Indiana University-Purdue University Indianapolis (IUPUI) / Autonomous Emergency Braking (AEB) system uses vehicle’s on-board sensors such as radar, LIDAR, camera, infrared, etc. to detect the potential collisions, alert the driver and make safety braking decision to avoid a potential collision. Its limitation is that it requires clear line-of-sight to detect what is in front of the vehicle. Whereas, in current V2V (vehicle-to-vehicle communication) systems, vehicles communicate with each other over a wireless network and share information about their states. Thus the safety of a V2V system is limited to the vehicles with communication capabilities. Our idea is to integrate the complementary capabilities of V2V and AEB systems together to overcome the limitations of V2V and AEB systems. In a V2V-AEB system, vehicles exchange data about the objects information detected by their onboard sensors along with their locations, speeds, and movements. The object information detected by a vehicle and the information received through the V2V network is processed by the AEB system of the subject vehicle. If there is an imminent crash, the AEB system alerts the driver or applies the brake automatically in critical conditions to prevent the collision. To make V2V-AEB system advance, we have developed an intelligent heart Monitoring system and integrated it with the V2V-AEB system of the vehicle. The advancement of wearable and implantable sensors enables them to communicate driver’s health conditions with PC’s and handheld devices. Part of this thesis work concentrates on monitoring the driver’s heart status in real time by using fitness tracker. In the case of a critical health condition such as the cardiac arrest of a driver, the system informs the vehicle to take an appropriate operation decision and broadcast emergency messages over the V2V network. Thus making other vehicles and emergency services aware of the emergency condition, which can help a driver to get immediate medical attention and prevent accident casualties. To ensure that the effectiveness of the V2V-AEB system is not reduced by a time delay, it is necessary to study the effect of delay thoroughly and to handle them properly. One common practice to control the delayed vehicle trajectory information is to extrapolate trajectory to the current time. We have put forward a dynamic system that can help to reduce the effect of delay in different environments without extrapolating trajectory of the pedestrian. This method dynamically controls the AEB start braking time according to the estimated delay time in the scenario. This thesis also addresses the problem of communication overload caused by V2V-AEB system. If there are n vehicles in a V2V network and each vehicle detects m objects, the message density in the V2V network will be n*m. Processing these many messages by the receiving vehicle will take considerable computation power and cause a delay in making the braking decision. To prevent flooding of messages in V2V-AEB system, some approaches are suggested to reduce the number of messages in the V2V network that include not sending information of objects that do not cause a potential collision and grouping the object information in messages.

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Kraven på säkerhet och effektivitet ökar ständigt inom fordonsindustrin. För att uppfylla dessa strävar fordonstillverkare efter att uppnå en högre grad av autonomi, detta innebär dock att många problem måste lösas. Denna rapport behandlar ett av dessa, autonoma fordons möjlighet att identifiera utryckningsfordon. Målet är att presentera ett förslag på vilken teknik som anses mest lämpad för autonoma fordon att kommunicera med utryckningsfordon. Arbetet grundade sig i en förstudie där standarden ITS G5, IEEE 802.11g, ZigBee samt mobilnät analyserades utifrån deras tekniska specifikationer. Utifrån analysen presenterades tre situationer där de olika teknikernas användning ansågs begränsade, i tunnlar, i tät trafik samt på långa avstånd vid höga hastigheter. Dessa situationer ställde krav på teknikerna inom bland annat svarstid, räckvidd, överföringsförmåga samt möjlighet till direktkommunikation mellan fordonen. Utifrån dessa krav ställdes en jämförelsematris upp där de olika teknikernas prestanda jämfördes. Resultatet visar att ITS G5 och ZigBee har bäst prestanda på egen hand medan en kombination av mobilnät och ITS G5 uppnår högst prestanda. / The demand for safety and effectivity continuously increases within the automotive industry. One way to meet these demands is to achieve a higher level of autonomy, but to achieve the highest levels of autonomy there is a few problems to be solved along the way. This report treats one of these, an autonomous vehicle’s ability to identify emergency vehicles. The report, based on a pilot study, analyses the ITS G5 standard, IEEE 802.11g, Zigbee and mobile networks based on their technological specifications. From the analysis three situations are identified where the technologies are considered limited. These limitations are, but not limited to, reach, latency, data rates and ability to communicate vehicle to vehicle (V2V). The four technologies are then compared by these limitations in a matrix. The result shows that ITS G5 and ZigBee has the best performance by its own but the combination of mobile networks and ITS G5 shows the highest possible performance.

Unmanned aerial vehicles are becoming more popular in today’s society, which results in the rise of laws intended to maintain safety. To abide by these, while allowing the technology to expand, functioning path-planning algorithms are required.This also includes having methods for detecting and managing obstacles. This project aims to improve an existing path-planning algorithm that is based on A* and implemented in Python.The solution consisted of using functions for finding polytopeintersection,as well as optimizing the collision avoidance and the search algorithm. In addition to that, realistic constraints were implemented on the generated trajectory in order to reflect real-life limitations. The results demonstrated that the paths were always feasible, with respect to input and position constraints. The program’s computation time was also reduced up to 89% of the original run-time. There is, however, still room for improvement since the original code generated a shorter path for the three scenarios it was created for. On the other hand,the improved algorithm could handle a new scenario, which the original code failed to do. / Obemannade flygfarkoster blir alltmer vanliga i dagens samhälle, vilket resulterar i uppkomsten av nya lagar ämnade åt att upprätthålla säkerhet. För att förhålla sig till dessa, samtidigt som teknologin tillåts expandera, krävs fungerande vägplaneringsalgoritmer. Där ingår det även att ha metoder för att upptäcka och hantera hinder. Detta projekt syftar till att förbättra en befintlig vägplaneringsalgoritm som är baserad på A* och implenterad i Python. Lösningsmetoden bestod av att använda inbyggda Python-funktioner ämnade åt att finna skärningar mellan polytoper, samt optimera kollisionshantering och sökalgoritmen. Dessutom infördes realistiska krav på den framställda vägen i syfte om att reflektera verlighetens begränsningar. Resultatet visade att vägarna alltid var genomförbara, med avseende på inmatningsoch positionsrelaterade villkor. Programmets beräkningstid hade även reducerats upptill 89% av den ursprungliga körtiden. Det finns dock utrymme för förbättringar då den ursprungliga koden generar en kortare väg för de tre scenarion den tillverkades för. Däremot kinde den förbättrade algoritmen hantera ett nytt scenario, en ursprungliga koden misslyckades med. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Research in Unmanned Air Vehicles (UAV's) continues to push the limitations of size and weight. As technical advances have made UAV's smaller and less expensive, they have become more flexible and extensive in their roles. To continue using smaller and less expensive components while retaining and even enhancing performance requires more sophisticated processing of sensor data in order for the UAV to accurately determine its state and thereby allow the use of feedback in controlling the aircraft automatically. This work presents a three-stage state-estimation scheme for the class of UAV's know as Miniature Air Vehicles (MAV's). The first stage estimates pitch and roll, the second stage estimates heading, and the third stage produces a position estimate and an estimate of wind speed and direction. All three stages make use of the extended Kalman filter, a framework for using a system dynamic model to predict future states and to update the predictions using weighted sensor measurements as they become available, where the weighting is based on the relative uncertainty of the dynamic model and the sensors. Using the three-stage state esti-mation scheme, significant improvements in the estimation of pitch, roll and heading have been achieved in simulation and flight testing. Performance of the navigation (position and wind) stage is comparable to an existing baseline algorithms for position and wind, and shows additional promise for use in dead reckoning when GPS updates become unavailable.

Humanity has always wanted to explore the world we live in and answer different questions about our universe. After the International Space Station will end its service one possible next step could be a Moon Outpost: a convenient location for research, astronaut training and technological development that would enable long-duration space. This location can be inside one of the presumed lava tubes that should be present under the surface but would first need to be inspected, possibly by machine capable of capturing and relaying a map to a team on Earth.In this report the past and future Moon base missions will be summarized considering feasible outpost scenarios from the space companies or agencies. and their prospected manned budget. Potential mission profiles, objectives, requirements and constrains of the BATonomous Moon cave Explorer (BAT-ME) mission will be discussed and defined. Vehicle and mission concept will be addressed, comparing and presenting possible propulsion or locomotion approaches inside the lava tube.The Inkonova “Batonomous™” system is capable of providing Simultaneous Localization And Mapping (SLAM), relay the created maps, with the possibility to easily integrate the system on any kind of vehicle that would function in a real-life scenario.Although the system is not fully developed, it will be assessed from a technical perspective, and proper changes for a viable system transition for the space-Moon environment will be devised. The transition of the system from the Batonomous™ state to the BAT-ME required state will be presented from the requirement, hardware, software, electrical and operational point of view.The mission will be devised into operational phases, with key goals in mind. Two different vehicles will be presented and designed on a high engineering level. A risk analysis and management system will be made to understand the possible negative outcomes of different parts failure on the mission outcome.

<p>Upon introducing semi- and fully automated vehicles on the road, drivers will be reluctant to focus on the traffic interaction and rely on the vehicles' decision-making. However, encountering pedestrians still poses a significant difficulty for modern automated driving technologies. Considering the high-level complexity in human behavior modeling to solve a real-world problem, deep-learning algorithms trained from naturalistic data have become promising solutions. Nevertheless, although developing such algorithms is achievable based on scene data collection and driver knowledge extraction, evaluation remains challenging due to the potential crash risks and limitations in acquiring ground-truth intention changes. </p> <p><br></p> <p>This study proposes a VR-based testing bed to evaluate real-time pedestrian intention algorithms as VR simulators are recognized for their affordability and adaptability in producing a variety of traffic situations, and it is more reliable to conduct human-factor research in autonomous cars. The pedestrian wears the head-mounted headset or uses the keyboard input and makes decisions in accordance with the circumstances. The simulator has added a credible and robust experience, essential for exhibiting the real-time behavior of the pedestrian. While crossing the road, there exists uncertainty associated with pedestrian intention. Our simulator will anticipate the crossing intention with consideration of the ambiguity of the pedestrian behavior. The case study has been performed over multiple subjects in several crossing conditions based on day-to-day life activities. It can be inferred from the study outcomes that the pedestrian intention can be precisely inferred using this VR-based simulator. However, depending on the speed of the car and the distance between the vehicle and the pedestrian, the accuracy of the prediction can differ considerably in some cases.</p>

<p dir="ltr">The future of the global economy lies in space. As the economic and scientific benefits from space become more accessible and apparent to the public, the demand for more spacecrafts will only increase. However, simply using the current space architecture to sustain any major activities past low Earth orbit is infeasible. The limiting factor of relying on ground operators via the Deep Space Network will blunt future growth in cislunar space traffic as the bandwidth is insufficient to satisfy the needs of every spacecraft in this domain. For this reason, spacecrafts must begin to operate autonomously or semi-autonomously for operators to be able to manage more missions at a given time. This thesis focuses on the guidance and navigation policies that could help vehicles such as logistical or resupply spacecrafts perform their rendezvous autonomously. It is found that using GNSS signals and Moon-based optical navigation has the potential to help spacecrafts perform autonomous orbit determination in near-Moon trajectories. The estimations are high enough quality such that a stochastic controller can use this navigation solution to confidently guide the spacecraft to a target within a tolerance before proximity operations commence. As the reliance on the ground is shifted away, spacecrafts would be able to operate in greater numbers outside of Earth's lower orbits, greatly assisting humanity's presence in space. </p>

<p dir="ltr">Traffic safety and congestion are global concerns. Autonomous vehicles (AVs) are expected to enhance transportation safety and reduce congestion. However, achieving their full potential requires 100% market penetration, a challenging task. This study addresses key issues in mixed traffic environments, where human-driven vehicles (HDVs) and connected autonomous vehicles (CAVs) coexist. A number of critical questions persist: 1) inadequate exploration of human errors (errors originating from non-CAV sources) in mixed traffic; 2): limited focus on information selection and learning efficiency in network-level rerouting, particularly in highly dynamic environments; 3) inadequacy of personalized element driver inputs in motion-planning frameworks; 4) lack of consideration of user privacy concerns.</p><p dir="ltr">With the goal of advancing the existing knowledge in this field and shedding light on these matters, this dissertation introduces multiple frameworks. These frameworks leverage connectivity and automation to improve safety and mobility in mixed traffic, addressing various research levels, including local-level and network-level safety enhancement, as well as network-level and global-level mobility enhancement. With optimization- and learning-based methods implemented (Model Predictive Control, Deep Neural Network, Deep Reinforcement Learning, Transformer model and Federated Learning), frameworks introduced in this dissertation are expected to help highway agencies and vehicle manufacturers improve the safety and efficiency of traffic flow in the mixed-traffic era. Our research findings revealed increased crash-avoidance rates in critical situations, enhanced accuracy in predicting lane changes, improved dynamic rerouting within urban areas, and the implementation of effective data-sharing mechanisms with a focus on user privacy. This research underscores the potential of connectivity and automation to significantly enhance mixed-traffic safety and mobility.</p>

En följd av såväl politiska beslut som den ökade medvetenheten hos kunder är att efterfrågan av grönare teknik har ökat. Idag står andelen av laddbara personbilar för ungefär en tredjedel av alla nyregistrerade personbilar i Sverige. Det är inte bara personbilstillverkare som går igenom detta teknikskifte mot grönare teknik och smartare självkörande bilar, samma trend ses i lastbilsindustrin. Även fast kunderna i detta fall är andra företag som t.ex. stora åkerier finns det även här en stor efterfrågan på den nya tekniken. Det kan tyckas motstridigt att tillverka ett elfordon som både ska klara av att transportera tung last samtidigt som det ska kunna erbjuda en lång räckvidd. Självkörande lastbilar är något som Scania tillsammans med flera stora lastbilstillverkare jobbar med att utveckla. De utmaningar som finns för lastbilstillverkare gällande det autonoma skiljer sig från personbilstillverkare. Syftet med rapporten är att undersöka hur produktutvecklingsprocessen påverkas av teknikskiftet mot eldrivna, autonoma lastbilar. Inledningsvis genomfördes en litteraturstudie där tidigare kända teorier och studier inom relevanta områden undersöktes för att få en bättre förståelse för det nuvarande kunskapsläget. Därefter hölls tre stycken semistrukturerade intervjuer med personer från olika avdelningar med olika kompetenser från företag inom dels lastbilsindustrin, men även personbilsindustrin. Intervjuerna syftade till att samla så mycket information som möjligt kring de utmaningar som lastbilsindustrin står inför ur ett produktutvecklings perspektiv. Även de förändringar som skett i samband med teknikskiftet var av intresse under intervjuerna. Efter intervjuerna gjordes en sammanställning och en analys av det resultat som framkommit under studien. Resultatet visar att det har skett en stor förändring inom industrin på flera områden. Nya arbetsmetoder har implementerats för att korta ned ledtiderna och öka kvaliteten på produkterna. Det finns ett ökat behov av nya kompetenser inom branschen och det blir allt vanligare att anställa personal från hela världen som kan arbeta på distans. Vidare satsas det allt mer på att omskola befintlig personal. Resultatet visar även att antalet samarbeten har ökat och att det sker ett stort informationsutbyte mellan företag som båda jobbar med autonom teknik. / An increasing demand for greener technology has been forced through by political decisions, but also as a result of growing awareness amongst customers. Today, the proportion of rechargeable passenger cars accounts for about a third of all newly registered passenger cars in Sweden. It is not just passenger car manufacturers who are experiencing this shift towards greener technology and smarter autonomous cars. The same trend can be seen in the truck industry, even if the customers in this case are large hauliers. It may seem contradictory to manufacture a vehicle that must both be able to transport heavy loads and withstand long range. Scania, amongst other big truck manufacturers, has come a long way in developing autonomous trucks. The challenges of truck manufacturers differ from those of passenger car manufacturers regarding autonomous technology. This study will investigate how the product development process is affected by the shift in technologytowards electric, autonomous trucks.Initially, a literature study was conducted where previous theories and studies in relevant areas were examined in order to gain a better understanding of the current state of knowledge. Subsequently, three semi-structured interviews were held with people from different departments and with various competences from companies in both the truck and car industries. The aim of the interviews was to gather as much information as possible about the challenges facing the truck industry from the product development perspective. The changes that have taken place as a result of the technology shift were also of interest in the interviews. Afterwards, an analysis summary was made of the results that emerged during the study. The results show that there has been significant change in several areas within the industry. New working methods have been implemented to shorten lead times and increase the quality of the products. There is a growing need for new skills within the industry and it is becoming increasingly common to employ staff from all over the world who can work remotely. At the same time, more and more funding is going towards further training of existing staff. The results also show that the number of collaborations has increased and that there is a large exchange of information between companies that are in the autonomous technology business.