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%.

The purpose of this research is to explore the operational characteristics of a Maglev-based Automated Highway System and how it would interact with freeway operations. The extension of traditional traffic flow phenomenon, including weaving, merging, and stopping distance, into the automated system is looked at. These are also extended into platoon operations and their effect on such properties as gap control and ultimately the capacity of such a system. The ability to incorporate an AHS system into the existing Interstate Highway System is investigated. This includes placing the magways in the right-of-way of the highway system and interfacing the AHS with the existing freeways. A model is developed and run to simulate the assignment of traffic between the freeway and the guideway links. Both operational concepts of user equilibrium and system optimal conditions are explored, and equations are found to estimate the amount of traffic which can be found on the links based on the total traffic volume. / Master of Science

Vehicle platoons are efficient, closely-spaced groups of robotically controlled vehicles which travel at high speeds down the road, similar to carts in a train. Within this thesis, a promising control algorithm for vehicle platooning is explored. The control algorithm was previously demonstrated in a sterile setting which significantly reduced the challenges facing full-scale implementation of platoons, most notably loss of shared data and imprecision within the data. As found within this work, transmission loss and imprecise position, velocity, and acceleration data significantly degraded the control algorithm's performance. Vehicles in the platoon became more closely spaced, changed speeds more frequently, and expended far more energy than necessary. Introducing a measure of each following vehicle's position with respect to the lead vehicle into the control algorithm noticeably reduced platoon contraction. Adjusting the control algorithm's responsiveness based on what data was successfully received reduced the speed-variations by vehicles. Finally, using past behavior to predict the next acceleration reduced the energy used by each vehicle. Combining these modifications with a model of the proposed communication scheme shows platoons of up to 25 vehicles are feasible.

Research in automatic control has enabled trucks to use adaptive cruise control to drive very close to each other and form platoons. This reduces drag and improves efficiency by lowering fuel consumption. A central challenge to understanding the formation of these platoons is that not all trucks are emerging from the same origin or reaching the same destination; they only share parts of their joint trip. This study uses participatory design methodologies to create a design for an interactive visualization system to enable researchers to study the formation of platoons in simulated scenarios. Three transport researchers participated in interviews and a set of two workshops to establish their needs and formulate tasks that would improve their understanding of the simulations. The main research-through-design question was “when do platoons form and how large are they?” To forward and ground the discussion, I developed a prototype with increasing fidelity after each round of participatory design. The interface consists four panels: 1) a spatial panel that contains a map view; 2) a temporal panel with context and focus timelines: 3) an adaptation panel with details on inter-truck relationships; and 4) a filtering panel with a parallel coordinate system. The results indicate a need for a flexible interactive visualization system that enables researchers to study how trucks are affected by plan recalculations and how they adapt to their partners influencing the costs and benefits of platooning. / Forskning inom reglerteknik och fordonsstyrning har gett lastbilar och andra tunga fordon möjlighet använda adaptiv farthållning till att köra med ett litet mellanrum och bilda vägkolonner. De kan då utnyttja vindsuget från fordonet framför och på så vis sänka bränsleförbrukningen. En central utmaning i skapandet av dessa kolonner är att fordonen inte har gemensamma startpunkter och destinationer. De delar i de flesta fall endast stycken av sin rutt med andra fordon, och turerna behöver då sammanfalla i tid. Denna studie använder deltagande designmetodik för att designa ett interaktivt visualiseringsverktyg som kan hjälpa forskare att studera skapandet av lastbilskolonner i simulerade scenarion. Tre transportforskare deltog i intervjuer och två cykler av workshops för att synliggöra och formulera arbetsuppgifter som kunde förbättra deras förståelse av simulationerna. Den primära deltagande design-frågan var “när bildas kolonner och hur stora är de?” För att förankra och driva diskussionen kring designen framåt utvecklades en prototyp som viderutvecklades efter varje deltagande designcykel. Interfacet i den resulterande prototypen och består av fyra paneler: 1) en geografisk panel som innehåller en kartvy; 2) en panel med tidslinjer för både fokus och kontext; 3) en anpassningspanel med detaljer på fordonens relationer; och 4) en filtreringspanel med ett parallellt koordinatsystem. Resultatet av studien indikerar ett behov ett flexibel visuellt analysverktyg som tillåter forskare att studera hur fordonen påverkas av förändringar i resplaner och vilken anpassning som krävs för att möta upp andra fordon för kolonnbildning.

Traffic congestion and safety has become a major issue in the modern world's commute. Congestion has been causing people to travel billions of hours more and to purchase billions of gallons of fuel extra which account to congestion cost of billions of dollars. Autonomous driving vehicles have been one solution to this problem because of their huge impact on efficiency, pollution, and human safety. Also, extensive research has been carried out on control design of vehicular platoons because a further improvement in traffic throughput while not compromising the safety is possible when the vehicles in the platoon are provided with better predictive abilities. Motion control is a key area of autonomous driving research that handles moving parts of vehicles in a deliberate and controlled manner. A widely worked on problem in motion control concerned with time parameterized reference tracking is trajectory tracking. Having an efficient and effective tracking algorithm embedded in the autonomous driving system is the key for better performance in terms of resources consumed and tracking error. Many tracking control algorithms in literature rely on an accurate model of the vehicle and often, it can be an intimidating task to come up with an accurate model taking into consideration various conditions like friction, heat effects, ageing processes etc. And typically, control algorithms rely on periodic execution of the tasks that update the control actions, but such updates might not be required, which result in unnecessary actions that waste resources. The main focus of this work is to design an intermittent model-free optimal control algorithm in order to enable autonomous vehicles to track trajectories at high-speeds. To obtain a solution which is model-free, a Q-learning setup with an actor-network to approximate the optimal intermittent controller and a critic network to approximate the optimal cost, resulting in the appropriate tuning laws is considered. / Master of Science / A risen research effort in the area of autonomous vehicles has been witnessed in the past few decades because these systems improve safety, comfort, transport time and energy consumption which are some of the main issues humans are facing in the modern world’s highway systems. Systems like emergency braking, automatic parking, blind angle vehicle detection are creating a safer driving environment in populated areas. Advanced driver assistance systems (ADAS) are what such kind of systems are known as. An extension of these partially automated ADAS are vehicles with fully automated driving abilities, which are able to drive by themselves without any human involvement. An extensively proposed approach for making traffic throughput more efficient on existing highways is to assemble autonomous vehicles into platoons. Small intervehicle spacing and many vehicles constituting each platoon formation improve the traffic throughput significantly. Lately, the advancements in computational capabilities, in terms of both algorithms and hardware, communications, and navigation and sensing devices contributed a lot to the development of autonomous systems (both single and multiagent) that operate with high reliability in uncertain/dynamic operating conditions and environments. Motion control is an important area in the autonomous vehicles research. Trajectory-tracking is a widely studied motion control scenario which is about designing control laws that force a system to follow some time-dependent reference path and it is important to have an effective and efficient trajectory-tracking control law in an autonomous vehicle to reduce the resources consumed and tracking error. The goal of this work is to design an intermittent model-free trajectory tracking control algorithm where there is no need of any mathematical model of the vehicle system being controlled and which can reduce the controller updates by allowing the system to evolve in an open loop fashion and close the loop only when an user defined triggering condition is satisfied. The approach is energy efficient in that the control updates are limited to instances when they are needed rather than unnecessary periodic updates. Q-learning which is a model-free reinforcement learning technique is used in the trajectory tracking motion control algorithm to make the vehicles track their respective reference trajectories without any requirement of their motion model, the knowledge of which is generally needed when dealing with a motion control problem. The testing of the designed algorithm in simulations and experiments is presented in this work. The study and development of a vehicle platform in order to perform the experiments is also discussed. Different motion control and sensing techniques are presented and used. The vehicle platform is shown to track a reference trajectory autonomously without any human intervention, both in simulations and experiments, proving the effectiveness of the proposed algorithm.

Most phenomena in engineering fields involve physical variables that can potentially be predicted using simple or complex mathematical models. However, traffic engineers and researchers are faced with a complex challenge since they have to deal with the human element. For instance, it can be stated that the biggest challenge facing researchers in the area of car-following theory relates to accounting for the human-in-the-loop while modeling the longitudinal motion of the vehicles. In fact, a major drawback of existing car-following models is that the human-in-the-loop is not modeled explicitly. This is specifically important since the output from car-following models directly impacts several other factors and measures of effectiveness, such as vehicle emissions and fuel consumption levels. The main contribution of this research relates to modeling and incorporating, in an explicit and independent manner, the human-in-the-loop component in car-following theory in such a way that it can be either activated or deactivated depending on if a human driver is in control of the vehicle. That would ensure that a car-following model is able to reflect the different control and autonomy levels that a vehicle could be operated under. Besides that, this thesis offers a better understanding of how humans behave and differ from each other. In fact, through the implementation of explicit parameters representing the human-in-the-loop element, the heterogeneity of human behavior, in terms of driving patterns and styles, is captured. To achieve its contributions, the study starts by modifying the maximum acceleration vehicle-dynamics model by explicitly incorporating parameters that aim to model driver behavior in its expression making it suitable for the representation of typical acceleration behavior. The modified variant of the model is demonstrated to have a flexible shape that allows it to model different types of variations that drivers can generate, and to be superior to other similar models in that it predicts more accurate acceleration levels in all domains. The resulting model is then integrated in the Rakha-Pasumarthy-Adjerid car-following model, which uses a steady-state formulation along with acceleration and collision avoidance constraints to model the longitudinal motion of vehicles. The validation of the model using a naturalistic dataset found that the modified formulation successfully integrated the human behavior component in the model and that the new formulation decreases the modeling error. Thereafter, this dissertation proposes a new car-following model, which we term the Fadhloun-Rakha model. Even though structurally different, the developed model incorporates the key components of the Rakha-Pasumarthy-Adjerid model in that it uses the same steady state formulation, respects vehicle dynamics, and uses very similar collision-avoidance strategies to ensure safe following distances between vehicles. Besides offering a better fit to empirical data, the Fadhloun-Rakha model is inclusive of the following characteristics: (1) it models the driver throttle and brake pedal input; (2) it captures driver variability; (3) it allows for shorter than steady-state following distances when following faster leading vehicles; (4) it offers a much smoother acceleration profile; and (5) it explicitly captures driver perception and control inaccuracies and errors. Through a quantitative and qualitative evaluation using naturalistic data, the new model is demonstrated to outperform other state-of-the-practice car-following models. In fact, the model is proved to result in a significant decrease in the modeling error, and to generate trajectories that are highly consistent with the observed car-following behavior. The final part of this study investigates a case in which the driver is excluded and the vehicles are operating in a connected environment. This section aims to showcase a scenario in which the human-in-the-loop is deactivated through the development of a platooning strategy that governs the motion of connected cooperative multi-vehicle platoons. / Doctor of Philosophy / Even though the study of the longitudinal motion of vehicles spanned over several decades leading to the development of more precise and complex car-following models, an important aspect was constantly overlooked in those models. In fact, due to the complexity of modeling the human-in-the-loop, the vehicle and the driver were almost always assumed to represent a single entity. More specifically, ignoring driver behavior and integrating it to the vehicle allowed avoiding to deal with the challenges related to modeling human behavior. The difficulty of mathematically modeling the vehicle and the driver as two independent components rather than one unique system is due to two main reasons. First, there are numerous car models and types that make it difficult to determine the different parameters impacting the performance of the vehicle as they differ from vehicle to vehicle. Second, different driving patterns exist and the fact that they are mostly dependent on human behavior and psychology makes them very difficult to replicate mathematically. The research presented in this thesis provides a comprehensive investigation of the human-in-the-loop component in car-following theory leading to a better understanding of the human-vehicle interaction. This study was initiated due to the noticeable overlooking of driver behavior in the existing literature which, as a result, fails to capture the effect of human control and perception errors.

Electric trucks and platooning technology are expected to be part of the transportation system in the near future. Therefore, it is important to develop platoon coordination strategies and study the potential of platooning for when trucks are electric. In this paper, we study the platoon coordination problem at a single charging station where electric trucks can charge while they wait for other trucks to form platoons with.We assume all trucks to have identical routes after the charging station. The objective is to maximize the total reward of all trucks, including the platooning profit and cost of waiting.Moreover, the trucks have waiting time constraints to respect their mission deadlines and charging time constraints to make sure they can travel between the hub and destination without running out of battery. The energy consumption is decreased when driving as a follower truck in a platoon, which decreases the minimum charging time for the truck. We formulate the platoon coordination problem of electric trucks as a linear integer optimization problem. To evaluate the method, it was compared to a simpler coordination method. The savings from platooning with electric vehicles, using both coordination methods, were also compared to platooning with diesel trucks. The results showed that platooning with electric vehicles can save up to 10% of the driving cost and therefore have significant economic benefits. It was also shown that the method has an acceptable computational efficiency for real-time coordination. / Inom en snar framtid förväntas elektriska lastbilar och platooning vara en del av transportsystemet. Det är därför viktigt att utveckla strategier för platoonkoordinering och undersöka potentialen av platooning med elektriska lastbilar. I det här pappret studerar vi ett platoonkoordineringsproblem med en gemensam startpunkt och en gemensam slutpunkt för alla lastbilar. Startpunkten är en laddningsstation där lastbilarna kan kombinera laddning med att vänta in andra lastbilar att forma platooner med. Lastbilarna i systemet har även samma rutt mellan de två punkterna. Målet är att maximera den totala vinsten för alla lastbilar, med hänsyn till både platooningvinsten och kostnaden för att vänta. Utöver det har lastbilarna begränsad väntetid för att hålla sina deadlines. Vi behöver även ta hänsyn till lastbilarnas laddningstider då de behöver ha tillräckligt med laddning för att åka hela resan från startpunkt till slutdestination. Energikonsumtionen minskar när en lastbil åker som följare vilket minskar den minimala laddningstiden som behövs för att åka hela sträckan. Vi formulerar koordineringsproblemet med elektriska lastbilar som ett linjärt heltalsoptimeringsproblem. För att utvärdera metoden jämfördes den med en enklare koorineringsmetod. Besparingarna från platooning med elektriska lastbilar, med båda koordineringsmetoderna, jämfördes även med platooning med diesellastbilar. Resultatet visade att platooning med ellastbilar kan spara upp till 10% av körkostnaderna och har därför betydande ekonomiska fördelar. Det visades också att metoden har en acceptabel beräkningseffektivitet för koordinering i realtid. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Abstract Although researchers have studied the effects of platooning, most of the work done so far has focused on fuel consumption. There are a few studies that have targeted the impact of platooning on the highway operations and safety. This thesis focuses on the impact of heavy-duty vehicles (HDVs) platooning on highway characteristics. Specifically, this study aims at evaluating the effects of platooning of HDVs on capacity, safety, and CO2 emissions. This study is based on a hypothetical model that was created using the VISSIM software. VISSIM is a powerful simulation software designed to mimic the field traffic flow conditions. For model validity, the model outputs were compared with recommended values from guidelines such as the Highway Capacity Manual (HCM) (Transportation Research Board, 2016). VISSIM was used to obtain the simulation results regarding capacity. However, in addition to VISSIM, two other software packages were used to obtain outputs that cannot be assessed in VISSIM. MOVES and SSAM are two simulation software packages that were used for emission and safety metrics, respectively. Both software packages depended on input from VISSIM for analysis. It was found that with the presence of HDVs in the model, the capacity, the emission of CO2, and the safety of the roadway would improve positively. A capacity of 4200 PCE/h/ln could be achieved when there are enough HDVs in platoons. Furthermore, more than 3% of the traffic flow emission of CO2 reduction is possible when 100% of the HDVs used in the model are in platoons. In addition to that, a reduction of more than 75% of the total number of conflicts might be obtained. Furthermore, with the analysis of the full factorial method and the Design of Experiment (DOE) conducted by using Excel and Minitab respectively, it was possible to investigate the impact of the platoons’ factors on the highway parameters. Most of these factors affect the parameters significantly. However, the change in the desired speed was found to insignificantly affect the highway parameters, due to the high penetration rate. Keywords: VISSIM, MOVES, SSAM, COM-interface, HDVs, Platooning, Number of Conflicts

Automated vehicles promise to be one of the most constructive inventions of late as they promote road safety, fuel efficiency, and reduced time road travel, by decreasing traffic congestion and workload on the driver. In a platoon (which is a method of grouping vehicles, which helps increase the capacity of roads by managing the distance between vehicles by using electrical and mechanical coupling) of such automated vehicles, as in automated highway systems (AHS), tracking of inter-vehicular spacing is one of the significant factors to be considered. Because of the close spacing, computer-controlled platoons with inter-vehicular communication, which is the concept of adaptive cruise control (ACC), become open to cyber security attacks. Cyber physical and cyber attacks on smart grid systems in the electricity market have been a focus of researchers, and much work has been done on that front. However, cyber physical (CP) attacks on autonomous vehicle platoons have not been examined. Thus this research entails the survey of a number of vehicle models used in different works pertaining to longitudinal vehicle motion and analysis of a special class of cyber physical attacks called false data injection (FDI) attacks on vehicle platoons moving with longitudinal motion. In this kind of attack, an attacker can exploit the configuration of any cyber physical system to launch such attacks to successfully introduce arbitrary errors into certain state variables so as to gain control over the system. So here, an n-vehicle platoon is considered and a linearized vehicle model is used as a testbed to study vehicle dynamics and control, after false information is fed into the system.

Blockchain technology emerged in 2009 together with the introduction of Bitcoin, the first virtual currency which enabled nodes in a network, that do not necessarily trust each other, to exchange digital value without the use of trusted intermediaries. Since then, the idea of disintermediation and decentralization has gained traction in a large number of applications outside the world of finance and virtual currencies. This thesis is written in collaboration with Scania, an automotive industry manufacturer, with the purpose of gaining a better understanding of blockchain technology and how it can be used in the transportation industry. This thesis proposes five potential blockchain use cases that aim to either enhance Scania’s existing services or to create new services. Out of these five use cases, one is deemed inappropriate in regards to the use of blockchain technology while the other four have potentials benefits. The common denominator among these use cases is that they are decentralized in nature meaning that the use of intermediaries is mitigated. It is recognized that all use cases could be implemented using traditional, centralized databases and that the use of blockchain boils down to a technology choice with its own trade-offs relative to other potential choices. This thesis concludes that blockchain technology offers a new kind of database architecture, the main benefit of which is that it lets several non-trusting entities agree on a common set of facts, without having a trusted intermediary establishing these facts.