Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this thesis, a human-centric approach is adopted in order to provide an enriching driving experience. The thesis investigates the natural behavior of drivers when changing lanes in terms of preferences of vehicle kinematics parameters using a real-world driving dataset collected as part of the Second Strategic Highway Research Program (SHRP2). The SHRP2 Naturalistic Driving Study (NDS) set is mined for lane change events. This work develops a way to detect reliable lane changing instances from a huge NDS dataset with more than 5,400,000 data files. The lane changing instances are distinguished from noisy and erroneous data by using machine vision lane tracking system variables such as left lane marker probability and right lane marker probability. We have shown that detected lane changing instances can be validated using only vehicle kinematics data. Kinematic vehicle parameters such as vehicle speed, lateral displacement, lateral acceleration, steering wheel angle, and lane change duration are then extracted and examined from time series data to characterize these lane-changing instances for a given driver. We have shown how these vehicle kinematic parameters change and exhibit patterns during lane change maneuvers for a specific driver. The thesis shows the limitations of analyzing vehicle kinematic parameters separately and develops a novel metric, Lane Change Dynamic Score(LCDS) that shows the collective effect of these vehicle kinematic parameters. LCDS is used to classify each lane change and thereby different driving styles. / Master of Science / The current tendency of car manufacturers is to create vehicles that will offer the user the most comfortable ride possible. The user experience is given a lot of attention to ensure it is up to par. With technological advancements, we are moving closer to an era in which automobiles perform many functions autonomously. However, different drivers may react differently to highly automated driving technologies. Therefore, adapting to different driving styles is critical to increasing the acceptance of autonomous vehicle features. In this work, we examine one of the stressful maneuvers of lane changes. The analysis of various drivers' lane-changing behaviors and the value of personalization are the main subjects of this study based on actual driving scenarios. To achieve this, we have provided an algorithm to identify occurrences of lane-changing from real driving trip data files. Following that, we investigated parameters such as lane change duration, vehicle speed, displacement, acceleration, and steering wheel angle when changing lanes. We have demonstrated the patterns and changes in these vehicle kinematic characteristics that occur when a particular driver performs lane change operations. The thesis shows the limitations of analyzing vehicle kinematic parameters separately and develops a novel metric, Lane Change Dynamic Score(LCDS) that shows the collective effect of these vehicle kinematic parameters. LCDS is used to classify each lane change and thereby different driving styles.

In dieser Arbeit wird das Verhalten der Fahrer vor, während und nach dem Spurwechsel anhand eines Datensatzes untersucht. Dieser wurde im Jahr 2006 in den USA erhoben und enthält die genauen Trajektoriendaten für jedes Fahrzeug. Es konnte gezeigt werden, dass schnellere Fahrzeuge ihren Spurwechsel auch schneller abschließen. Es ist auch erkennbar, dass bei einem Wechsel nach rechts kein kleinerer Abstand zum Vorderfahrzeug in Kauf genommen wird. Eine Untersuchung der freiwilligen und notwendigen Wechsel konnte keine signifikanten Unterschiede feststellen. Im zweiten Teil der Auswertung wurden die Spurwechselentscheidungen mittels eines generellen Modells und MOBIL untersucht. Die einzusetzenden Werte wurden mit den Fahrzeugfolgemodellen OVM, Gipps-Modell und IDM erzeugt. Die Entscheidungen der Spurwechselmodelle fielen nur selten so aus, wie sie in der Realität getroffen wurden. Damit werden die Modelle ihrem eigenen Anspruch nicht gerecht, die Realität möglichst gut nachzubilden. / The topic of this master thesis is the investigation of the behaviour of the drivers before, during and after lane changes on highways. For this purpose a data set of the I-80 in the USA was used. It was collected in 2006 and contains the trajectories of all vehicles. It could be shown that faster cars even do a faster lane change. The drivers also do not accept a smaller gap to the preceding car after a lane change to the right. A comparison of voluntary and necessary lane changes did not show significant differences. In the second part of the analysis the lane change decision was examined using a general model and MOBIL. The data to be inserted were generated using the car-following models OVM, Gipps-model and IDM. But the outcomes of the lane change models only rarely matched reality. Therefore, the models did not fulfill their own standards to picture the existing reality.

Os simuladores de tráfego são programas computacionais que, através de diversos modelos, tentam simular o tráfego, o comportamento dos motoristas, o desempenho dos veículos, entre outros aspectos que envolvem uma rede viária. Estes modelos precisam ser calibrados para representar as condições de um determinado local. O objetivo da pesquisa foi propor um método de calibração de um microssimulador de tráfego através de dados coletados por estações de monitoramento. O estudo de caso foi realizado através do simulador VISSIM para um trecho do Rodoanel Mário Covas (SP-021), utilizando um algoritmo genético (AG). A calibração envolveu, além dos parâmetros comportamentais dos sub-modelos de car-following e lane-change, o ajuste das distribuições de velocidade desejada dos veículos e um método para simulação do congestionamento. A função fitness do AG foi baseada em três medidas de desempenho: uma que comparava gráficos de fluxo-velocidade simulados e observados e outras duas que comparavam a distribuição do volume de tráfego e o percentual de veículos comerciais por faixa de tráfego. Os resultados mostraram que a medida mais apropriada para a comparação dos gráficos foi a distância de Hausdorff modificada (MHD). A medida MHD também foi fundamental para garantir a ciência do método de simulação de congestionamento de tráfego proposto. O modelo calibrado foi validado usando dados de tráfego coletados em dias diferentes, pela mesma estação de monitoramento. / Traffic simulators are computer programs that, through various models, try to simulate traffic, driver behavior, vehicle performance, and other aspects involved in a road network. These models need calibration to represent local conditions satisfactorily. The objective of the research was to propose a method for the calibration of a traffic microsimulator based on traffic data collected by monitoring stations. To demonstrate the feasibility of the proposed approach, a case study was performed calibrating the simulator VISSIM for a section of Rodoanel Mario Covas (SP-021) using a genetic algorithm (GA). The calibration focused on behavioral parameters for car-following and lane-change submodels, as well as on the desired speed distributions of vehicles and on a method to simulate congestion. The GA fitness function was based on three performance measures: one that compared simulated and observed speed-flow plots, and two that compared the distribution of traffic volume and truck volumes across traffic lanes, respectively. The results showed that the most appropriate measure for comparison of the graphs was the modified Hausdor distance (MHD). MHD was also important to ensure the efficiency of the method used to simulate traffic congestion. The calibrated model was validate using traffic data collected on different days, by the same monitoring station.

Os simuladores de tráfego são programas computacionais que, através de diversos modelos, tentam simular o tráfego, o comportamento dos motoristas, o desempenho dos veículos, entre outros aspectos que envolvem uma rede viária. Estes modelos precisam ser calibrados para representar as condições de um determinado local. O objetivo da pesquisa foi propor um método de calibração de um microssimulador de tráfego através de dados coletados por estações de monitoramento. O estudo de caso foi realizado através do simulador VISSIM para um trecho do Rodoanel Mário Covas (SP-021), utilizando um algoritmo genético (AG). A calibração envolveu, além dos parâmetros comportamentais dos sub-modelos de car-following e lane-change, o ajuste das distribuições de velocidade desejada dos veículos e um método para simulação do congestionamento. A função fitness do AG foi baseada em três medidas de desempenho: uma que comparava gráficos de fluxo-velocidade simulados e observados e outras duas que comparavam a distribuição do volume de tráfego e o percentual de veículos comerciais por faixa de tráfego. Os resultados mostraram que a medida mais apropriada para a comparação dos gráficos foi a distância de Hausdorff modificada (MHD). A medida MHD também foi fundamental para garantir a ciência do método de simulação de congestionamento de tráfego proposto. O modelo calibrado foi validado usando dados de tráfego coletados em dias diferentes, pela mesma estação de monitoramento. / Traffic simulators are computer programs that, through various models, try to simulate traffic, driver behavior, vehicle performance, and other aspects involved in a road network. These models need calibration to represent local conditions satisfactorily. The objective of the research was to propose a method for the calibration of a traffic microsimulator based on traffic data collected by monitoring stations. To demonstrate the feasibility of the proposed approach, a case study was performed calibrating the simulator VISSIM for a section of Rodoanel Mario Covas (SP-021) using a genetic algorithm (GA). The calibration focused on behavioral parameters for car-following and lane-change submodels, as well as on the desired speed distributions of vehicles and on a method to simulate congestion. The GA fitness function was based on three performance measures: one that compared simulated and observed speed-flow plots, and two that compared the distribution of traffic volume and truck volumes across traffic lanes, respectively. The results showed that the most appropriate measure for comparison of the graphs was the modified Hausdor distance (MHD). MHD was also important to ensure the efficiency of the method used to simulate traffic congestion. The calibrated model was validate using traffic data collected on different days, by the same monitoring station.

Interstate highways are one of the most important components of the transportation infrastructure in America. Freeway ramps play an important role in the whole interstate transportation system. This paper researches the traffic flow characteristics of four typical exit ramps in USA, which are tapered one-lane exit, tapered two-lane exit, parallel one-lane exit and parallel two-lane exit. Computer simulation software, such as CORSIM and HCS are applied as the main tools in this research. ANOVA and Tukey are used for statistical purpose. It compares the maximum capacity, average running speed and the total lane change number of those four exit ramps. It is found that no matter in terms of traffic discharging rate or total lane charging number; the tapered two-lane exit has the best operational performance. Tapered one-lane exit ramp has the least capacity. Parallel one-lane exit and parallel two-lane exit have very limited traffic operational difference in terms of capacity and running speed. It is recommended that parallel two-lane exit ramp should not be designed along the freeway if the right of way along arterial road is enough. It is observed from the simulation data that the grade of freeway, truck percentage, restricted to the truck use of certain lane(s) and the location of exit sign have significant impact on the running speed and total lane change number. An uphill can decrease the running speed dramatically while more truck brings more lane change, causing safety concerns. It is found that when trucks are restricted to the right two most lane, there will be less lane change number comparing with trucks are not restricted. Location of exit sign operates well at the distance between 4000 ft to 5000 ft. does have a significant impact on the operational speed and total lane change number before, within or after functional area of an exit, based on the data analysis of simulation runs.

The goal of this thesis is to implement the control and design of an intelligent vehicle based on an embedded DSP platform (eZdspTM F2812). The overall system including steering wheel AC serve motor, brake actuator, throttle driving circuit and the sensors is equipped in a golf car as a platform. Otherwise, digital image processing technology is used to realize the autonomous driving system which can achieve multi-mode of lane-keeping, lane-change and obstacle-avoidance. In the lane-keeping control, the road information can be provided by the vision system. According to the offset and displacement of angle as input signal, a fuzzy controller is used to compute the desired steering wheel angle and let the golf car can cross road safely. In lane-change, a smooth trajectory can be generated by IMU, IMU is used to collect the information data of yaw rate and yaw angle when human-driving. That makes autonomous driving system become more humanlike and to achieve an open-loop lane-change maneuver. In obstacle-avoidance, we use a laser range scanner to detect the distance of a front obstacle. When the distance is lower than safety distance, double lane-change will be activated to avoid the front obstacle. The overall system has been examined on NSYSU campus roads.

Balloon Cars (Soft Cars) used for active-system testing are presently statically following one specific path. Autonomous GPS driven balloon cars can be extremely useful if made to be accurate.Volvo group’s long term plan involves usage of such cars to improve active-safety systems. Thisreport presents comprehensive details about the development of the control system of the soft-car.Software development was preceded by purchase of parts. Detailed descriptions of the ballooncar hardware components are presented. Various hardware components were interconnected toform a CAN Bus network. This thesis work describes CAN networks in general and with referenceto the developed Linux based software system.The navigation system is presented in the thesis report using a ‘bottom up’ approach. First theLow-level functions and variables are described that directly control the hardware component.They are called by high level functions that are subsequently explained. The high level functionsinclude accurate turning and an automated lane change process.The high level functions may be sequentially called and to accurately follow a specific path. Various lines and points may be used in a user defined Cartesian coordinate system. Details about theperformance of various high level functions as well as of a demonstration of a pattern are presented along with the limitations of the overall system.

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.

Lane change or "Side" Crash Avoidance Systems (SCAS) technologies are becoming available to help alleviate the lane change crash problem. They detect lane change crash hazards and warn the driver of the presence of such hazards. This thesis examines driver lane change behavior and evaluates the potential effectiveness of five warning onset rules for lane change or "side" crash avoidance system (SCAS) technologies. The ideal SCAS should warn the driver only when two conditions are met: (1) positive indication of lane change intent and (2) positive detection of a proximal vehicle in the adjacent lane of concern. Together, these two conditions create a crash hazard. The development of SCAS technologies depends largely on an understanding of driver behavior and performance during lane change maneuvers. By quantifying lane change behavior, real world crash hazard scenarios can be simulated. This provides an opportunity to evaluate potential warning onset rules or algorithms of driver intent to change lanes. Five warning onset rules for SCAS were evaluated: turn-signal onset (TSO), minimum separation (MS), line crossing (LC), time-to-line crossing (TLC), and tolerance limit (TL). The effectiveness of each rule was measured by the maximum response time available (tavailable) to avoid a crash for a particular lane change crash scenario, and by the crash outcome, crashed or crash avoided, of a particular lane change crash scenario. / Master of Science

In dieser Arbeit wird das Verhalten der Fahrer vor, während und nach dem Spurwechsel anhand eines Datensatzes untersucht. Dieser wurde im Jahr 2006 in den USA erhoben und enthält die genauen Trajektoriendaten für jedes Fahrzeug. Es konnte gezeigt werden, dass schnellere Fahrzeuge ihren Spurwechsel auch schneller abschließen. Es ist auch erkennbar, dass bei einem Wechsel nach rechts kein kleinerer Abstand zum Vorderfahrzeug in Kauf genommen wird. Eine Untersuchung der freiwilligen und notwendigen Wechsel konnte keine signifikanten Unterschiede feststellen. Im zweiten Teil der Auswertung wurden die Spurwechselentscheidungen mittels eines generellen Modells und MOBIL untersucht. Die einzusetzenden Werte wurden mit den Fahrzeugfolgemodellen OVM, Gipps-Modell und IDM erzeugt. Die Entscheidungen der Spurwechselmodelle fielen nur selten so aus, wie sie in der Realität getroffen wurden. Damit werden die Modelle ihrem eigenen Anspruch nicht gerecht, die Realität möglichst gut nachzubilden.:1 Einleitung 1 2 Theoretische Grundlagen 3 2.1 Begriffserklärungen 3 2.2 Fahrstreifenwechsel 6 2.2.1 Formen von Spurwechseln 6 2.2.2 Ebenen von Entscheidungen 7 2.3 Verkehrsmodelle 8 2.3.1 Mathematische Grundlagen 9 2.3.2 Fahrzeugfolgemodelle 9 2.3.3 Simulation des Fahrstreifenwechsels 12 3 Aufbereitung des Datensatzes 15 3.1 Untersuchungsgebiet 15 3.2 Datensatz 16 3.3 Datenaufbereitung 18 3.3.1 Bestimmung der lokalen Geschwindigkeit 18 3.3.2 Bestimmung der lokalen Beschleunigung 21 3.3.3 Bestimmung der Abstände und Zeitlücken 22 3.4 Bekannte Fehler im Datensatz 23 3.5 Implementierung und Kalibrierung der Modelle 28 4 Auswertung des Datensatzes 31 4.1 Ermittlung wichtiger Kenngrößen 31 4.2 Deskriptive Beschreibung von Fahrstreifenwechseln 33 4.2.1 Freiwillige Spurwechsel 33 4.2.2 Notwendige Spurwechsel 37 4.3 Modellbasierte Auswertung 39 4.3.1 Kalibrierung und Validierung 39 4.3.2 Untersuchung der Spurwechselentscheidung 41 4.3.3 Untersuchung der Spurwechselentscheidung mit MOBIL 43 5 Zusammenfassung und Ausblick 47 5.1 Zusammenfassung und Überprüfung der Hypothesen 47 5.2 Weitere Forschungsmöglichkeiten 50 / The topic of this master thesis is the investigation of the behaviour of the drivers before, during and after lane changes on highways. For this purpose a data set of the I-80 in the USA was used. It was collected in 2006 and contains the trajectories of all vehicles. It could be shown that faster cars even do a faster lane change. The drivers also do not accept a smaller gap to the preceding car after a lane change to the right. A comparison of voluntary and necessary lane changes did not show significant differences. In the second part of the analysis the lane change decision was examined using a general model and MOBIL. The data to be inserted were generated using the car-following models OVM, Gipps-model and IDM. But the outcomes of the lane change models only rarely matched reality. Therefore, the models did not fulfill their own standards to picture the existing reality.:1 Einleitung 1 2 Theoretische Grundlagen 3 2.1 Begriffserklärungen 3 2.2 Fahrstreifenwechsel 6 2.2.1 Formen von Spurwechseln 6 2.2.2 Ebenen von Entscheidungen 7 2.3 Verkehrsmodelle 8 2.3.1 Mathematische Grundlagen 9 2.3.2 Fahrzeugfolgemodelle 9 2.3.3 Simulation des Fahrstreifenwechsels 12 3 Aufbereitung des Datensatzes 15 3.1 Untersuchungsgebiet 15 3.2 Datensatz 16 3.3 Datenaufbereitung 18 3.3.1 Bestimmung der lokalen Geschwindigkeit 18 3.3.2 Bestimmung der lokalen Beschleunigung 21 3.3.3 Bestimmung der Abstände und Zeitlücken 22 3.4 Bekannte Fehler im Datensatz 23 3.5 Implementierung und Kalibrierung der Modelle 28 4 Auswertung des Datensatzes 31 4.1 Ermittlung wichtiger Kenngrößen 31 4.2 Deskriptive Beschreibung von Fahrstreifenwechseln 33 4.2.1 Freiwillige Spurwechsel 33 4.2.2 Notwendige Spurwechsel 37 4.3 Modellbasierte Auswertung 39 4.3.1 Kalibrierung und Validierung 39 4.3.2 Untersuchung der Spurwechselentscheidung 41 4.3.3 Untersuchung der Spurwechselentscheidung mit MOBIL 43 5 Zusammenfassung und Ausblick 47 5.1 Zusammenfassung und Überprüfung der Hypothesen 47 5.2 Weitere Forschungsmöglichkeiten 50