<p>Denna rapport beskriver ett examensarbete för högskoleingenjörsexamen i elektroteknik vid Växjö Universitet. Syftet är att konstruera ett styrsystem till en robotbil, ett program som hindrar bilen från att krocka med omgivningen. Roboten ska även kunna styras från en dator via ett grafiskt gränssnitt implementerat i Labview. Nödvändig hårdvara för styrning och kommunikation har konstruerats.</p><p>Det har behövts tre olika programmeringsspråk för att nå de krav som har ställts på uppgiften, C, Perl och Labview. Microprocessorn i robotbilen har programmerats i C och gör bilen helt autonom, endast beroende av signaler från avståndssensorer. Avlusningsprogrammet skrevs i Perl och styrningen från datorn har implementerats i Labview. Avlusningsprogrammet togs fram på grund av att det blev svårt att hålla koll på allt som skedde med värden och beräkningar i den automatiska styrningen av robotbilen.</p> / <p>This thesis describes a project for the bachelor degree in electrical engineering at Växjö University. The purpose with this project is to construct a guidance system for a robot car, a program that prevents the car from colliding with objects when moving without external control. The robot could also be controlled from the computer through a virtual instrument implemented in Labview. The necessary hardware for steering and communicating has been constructed. The software is implemented using three different programming languages, C, Perl and Labview.</p>

Traffic congestion on urban road networks has been recognized as one of the most serious problems with which modern cities are confronted. It is generally anticipated that Dynamic Route Guidance Systems (DRGS) will play an important role in reducing urban traffic congestion and improving traffic flows and safety. One of the most critical issues in designing these systems is in the development of optimal routing strategies that would maximize the benefits to overall system as well as individual users. Infrastructure based DRGS have advantage of pursuing system optimal routing strategy, which is more essential under abnormal traffic conditions such as non-recurrent congestion and natural disaster. However user compliance could be a problem under such a strategy, particularly when some of equipped drivers are urged not to choose minimum travel time path for the sake of improving the total network travel time. On the other hand, In-vehicle based DRGS can utilize the user-specified route selection criteria to avoid "Braess Paradox" under normal traffic conditions. However, it may be of little use under abnormal traffic conditions and high DRGS market penetration. In conducting the comparative analysis between system optimal strategy and user equilibrium strategy, significant differences were found within the mid-range traffic demand. The maximum total travel time difference occurs when the level of traffic demand is half of the system capacity. At this point, system optimal route guidance strategy can save more than 11% of the total travel time of user equilibrium route guidance strategy. The research proposes an adaptive routing strategy as an efficient dynamic route guidance under non-recurrent traffic congestion. Computation results show that there is no need to implement system optimal routing strategy at the initial stage of the incident. However, it is critical to use system optimal routing strategy as freeway and arterial are getting congested and the queue delay in freeway increases. The adaptive routing strategy is evaluated using Traffic simulation model, INTEGRATION. According to simulation results using an ideal network, the travel time saving ratio is maximum when both arterial and freeway have normal traffic demand under incident. In case of a realistic network, the adaptive routing strategy also proved to save the total travel time between 3% to 10% over the traditional user equilibrium routing strategy. The reduction of total travel time increases as the incident duration increases. Consequently, it is concluded that the adaptive routing strategy for DRGS is more efficient than using user equilibrium routing strategy alone. / Ph. D.

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.

Software is the crux of many commercial, industrial and military systems. The software systems need to be very reliable especially in case of safety critical systems. Unmanned Aerial Vehicle (UAV) and manned aircraft are safety critical systems and hence failures related to software or software-hardware interaction leads to huge problems. The software systems need to be certified before they are deployed. Even after being certified several accidents and incidents have occurred and are occurring. The software errors can occur during any phase of software development. The reliability of the software is enhanced using the verification process. Runtime monitoring has various advantages over testing and model checking. Hence this thesis work explores runtime monitoring of UAV. The runtime monitoring shall verify the run of the current system state. The runtime monitoring shall monitor the health of the UAV and shall report to the operator about its status. The software faults and errors if not prevented shall lead to software failure. UAV lacks the situational awareness due to absence of pilot onboard. This motivated to use runtime monitor to enhance the situation awareness. The runtime monitor shall detect the software errors and avoid failures. This monitor shall also enhance the situational awareness of the remote operator. The runtime monitor that enhance situation awareness shall not only be applicable to specific UAV but this shall be applicable to all the UAV’s. Hence this work provides an independent Generic Runtime Monitor (GRM) to enhance the situation awareness. The runtime monitor has various methods but using formal specifications in specific using Linear Temporal Logic(LTL) to generate monitor is considered in this work. Runtime monitoring makes UAV more safe and at the same time reduces the costs as it verifies only the current run of the system state by providing a detection of critical errors. The situation awareness includes functional and environmental states that remote pilot shall not be aware of. The architecture plays vital role for the system design. GRM architecture is one such architecture which chalks out the overall independent system design for the runtime monitoring of the UAV system. This architecture is an extensible one. The generic requirements were elicited from different sources such as Aircraft Incidents and Accidents, Boeing Aero Magazine, Autonomous Rotorcraft Testbed for Intelligent Systems (ARTIS) requirements, generic Autonomy Levels for Unmanned Rotorcraft Systems (ALFURS) framework etc. The situation awareness can be categorized into three levels namely perception, comprehension and projection. The requirements were elicited for all the three levels of situation awareness. These requirements further formalized using temporal logics. The formalized requirements further translated into state automaton automatically.

Dans ces travaux, nous proposons un système de guidage automatique pour la navigation sûre d'un robot mobile dans un monde ouvert. Le principe est de contrôler la direction et la vitesse du véhicule afin de préserver son intégrité physique et celle de son environnement. Cela se traduit par la généralisation du concept d'obstacle permettant d'estimer l'espace de vitesses admissibles par le véhicule en fonction de la surface de navigation, des capacités du véhicule et de son état. Afin d'atteindre cet objectif, le système doit pour chaque itération : 1) fournir à la tâche de perception une zone sur laquelle elle devra focaliser son attention pour la reconstruction de l'environnement ; 2) générer des trajectoires admissibles par le véhicule ; 3) estimer le profil de vitesse admissible pour chacune d'entre elles ; 4) pour finir, sélectionner la plus optimale par rapport à un critère prédéfini. Des résultats simulés et obtenus sur un démonstrateur réel permettent d'analyser les performances obtenues du système face à des scénarios divers et en démontre la pertinence. / In this work, we propose an automatic guidance system for safe navigation of a mobile robot in an open environment. The principle is to control the direction and the speed oh the vehicle in order to preserve its physical integrity and that of its environment. That results in the generalization of obstacle's concept to estimate the admissible speeds of the vehicle taking into account the surface navigation, the capabilities of the vehicle and its state. To accomplish this objective, th system has to ; 1) provide to the perception task an area on witch it can focus its attention to build the environment, 2) generate acceptable trajectories by th vehicles ; 3) estimate the admissible speed profile for each of them, 4) finally, select the most optimal with respect to a predefined criterion. Simulated and real results show the performance of the system obtained against various scenarios.