Racing drivers always want to traverse path at vehicle’s maximum performance limits while keeping the vehicle at its ideal trajectory. The main objective of this report is to elaborate strategy for the path following problem in which driver has to follow the predefined 2D roads. New steering controller design for closed loop racing driver model in Dymola vehicle dynamics library is developed. The methodology proposed by Sharp et al. [2] is followed with the optimal velocity profile that tries to mimic the actions of the real drivers in real time scenarios. Vehicle handling limits i.e. longitudinal and lateral limits are defined before simulation. While travelling in the neighbourhood of optimal velocity on the straight road as well as during the curves, the performance of the steering controller is tested by conducting the test on J turn, Clothoid, Extended chicane and the closing curve path and also tested during the different environment effects e.g. when there is a side wind affecting the vehicle. Performance of existing and new steering controllers discussed and compared in result chapter. It is ensured that the drawbacks in the existing steering controller are eliminated by using the proposed methodology in new implemented steering controller. Key Words: Driver Model, Steering Controller, Path following, Velocity profile

The safety requirements for vehicles are today high and they will become more stringent in the future. The car companies test their products every day to ensure that safety requirements are met. These tests are often done by professional drivers. If the car is tested in an everyday traffic situation, a normal experienced driver is desired. A drawback is that a human will eventually learn the manoeuvre he/she is told to do. An artificial driver is therefore to prefer to make the test repeatable. This thesis’ purpose is to develop and implement an artificial driver as a controller in order to follow a predefined trajectory. The driver model’s performance driving a double lane change manoeuvre should be as close to a real driver’s as possible. Data was gathered by inviting people to drive in a simulator. The results from the simulator tests were used to implement three different drivers with different experiences. The gathered data was used to categorize the test drivers into different driver types for each specific velocity by using the vehicle position from thetest results. This thesis studies the driver from a controller’s perspective and it resulted in two implemented controllers for reference tracking. The first approach was a Model Predictive Controller with reference tracking and the other approach was to use a FIR-filter in order to describe the drivers’ characteristics. A vehicle model was implemented in order to do the double lane change manoeuvre in a simulation environment together with the implemented driver model. The results show that the two approaches can be used for reference tracking. The MPC showed good results with the recreation of the test runs that were made by the categorized drivers. The FIR-filter had problems to mimic the drivers’ test runs and their characteristics. The advantage with MPC is its robustness, while the advantages with the FIR-filter are its, in comparison, simplicity in the implementation and the algorithm’s low computational cost. In order to make the FIR-filter more robust, some improvements have to be made. One improvement is to use gain scheduling in order to adjust the filter coefficients depending on thevelocity. / De säkerhetskraven som idag ställs på fordon är höga och det kommer bli mer strikt i framtiden. Bilföretag testar sina bilar varje dag för att se om komponenterna och bilen klarar säkerhetskraven som ställs. Till dessa tester används professionella testförare. I en vardaglig trafiksituation är det önskvärt att en normalt erfaren bilförare utför testen. En mänsklig förare kommer använda sin inlärningsförmåga vid repeterande manöver, vilket inte är önskvärt. En artificiell förare är därför att föredra. Den artificiella föraren ska köra så likt en verklig förare som möjligt vid en "double lane change"- (DLC) manöver. Detta examensarbete har som avsikt att implementera en förare som en regulator för att kunna följa en förutbestämd trajektoria på samma sätt som en verklig förare. I detta examensarbete har "DLC"-manövern studerats. I examensarbetet har insamlad data från testförare använts för att kunna implementera tre olika förartyper med olika erfarenheter. Den insamlade datan användes till att kategorisera testförarna för varje särskild hastighet. Två tillvägagångssätt har gjorts med föraren, en där föraren är en modellbaserad prediktionsregulator med referensignalsföljning (MPC) och en där föraren implementeras som ett ändligt impulssvarsfilter (FIR-filter). En fordonsmodell har implementerats för att en "DLC"-manöver ska kunna testas i en simuleringsmiljö. Resultaten blev att de två metoderna klarade av referensföljningen. MPC:n var bra på att återskapa testförararnas körningar. FIR-filtret hade problem med att härma förarnas körningar och deras karaktäristik. Fördelen med MPC är dessrobusthet och fördelen med FIR-filtret är dess, i jämförelse, simplicitet vid implementering samt den låga beräkningskostnaden för algoritmen. För att göra FIR-filtret mer robust måste förbättringar göras. En förbättring är att använda gain scheduling för att anpassa filterkoefficienterna beroende på hastigheten.

Submitted by (ana.araujo@ufrpe.br) on 2016-08-03T14:07:18Z No. of bitstreams: 1 Luiz Jose Rodrigues dos Santos.pdf: 1081987 bytes, checksum: 435fc2cb438881b9c3905e16b4b41ed0 (MD5) / Made available in DSpace on 2016-08-03T14:07:42Z (GMT). No. of bitstreams: 1 Luiz Jose Rodrigues dos Santos.pdf: 1081987 bytes, checksum: 435fc2cb438881b9c3905e16b4b41ed0 (MD5) Previous issue date: 2008-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Urban traffic represents a phenomenon of great socioeconomic importance,whose modeling from the point of view of prevision on the basis of initial conditions, still represents a challenge for modern science. Computational methods (computer simulations) represent a powerful tool for modeling and prediction of a number of effects, where systems of coupled differential equations may be used to simulate different phenomena observed in traffic systems. In particular, a quantity of high importance for maintenance and planning of road systems is the vehicular capacity which can be supported without traffic jams, whose description and prevision is still not well understood. In this work, a generalization of an existing microscopic traffic model, the Intelligent Driver Model (IDM), is proposed by implementing a distribution of desired velocities, where it is shown that vehicle capacity of multiple lane roads can be measured in a rather realistic manner, as a function of model parameters,which may be adjusted to real observations. / O tráfego urbano representa um fenômeno de grande importância sócio econômica, cuja modelagem de ponto de vista de previsão a partir de condições iniciais, ainda representa um desafio para a ciência moderna. Métodos computacionais (simulação computacional) representam uma ferramenta poderosa para modelagem e previsão de diversos efeitos, nos quais sistemas de equações diferenciais acopladas podem simular diversos fenômenos observados no sistema de tráfego. Em particular, uma grandeza de alto impacto para o gerenciamento e planejamento de rodovias é a capacidade veicular que elas podem suportar sem que aconteça o efeito de congestionamento, cuja descrição e previsão ainda não estão bem entendida. Neste trabalho, propõe-se uma generalização de um modelo microscópico computacional existente, o Intelligent Driver Model (IDM), aplicando uma distribuição de velocidades desejadas, onde torna-se possível medir de forma bastante realista a capacidade veicular de rodovias com múltiplas faixas, em função de parâmetros de modelo, que podem ser ajustados às observações reais.

Objective: Systems that can warn the driver of a possible collision with a vulnerable road user (VRU) have significant safety benefits. However, incorrect warning times can have adverse effects on the driver. If the warning is too late, drivers might not be able to react; if the warning is too early, drivers can become annoyed and might turn off the system. Currently, there are no methods to determine the right timing for a warning to achieve high effectiveness and acceptance by the driver. This study aims to validate a driver model as the basis for selecting appropriate warning times. The timing of the forward collision warnings (FCWs) selected for the current study was based on the comfort boundary (CB) model developed during a previous project, which describes the moment a driver would brake. Drivers’ acceptance toward these warnings was analyzed. The present study was conducted as part of the European research project PROSPECT (“Proactive Safety for Pedestrians and Cyclists”). Methods: Two warnings were selected: One inside the CB and one outside the CB. The scenario tested was a cyclist crossing scenario with time to arrival (TTA) of 4 s (it takes the cyclist 4 s to reach the intersection). The timing of the warning inside the CB was at a time to collision (TTC) of 2.6 s (asymptotic value of the model at TTA = 4 s) and the warning outside the CB was at TTC = 1.7 s (below the lower 95% value at TTA = 4 s). Thirty-one participants took part in the test track study (between-subjects design where warning time was the independent variable). Participants were informed that they could brake any moment after the warning was issued. After the experiment, participants completed an acceptance survey. Results: Participants reacted faster to the warning outside the CB compared to the warning inside the CB. This confirms that the CB model represents the criticality felt by the driver. Participants also rated the warning inside the CB as more disturbing, and they had a higher acceptance of the system with the warning outside the CB. The above results confirm the possibility of developing wellsaccepted warnings based on driver models. Conclusions: Similar to other studies’ results, drivers prefer warning times that compare with their driving behavior. It is important to consider that the study tested only one scenario. In addition, in this study, participants were aware of the appearance of the cyclist and the warning. A further investigation should be conducted to determine the acceptance of distracted drivers.

As the development of highways, it is quite normal for buses running in a speed around 100km/h. When buses are running in a high speed, they may suffer from the influence of side wind disturbances at anytime. Sometimes, it may result in traffic accidents. Therefore, the study of bus stability under side wind disturbances becomes more and more important. Due to restrictions of real tests, computer simulation can be used to study this subject. The bus side wind response character is reflected through the driver’s manoeuvre , so open-loop analysis is hard to give a comprehensive evaluation of the side wind stability of the bus. Therefore, closed-loop analysis is studied in this thesis. An ADAMS bus model and a side wind force model are developed in this thesis, along with two driver models, the PID control model and the preview curvature model. The driver models are built in Simulink and co-simulation between ADAMS/View and Simulink is conducted. The results of co-simulation show that the two driver models can both control the bus from deviating from the desired course under side wind disturbances. The PID control model is simple and shows a very good control effect. The maximum lateral displacement of the bus by PID control model is just 0.0205m under maximum side wind load 1000N and 2500Nm when preview time is 1.2s, while it is 0.0702m by preview curvature model, however, it is difficult to determine the coefficients Kd, Kp, and Ki in the PID controller. The preview curvature model also shows a good control effect in terms of the maximum lateral displacement and yaw angle of the bus. Comparing these two models, the PID control model is more sensitive to deviations, with quicker response and larger steering input. The bus model system is stable under side wind disturbances. Through driver ’s proper steering manoeuvre, the bus is well controlled. The closed-loop analysis is a good method to study the bus stability under side wind disturbances.

Recently, various self-driving and driving assistance systems such as Advanced Driver Assistance System (ADAS) have been developed with the intent to reduce the number of motor vehicle accidents. While self-driving systems have been proven to reduce traffic accidents, the systems sometimes make other drivers confused because of their mechanical behavior. To avoid confusion and possible error, it is necessary to construct self-driving systems that exhibit human-like behaviors. Risk Potential theory has been used to construct models that successfully represent driver behavior, especially expert behavior. This project uses Risk Potential theory to construct and evaluate a collision avoidance driver model which uses braking to avoid potential collisions with pedestrians. As a first step, a basic driver model which uses Risk Potential theory is constructed and evaluated using metrics such as collision avoidance, comfortability, and false alarm avoidance. Second, human driving data is collected to observe driver’s risk perception during interactions with a pedestrian. Finally, our proposed driver models improve on standard RP model’s performance but comparisons of the models with observed human performance reveal opportunities for further improvement.

No description available.

<p>VIRTUAL PROTOTYPING has been generally adopted in product development in order to minimise the traditional reliance on testing of physical prototypes. It thus constitutes a major step towards solving the conflict of actual increasing development cost and time due to increasing customer demands on one side, and the need to decrease development cost and time due to increasing competition on the other. Particularly challenging for the off-road equipment industry is that its products, working machines, are complex in architecture. Tightly coupled, non-linear sub-systems of different technical domains make prediction and optimisation of the complete system’s dynamic behaviour difficult.</p><p>Furthermore, in working machines the human operator is essential for the performance of the total system. Properties such as productivity, fuel efficiency, and operability are all not only dependent on inherent machine properties and working place conditions, but also on how the operator uses the machine. This is an aspect that is traditionally neglected in dynamic simulations, because the modelling needs to be extended beyond the technical system.</p><p>The research presented in this thesis focuses on wheel loaders, which are representative for working machines. The technical system and the influence of the human operator is analysed, and so-called short loading cycles are described in depth. Two approaches to rule-based simulation models of a wheel loader operator are presented and used in simulations. Both operator models control the machine model by means of engine throttle, lift and tilt lever, steering wheel, and brake only – just as a human operator does. Also, only signals that a human operator can sense are used in the models. It is demonstrated that both operator models are able to adapt to basic variations in workplace setup and machine capability. Thus, a “human element” can be introduced into dynamic simulation of working machines, giving more relevant answers with respect to operator-influenced complete-machine properties such as productivity, fuel efficiency, and operability already in the concept phase of the product development process.</p> / ISRN/Report code: LiU-Tek-Lic 2005:44

Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. The chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. The focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers.

Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. The chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. The focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers.