equipped with WiFi and can therefore apply Vehicle-to-Vehicle (V2V) communication. As a result, a short intermediate distance between the vehicles can be maintained. Reduction of the aerodynamic drag is the result of the short distance, which in turn, reduces the consumed fuel. This thesis is a part of a larger project, consisting of two other theses that investigate estimation of the sensor data. Other scenarios that may arise with the platooning concept, e.g. packet losses and time synchronization of the different sensors are also analyzed. The purpose of this master thesis is to develop and evaluate a Model Predictive Control (MPC) in the concept of platooning. The main focus lies on implementation of two types of MPC, centralized and distributed, and later on integration with the other two subsystems is performed. Results from the MPC itself are evaluated, principally in terms of fuel con- sumption and computational demand. The major part of the results are based on the complete system as one unit and covers different test scenarios such as WiFi loss and non-transmitting vehicle entering the platoon. A comparison of how much energy that is consumed by the engine between an HDV driving with its cruise control and an HDV driving in a platoon has been performed. With an intermediate distance of 10 meters, driving with varying velocity and ideal signals the energy consumption got reduced with an average of 11%. / Syftet med platooning är att flera tunga fordon kör tätt efter varandra i ett fordonståg. Varje fordon regleras autonomt i longitudinell riktning och är utrustad med WiFi. Detta bidrar till att fordonen kan kommunicera med varandra och denna kommunikation, även kallad Vehicle-to-Vehicle (V2V) - communication, leder till att det relativa avståndet mellan fordonen kan minskas, vilket i sin tur leder till minskat luftmotstånd och därmed minskad bränsleförbrukning. Detta examensarbete är en del av ett större projekt som består av ytterligare två examensarbeten. De andra två hanterar estimeringen av sensordata samt behandlar förlorat sensordata och tidssynkronisering av de olika sensorerna som används. Syftet med detta examensarbete är att utveckla och utvärdera en MPC regu- lator i platooning sammanhang. Huvudfokuset ligger på implementeringen, både centraliserad och distribuerad MPC, och integreringen med de två andra delsystemen. Resultaten från enbart MPC utvärderas i termer av bränsleförbrukning och även beräkningskapactiet, då MPC är känt för att vara väldigt beräkningskrävan- de och är ofta en begränsning för hårdvaran. Den största delen av resultaten är baserade på hela systemet och täcker olika scenarion som exempelvis dålig WiFi uppkoppling och att icke−sändande fordon intar platoonen. En jämförelse av hur mycket energi motorn förbrukade har gjorts mellan ett tungt fordon som kör med farthållaren påslagen och ett tungt fordon som kör i en platoon. Med ett relativt avstånd på 10 meter, varierande hastighet och icke brusiga signaler kan bränsleförbrukning minskas med ett medel på approximativt 11%.

While the demand for video streaming services has risen rapidly in recent years, supporting video streaming service to a large number of receivers still remains a challenging task. Issues of video streaming in the Internet, such as scalability, and reliability are still under extensive research. Recently proposed network contexts such as overlay networks, and mobile ad hoc networks pose even tougher challenges. This thesis focuses on supporting scalable video streaming applications under various network environments. More specifically, this thesis investigates the following problems: i) Server selection in replicated batching video on demand (VoD) systems: we find out that, to optimize the user perceived latency, it is vital to consider the server state information and channel allocation schemes when making server selection decisions. We develop and evaluate a set of server selection algorithms that use increasingly more information. ii) Scalable live video streaming with time shifting and video patching: we consider the problem of how to enable continuous live video streaming to a large group of clients in cooperative but unreliable overlay networks. We design a server-based architecture which uses a combined technique of time-shifting video server and P2P video patching. iii) A Cooperative patching architecture in overlay networks: We design a cooperative patching architecture which shifts video patching responsibility completely to the client side. An end-host retrieves lost data from other end-hosts within the same multicast group. iv) V3: a vehicle to vehicle video streaming architecture: We propose V3, an architecture to provide live video streaming service to driving vehicles through vehicle-to-vehicle (V2V) networks. V3 incorporates a novel signaling mechanism to continuously trigger video sources to send video data back to the receiver. It also adopts a store-carry-and-forward approach to transmit video data in a partitioned network environment. We also develop a multicasting framework that enables live video streaming applications from multiple sources to multiple receivers in V2V networks. A message integration scheme is used to suppress the signaling overhead, and a two-level tree-based routing approach is adopted to forward the video data.

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With the number of deaths, commute time, and injuries constantly rising due to human driving errors, it’s time for a new transportation system, where humans are no longer involved in driving decisions and vehicles are the only machine that decide the actions of a vehicle. To accomplish a fully autonomous world, it’s important for vehicles to be able to communicate instantly and report their movements in order to reduce accidents. This paper discusses four approaches to vehicle to vehicle communication, as well as the underlying standards and technology that enable vehicles to accomplish communicating.

<p>Connected and autonomous vehicle (CAV) technologies provide disruptive and transformational opportunities for innovations toward intelligent transportation systems. Compared with human driven vehicles (HDVs), the CAVs can reduce reaction time and human errors, increase traffic mobility and will be more knowledgeable due to vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. CAVs’ potential to reduce traffic accidents, improve vehicular mobility and promote eco-driving is immense. However, the new characteristics and capabilities of CAVs will significantly transform the future of transportation, including the dissemination of traffic information, traffic flow dynamics and network equilibrium flow. This dissertation seeks to realize and enhance the application of CAVs by specifically advancing the research in three connected topics: (1) modeling and controlling information flow propagation within a V2V communication environment, (2) designing a real-time deployable cooperative control mechanism for CAV platoons, and (3) modeling network equilibrium flow with a mix of CAVs and HDVs. </p> <p>Vehicular traffic congestion in a V2V communication environment can lead to congestion effects for information flow propagation due to full occupation of the communication channel. Such congestion effects can impact not only whether a specific information packet of interest is able to reach a desired location, but also the timeliness needed to influence traffic system performance. This dissertation begins with exploring spatiotemporal information flow propagation under information congestion effects, by introducing a two-layer macroscopic model and an information packet relay control strategy. The upper layer models the information dissemination in the information flow regime, and the lower layer model captures the impacts of traffic flow dynamics on information propagation. Analytical and numerical solutions of the information flow propagation wave (IFPW) speed are provided, and the density of informed vehicles is derived under different traffic conditions. Hence, the proposed model can be leveraged to develop a new generation of information dissemination strategies focused on enabling specific V2V information to reach specific locations at specific points in time.</p> <p>In a V2V-based system, multiclass information (e.g., safety information, routing information, work zone information) needs to be disseminated simultaneously. The application needs of different classes of information related to vehicular reception ratio, the time delay and spatial coverage (i.e., distance it can be propagated) are different. To meet the application needs of multiclass information under different traffic and communication environments, a queuing strategy is proposed for each equipped vehicle to disseminate the received information. It enables control of multiclass information flow propagation through two parameters: 1) the number of communication servers and 2) the communication service rate. A two-layer model is derived to characterize the IFPW under the designed queuing strategy. Analytical and numerical solutions are derived to investigate the effects of the two control parameters on information propagation performance in different information classes. </p> <p>Third, this dissertation also develops a real-time implementable cooperative control mechanism for CAV platoons. Recently, model predictive control (MPC)-based platooning strategies have been developed for CAVs to enhance traffic performance by enabling cooperation among vehicles in the platoon. However, they are not deployable in practice as they require anembedded optimal control problem to be solved instantaneously, with platoon size and prediction horizon duration compounding the intractability. Ignoring the computational requirements leads to control delays that can deteriorate platoon performance and cause collisions between vehicles. To address this critical gap, this dissertation first proposes an idealized MPC-based cooperative control strategy for CAV platooning based on the strong assumption that the problem can be solved instantaneously. It then develops a deployable model predictive control with first-order approximation (DMPC-FOA) that can accurately estimate the optimal control decisions of the idealized MPC strategy without entailing control delay. Application of the DMPC-FOA approach for a CAV platoon using real-world leading vehicle trajectory data shows that it can dampen the traffic oscillation effectively, and can lead to smooth deceleration and acceleration behavior of all following vehicles.</p> <p>Finally, this dissertation also develops a multiclass traffic assignment model for mixed traffic flow of CAVs and HDVs. Due to the advantages of CAVs over HDVs, such as reduced value of time, enhanced quality of travel experience, and seamless situational awareness and connectivity, CAV users can differ in their route choice behavior compared to HDV users, leading to mixed traffic flows that can significantly deviate from the single-class HDV traffic pattern. However, due to a lack of quantitative models, there is limited knowledge on the evolution of mixed traffic flows in a traffic network. To partly bridge this gap, this dissertation proposes a multiclass traffic assignment model. The multiclass model captures the effect of knowledge level of traffic conditions on route choice of both CAVs and HDVs. In addition, it captures the characteristics of mixed traffic flow such as the difference in value of time between HDVs and CAVs and the asymmetry in their driving interactions, thereby enhancing behavioral realism in the modeling. New solution algorithms will be developed to solve the multiclass traffic assignment model. The study results can assist transportation decision-makers to design effective planning and operational strategies to leverage the advantages of CAVs and manage traffic congestion under mixed traffic flows.</p> <p>This dissertation deepens our understanding of the characteristics and phenomena in domains of traffic information dissemination, traffic flow dynamics and network equilibrium flow in the age of connected and autonomous transportation. The findings of this dissertation can assist transportation managers in designing effective traffic operation and planning strategies to fully exploit the potential of CAVs to improve system performance related to traffic safety, mobility and energy consumption. </p>

<p>This thesis describes the simulation of the proposed IEEE 802.11p Physical layer (PHY). A MATLAB simulation is carried out in order to analyze baseband processing of the transceiver. Orthogonal Frequency Division Multiplexing (OFDM) is applied in this project according to the IEEE 802.11p standard, which allows transmission data rates from 3 up to 27Mbps. Distinct modulation schemes, Binary Phase Shift Keying (BPSK), Quadrate Phase Shift Keying (QPSK) and Quadrature Amplitude modulation (QAM), are used according to differing data rates. These schemes are combined with time interleaving and a convolutional error correcting code. A guard interval is inserted at the beginning of the transmitted symbol in order to reduce the effect of Intersymbol Interference (ISI). The Viterbi decoder is used for decoding the received signal. Simulation results illustrate the Bit Error Rate (BER), Packet Error Rate (PER) for different channels. Different channel implementations are used for the simulations. In addition a ray-tracing based software tool for modelling time variant vehicular channels is integrated into SIMULINK. BER versus Signal to Noise Ratio (SNR) statistics are as the basic reference for the physical layer of the IEEE 802.11p standard for all vehicular wireless network simulations.</p>

This thesis describes the simulation of the proposed IEEE 802.11p Physical layer (PHY). A MATLAB simulation is carried out in order to analyze baseband processing of the transceiver. Orthogonal Frequency Division Multiplexing (OFDM) is applied in this project according to the IEEE 802.11p standard, which allows transmission data rates from 3 up to 27Mbps. Distinct modulation schemes, Binary Phase Shift Keying (BPSK), Quadrate Phase Shift Keying (QPSK) and Quadrature Amplitude modulation (QAM), are used according to differing data rates. These schemes are combined with time interleaving and a convolutional error correcting code. A guard interval is inserted at the beginning of the transmitted symbol in order to reduce the effect of Intersymbol Interference (ISI). The Viterbi decoder is used for decoding the received signal. Simulation results illustrate the Bit Error Rate (BER), Packet Error Rate (PER) for different channels. Different channel implementations are used for the simulations. In addition a ray-tracing based software tool for modelling time variant vehicular channels is integrated into SIMULINK. BER versus Signal to Noise Ratio (SNR) statistics are as the basic reference for the physical layer of the IEEE 802.11p standard for all vehicular wireless network simulations.

Vehicular Ad hoc NETworks (VANETs), an emerging technology, would allow vehicles to form a self-organized network without the aid of a permanent infrastructure. As a prerequisite to communication in VANETs, an efficient route between communicating nodes in the network must be established, and the routing protocol must adapt to the rapidly changing topology of vehicles in motion. This is one of the goals of VANET routing protocols. In this thesis, we present an efficient routing protocol for VANETs, called the Reliable Inter-VEhicular Routing (RIVER) protocol. RIVER utilizes an undirected graph that represents the surrounding street layout where the vertices of the graph are points at which streets curve or intersect, and the graph edges represent the street segments between those vertices. Unlike existing protocols, RIVER performs real-time, active traffic monitoring and uses this data and other data gathered through passive mechanisms to assign a reliability rating to each street edge. The protocol then uses these reliability ratings to select the most reliable route. Control messages are used to identify a node’s neighbors, determine the reliability of street edges, and to share street edge reliability information with other nodes.

Context. Connected vehicles use sensors such as cameras or radars to collect data about surrounding environments automatically and share these data with each other or with road side infrastructure using short-range wireless communication. Due to the large amount of information generated, strategies are required to minimize information redundancy when important information is propagated among connected vehicles. Objectives. This research aims to develop an information propagation strategy in connected vehicle systems using software agent-based coordination strategies to reduce unnecessary message broadcast and message propagation delay. Methods. A review of related work is used to acquire a deep insight as well as knowledge of the state-of-the-art and the state-of-practice from relevant studies in the subject area. Based on the review of related work, we propose an agent-based coordination strategy for information propagation in connected vehicle systems, in which connected vehicles coordinate their message broadcast activities using auctions. After that, a simulation experiment is conducted to evaluate the proposed strategy by comparing it with existing representative strategies. Results. Results of simulation experiments and statistical tests show that the proposed agent-based coordination strategy manifest some improvements in reducing unnecessary message broadcast and message propagation delay compared to other strategies involved in the simulation experiments. Conclusions. In this research, we suggest a new strategy to manage the propagation of information in connected vehicle systems. According to the small scale simulation analysis, the use of auctions to select message transmitters enables our proposed strategy to achieve some improvements in reducing unnecessary message broadcast and propagation delay than existing strategies. Thus, with the help of our proposed strategy, unnecessary message broadcast can be minimized and the communication resources of connected vehicle systems can be utilized effectively. Also, important safety messages can be propagated to drivers faster, negative traffic events could be averted. / 0707708513