This report proposes a solution for an automated vehicle follower based on one front-facing monocular camera that can be used to achieve platooning for a lower cost than the systems available on the market today. The sensor will be local to the automated follower vehicle, i.e. no Vehicle-to-Vehicle (V2V) communication. A state-of-the-art chapter describes di erent aspects of platooning, computer vision techniques, state of the art hardware developed especially for autonomous driving as well as systems closely related to the proposed solution. The theory behind the performed implementations such as trajectory, controls, image operations and vehicle models will be presented, followed by a chapter dedicated to the actual implementation. The experimental vehicle used to validate the solution was a modied 1=12 scale radio controlled (RC) car. An Arduino controls the steering and driving motor, and a PC mounted on the vehicle uses a webcam to capture images. The preceding vehicles position relative the follower vehicle was calculated from captured images from the webcam and a trajectory towards the preceding vehicles path was generated from a cubic curve. Measurements from a stereo vision system was used to evaluate the accuracy of the follower vehicle and minimal spacing needed between follower and preceding vehicle. The follower vehicle satisfy the behavior of following a preceding vehicle, but the accuracy of the follower vehicle should be improved to generate a more accurate trajectory before being tested on a larger scale vehicle. The solution shows that a monocular camera can be used to follow a vehicle, and with implementation of a GPS module and a fuzzy velocity controller it could be used to test on a full sized vehicle. / Denna rapport foreslar en losning som gor det mojligt att automatisera ett fordon genom en monokular kamera som foljer en framforvarande ledbil som skulle kunna anvandas inom platooning for en lagre kostnad an de losningar som nns pa marknaden idag. Sensorn ar lokal till det automatiserade fordonet och anvander sig inte utav V2V kommunikation. Ett state-of-the-art kapitel beskriver olika aspekter inom platooning av fordon, datorseende, specikt framtagen hardvara for automatiserade bilar samt automatiserande system som nns inkluderade i bilar idag. Teorin bakom implementationen av bilens trajektoria, reglerteknik, bildbehandlingsoperationer och fordonsmodeller presenteras ocksa. Teorin anvands sedan for att utveckla en prototyp som anvands till att besvara forskningsfragorna. Prototypfordonet ar en modierad radiostyrd bil i skala 1/12. En Arduino styr drivmotor och styrning medan en PC monterad pa bilen anvander sig av en webbkamera for att ta bilder. Ledbilens position relativt foljbilen beraknas med hjalp av bilderna och en bana att folja efter genereras av en tredjegradskurva. Matningar genom ett stereo vision system anvandes for att besvara fragor angaende noggranheten for den utvecklade efterfoljande bilen samt lagsta sakra avstand som kan anvandas mellan bilarna. Den utvecklade prototypbilen foljer efter ledbilen pa ett onskvart satt, dock borde trajektorian som den foljer utvecklas mera innan testning utfors pa storre fordon. Losningen pavisar att en monokular kamera kan anvandas for att folja efter en bil. Om systemet utokas med en GPS modul och en fuzzy hastighetskontroll kan denna losning testas med bilar i full storlek.

Maritime target tracking from an airborne radar faces many issues due to the features of theenvironment, the targets to be tracked and the movement of the radar platform. Therefore, aunique tracking algorithm is not always able to reach the best possible performance for everyencountered situation. It needs to self-adapt to the environment and to the targets which areobserved in order to always be as ecient as possible. Adaptability is thus a key issue of radartracking.Several implementations of the mathematical Bayesian estimation theory, commonly called lters,have been used in the literature in order to estimate as precisely as possible targets trajectory.Depending on the situations and the assumptions that are considered, some of themare expected to perform better. This thesis suggests to look deeper into the tracking techniquesthat can be found in the literature and compare them in order to dene more precisely the advantagesof each of them over the others. This should enable to wisely choose the method thatis most likely to provide the best performance for a given situation. In particular, the nonlinearconversion between the Cartesian coordinates with which the state vector is dened and thespherical coordinates used for the measurements is investigated. A measure of nonlinearity isintroduced, studied and used to compare the extended Kalman lter and the particle lter.The size of the detected maritime targets is a special feature that makes it possible to draw amaneuverability-based classication which enables to adapt the tracking technique to be used.Joint tracking and classication (JTC) has already been described in the literature with a specicmeasurement model. This thesis makes this model more realistic using a random distribution ofthe reection point on the target's shape. The tracking method is modied to take into accountthis new measurement model and some simulations are run.This modied JTC algorithm proves to be more ecient than the JTC structure presented inthe literature. Eventually, this thesis shows that nonlinearity is a paramount issue that needsto be considered to implement an ecient self-adapatable radar tracking algorithm, this beingespecially true for extended targets. / Maritim malfoljning fran en luftburen radar star infor manga problem pa grund av miljons karaktar, de mal som ska sparas och radarplattformens rorelse. Darfor kan en unik sparningsalgoritminte na basta mojliga prestanda for varje situation som uppstar. Den maste anpassa sig sjalvtill miljon och till de mal som overvakas for att bli sa eektiv som mojligt. Anpassningsformagaar alltsa en viktig fraga inom radarsparning.Flera implementeringar av den matematiska Bayesianska berakningsteorin, vanligtvis kalladelter, har anvants i litteraturen for att forutsaga malbanor sa exakt som mojligt. Beroendepa situationer och antaganden som beaktas forvantas vissa av dem bli battre. Denna avhandlingforeslar att noggrant undersoka sparningsteknikerna som kan hittas i litteraturen ochjamfora dem for att mer precist deniera fordelarna av var och en framfor de andra. Det skulleunderlatta ett klokt val av metoden som mest sannolikt ger basta prestanda for varje given situation.Sarskilt undersoks den icke-linjara omvandlingen mellan kartesiska koordinatsystemet,som denierar tillstandsvektorn, och sfariska koordinater som anvands for matningarna. Ettmatt pa icke-linjaritet presenteras, studeras och anvands for att jamfora ett utokat Kalmanltermed partikelltret.Storleken pa de detekterade maritima malen ar en speciell egenskap som gor det mojligt attgora en klassicering baserad pa manovrerbarhet som hjalper till att anpassa sparningsteknikensom ska anvandas. Simultan foljning och klassiering, "joint tracking and classication" (JTC)pa engelska, har redan beskrivits i litteraturen med en specik matmodell. Denna avhandlinggor modellen mer realistisk med hjalp av en slumpmassig fordelning av reektionspunkten pamalets form. Sparningsmetoden ar modierad for att beakta denna nya matmodell och nagrasimuleringar utfors.Denna modierade JTC-struktur visar sig mer eektiv an JTC-strukturen som presenteras ilitteraturen. Slutligen visar denna avhandling att icke-linjaritet ar en viktig fraga som mastebeaktas for att erhalla en eektiv radarsparningsalgoritm som kan anpassa sig sjalv. Dettagaller sarskilt for utstrackta mal.