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Almén, Marcus. "Driver Model for Mission-Based Driving Cycles." Thesis, Linköpings universitet, Fordonssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140158.
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When further demands are placed on emissions and performance of cars, trucks and busses, the vehicle manufacturers are looking to have cheap ways to evaluate their products for specific customers' needs. Using simulation tools to quickly compare use cases instead of manually recording data is a possible way forward. However, existing traffic simulation tools do not provide enough detail in each vehicle for the driving to represent real life driving patterns with regards to road features. For the purpose of this thesis data has been recorded by having different people drive a specific route featuring highway driving, traffic lights and many curves. Using this data, models have then been estimated that describe how human drivers adjust their speed through curves, how long braking distances typically are with respect to the driving speed, and the varying deceleration during braking sequences. An additional model has also been created that produces a speed variation when driving on highways. In the end all models are implemented in Matlab using a traffic control interface to interact with the traffic simulation tool SUMO. The results of this work are promising with the improved simulation being able to replicate the most significant characteristics seen from human drivers when approaching curves, traffic lights and intersections.
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Guillen, Pablo Puente, and Irene Gohl. "Forward collision warning based on a driver model to increase drivers’ acceptance." Taylor & Francis, 2019. https://publish.fid-move.qucosa.de/id/qucosa%3A72239.
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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.
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Ehsani, Saéd M. "A driver model with supervision aspects." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0007/NQ42821.pdf.
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SANTOS, Luiz José Rodrigues dos. "Generalização do modelo computacional de tráfego veicular IDM (Intelligent Driver Model)." Universidade Federal Rural de Pernambuco, 2008. http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5172.
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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.
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Qiu, Jie. "Study of driver models forside wind disturbances." Thesis, KTH, Fordonsdynamik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157504.
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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.
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Jansson, Andreas, and Erik Olsson. "Development of a Driver Model for Vehicle Testing." Thesis, Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-102048.
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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.
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Hoult, W. "A neuromuscular model for simulating driver steering torque." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604261.
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A linear neuromuscular model was developed and incorporated within a driver/vehicle model. Optimal control was used to minimise metabolic energy and path-following error. Simultaneous feed-forward and feedback operation was observed, with the stretch reflex loop acting to reject disturbances. A trade-off between minimising the feedback error signal and energy consumption exists that has not been previously identified. A non-linear, Huxley/Zahalak-based model of an agonist/antagonist muscle pair connected to a second order load was implemented (the ‘MDM’ model). Mechanistic and energy consumption predictions compare favourably with published data. The model was linearized, to allow incorporation within a linear neuromuscular framework. A suitable model structure was fitted using parametric methods. A novel, linear, energy consumption model was proposed. A parameter study of the MDM model was carried out. Variable natural length behaviour was observed, consistent with real muscle operation. Findings suggested that the stretch reflex gain is not large enough to account for low frequency behaviour observed by some researchers for ‘stochastic disturbance’ type experiments. An optimal controller representing cognitive influence was shown to account for this behaviour. A Box-Jenkins method for identifying intrinsic and reflex dynamics models (on the basis of reflex delay) was developed and validated. The impact of the stretch reflex gain and noise levels on identification success was investigated. Intrinsic and reflex models were identified from eight test subjects’ data. The closed-loop neuromuscular model agreed well with measured data, and was generally consistent with MDM model predictions. Low frequency control action and changes in stretch reflex dynamics were observed, stemming from cognitive influence. Other researchers have failed to account for this.
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Kappattanavar, Abhishek Mallikarjuna. "Model Transformation in context of Driver Assistance System." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-203859.
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In today’s world we see that Embedded Systems forms a major part in the life of a human being. Almost every device today has an electronic chip embedded in it. When it comes to automotive, these electronic devices are multiplying. This has resulted in innovative methods of developing Embedded Systems. Among them, Model Based Development has become very popular and a standard way of developing embedded systems. Now, we can see that most embedded systems, especially the automotive systems, are being developed using Model development tools like Simulink. In the design and development of Driver Assistance System, Model Based Design (MBD) plays an important role from system design and simulation to code generation. Modeling tool Matlab/Simulink is now among the most popular tools. Due to the proprietary nature of Simulink and challenges in requirement elicitation phase the industry is looking towards an open source alternative, such as Scicos. Since, most of the OEMs are still using Simulink, there is a need for interoperability between Simulink and Scicos. The present work proposes metamodels for Simulink and Scicos, and Model transformation using these Metamodels for the inter-operability.
In order to develop the model transformation the metamodels for Simulink and Scicos were developed using EMF Ecore. These metamodels conform to OMGs MOF Standards. These metamodels were used in developing the transformation definition using the language QVTo. First a simple model was developed, and transformation rules were applied and verified using it. Then a Simulink subsystem of a cross wind assistance system was subjected to forward transformation. The outputs of the model before transformation and that after transformation were compared. They were found to give the same output as desired. Thus, verifying the transformation definition. An attempt was made to achieve reverse transformation. A subsystem in Scicos was considered for reverse transformation. After subjecting it to transformation, an intermediate model conforming to Simulink metamodel was obtained. This shows that the interoperability between Scicos and Simulink can be achieved.
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Haupt, Juliane. "Be motivated to pay attention! How driver assistance system use experience influences driver motivation to be attentive." Doctoral thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-206704.
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This work provides an in-depth-view of driver motivational aspects when driver assistance Systems (DAS) are considered. Thereby, the role of driver actual experience with DAS use was also identified and highlighted. A central outcome of this thesis is the STADIUM model describing the interplay of motivational factors that determine the engagement in secondary activities while taking actual DAS use experience into account. The role of motives in showing attentive behaviour depending on DAS (the navigation system) could also be underlined. The relevance, enrichment and need of combining qualitative and quantitative approaches when the effects of safety countermeasures on driver behaviour are investigated could also be shown. The results are discussed in terms of hierarchical driver behaviour models, the theory of planned behaviour and its extended versions and the strengths of the introduced studies and limitations. Implications for traffic safety are provided and future research issues are recommendedDiese Arbeit liefert einen gründlichen Einblick, welche Rolle motivationale Aspekte spielen, wenn Fahrerassistenzsysteme (FAS) genutzt werden. Dabei wurde auch die Funktion der tatsächlichen Erfahrung mit FAS identifiziert und hervorgehoben. Ein zentrales Ergebnis dieser Arbeit ist das STADIUM Modell, welches das Zusammenspiel motivationaler Faktoren in Abhängigkeit von der tatsächlichen Erfahrung mit FAS erklärt, die wiederum bestimmen, inwieweit und ob andere Aktivitäten während des Fahrens ausgeführt werden. Außerdem konnte unterstrichen werden, welche Rolle Motive spielen, aufmerksames Verhalten in Abhängigkeit von der Nutzung von FAS (dem Navigationssystem) zu zeigen. Zusätzlich konnte dargestellt werden, wie relevant, bereichernd und nützlich es ist, qualitative und quantitative Methoden zu kombinieren, wenn die Effekte von FAS auf das FahrerInnenverhalten untersucht werden. Die Ergebnisse werden diskutiert indem auf hierarchische Fahrerverhaltensmodelle, auf die Theorie des geplanten Verhaltens und ihre erweiterten Versionen und auf die Stärken und Schwächen der Studien Bezug genommen wird. Es werden Implikationen dargestellt und zukünftige Forschungsfragen und Problemstellungen empfohlen
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Miyajima, Chiyomi, Yoshihiro Nishiwaki, Koji Ozawa, Toshihiro Wakita, Katsunobu Itou, Kazuya Takeda, and Fumitada Itakura. "Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification." IEEE, 2007. http://hdl.handle.net/2237/9623.
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Keen, Steven Dale. "Modeling driver steering behaviour using multiple-model predictive control." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611428.
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Zheng, Pengjun. "A microscopic simulation model of merging operation at motorway on ramps." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289589.
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Zheng, Yue. "Driver model for a software in the loop simulation tool." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-265668.
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For this project, a Software-In-the-Loop (SIL) simulation tool is used at Scania (“VTAB” – Virtual Truck and Bus), which simulates the submodels of the mechanical vehicle components together with the real control units. The simulation tool contains the following submodels: Engine model, Drivetrain model, Drive cycle model, Restbus model, and Driver model. The simulated human driver submodel in the restbus model outputs two pedal control signals to the control unit, namely the gas and brake pedals. With these two pedal signals, the control unit decides the modes of mechanical vehicle components. This driver model needs to be reworked to obtain a better velocity following performance. Two controllers, fuzzy PI anti-windup and backward calculation, are implemented in the driver model and compared by the velocity tracking accuracy and the pedal switching frequency. In the comparison and analysis section, two different cycles and two weights of payload are simulated. The simulation results demonstrate that both controllers can improve the driver model’s velocity tracing accuracy. Further, the fuzzy PI anti-windup controller is better when considering pedal signals fluctuation frequency and implementation complexity.För detta projekt används ett simuleringsverktyg Software-In-the-Loop (SIL) på Scania (“VTAB” - Virtual Truck and Bus), vilket simulerar submodellerna för de mekaniska fordonskomponenterna tillsammans med de verkliga styrenheterna. Simuleringsverktyget innehåller följande submodeller: Motormodell, Drivmotormodell, Drivcykelmodell, Restbusmodell och Drivermodell. Den simulerade submodellen för mänsklig förare i restbussmodellen kommer att sända två pedalsstyrsignaler till styrenheten, nämligen gas och broms. Med dessa två pedalsignaler kan styrenheten avgöra lägen av mekaniska fordonskomponenter. Denna drivrutinmodell måste omarbetas för att få en bättre hastighetsspårnings presentationsförmåga. Två styrenheter, fuzzy PI anti-windup och bakåtberäkning, implementeras i förarmodell och jämförs respektive med hastighetsspårningsnoggrannhet och pedalväxelfrekvens. I jämförelseoch analysavsnittet simuleras två olika cyklar och två nyttolast. Simuleringsresultaten visar att båda kontrollerna kan förbättra förarmodellens hastighetsspårningskapacitet. Vidare är fuzzy PI-anti-windup-kontroller bättre när man tar hänsyn till pedalsignalernas fluktueringsfrekvens och implementeringskomplexitet
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D'Angio, Paul Christopher. "Adaptive and Passive Non-Visual Driver Assistance Technologies for the Blind Driver Challenge®." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27582.
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This work proposes a series of driver assistance technologies that enable blind persons to safely and independently operate an automobile on standard public roads. Such technology could additionally benefit sighted drivers by augmenting vision with suggestive cues during normal and low-visibility driving conditions. This work presents a non-visual human-computer interface system with passive and adaptive controlling software to realize this type of driver assistance technology. The research and development behind this work was made possible through the Blind Driver Challenge® initiative taken by the National Federation of the Blind.
The instructional technologies proposed in this work enable blind drivers to operate an automobile through the provision of steering wheel angle and speed cues to the driver in a non-visual method. This paradigm imposes four principal functionality requirements: Perception, Motion Planning, Reference Transformations, and Communication. The Reference Transformation and Communication requirements are the focus of this work and convert motion planning trajectories into a series of non-visual stimuli that can be communicated to the human driver.
This work proposes two separate algorithms to perform the necessary reference transformations described above. The first algorithm, called the Passive Non-Visual Interface Driver, converts the planned trajectory data into a form that can be understood and reliably interacted with by the blind driver. This passive algorithm performs the transformations through a method that is independent of the driver. The second algorithm, called the Adaptive Non-Visual Interface Driver, performs similar trajectory data conversions through methods that adapt to each particular driver. This algorithm uses Model Predictive Control supplemented with Artificial Neural Network driver models to generate non-visual stimuli that are predicted to induce optimal performance from the driver. The driver models are trained online and in real-time with a rapid training approach to continually adapt to changes in the driver's dynamics over time.
The communication of calculated non-visual stimuli is subsequently performed through a Non-Visual Interface System proposed by this work. This system is comprised of two non-visual human computer interfaces that communicate driving information through haptic stimuli. The DriveGrip interface is pair of vibro-tactile gloves that communicate steering information through the driverâ s hands and fingers. The SpeedStrip interface is a vibro-tactile cushion fitted on the driverâ s seat that communicates speed information through the driver's legs and back. The two interfaces work simultaneously to provide a continuous stream of directions to the driver as he or she navigates the vehicle.Ph. D.
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Ahmed, Umair. "Racing Driver Model in Dymola Vehicle Dynamics Library (VDL) : Steering Controller Design." Thesis, Karlstads universitet, Avdelningen för fysik och elektroteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-11858.
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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
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Wilkerson, Jaxon. "Handoff of Advanced Driver Assistance Systems (ADAS) using a Driver-in-the-Loop Simulator and Model Predictive Control (MPC)." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595262540712316.
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Kondyli, Alexandra. "Breakdown probability model at freeway-ramp merges based on driver behavior." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024857.
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Higgs, Bryan James. "Emotional Impacts on Driver Behavior: An Emo-Psychophysical Car-Following Model." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64901.
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This research effort aims to create a new car-following model that accounts for the effects of emotion on driver behavior. This research effort is divided into eight research milestones: (1) the development of a segmentation and clustering algorithm to perform new investigations into driver behavior; (2) the finding that driver behavior is different between drivers, between car-following periods, and within a car-following period; (3) the finding that there are patterns in the distribution of driving behaviors; (4) the finding that driving states can result in different driving actions and that the same driving action can be the result of multiple driving states; (5) the finding that the performance of car-following models can be improved by calibration to state-action clusters; (6) the development of a psychophysiological driving simulator study; (7) the finding that the distribution of driving behavior is affected by emotional states; and (8) the development of a car-following model that incorporates the influence of emotions.Ph. D.
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Turley, Carole. "Calibration Procedure for a Microscopic Traffic Simulation Model." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1747.pdf.
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Tuladhar, Looja R. "Resonant Power MOSFET Driver for LED Lighting." Youngstown State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1264709029.
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Amata, Hideomi, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, and Kazuya Takeda. "Prediction model of driving behavior based on traffic conditions and driver types." IEEE, 2009. http://hdl.handle.net/2237/13899.
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Bauer, Colin [Verfasser]. "A driver specific maneuver prediction model based on fuzzy logic / Colin Bauer." Berlin : Freie Universität Berlin, 2012. http://d-nb.info/1026884047/34.
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Abtahi, Shabnam. "Driver Drowsiness Monitoring Based on Yawning Detection." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23295.
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Driving while drowsy is a major cause behind road accidents, and exposes the driver to a much higher crash risk compared to driving while alert. Therefore, the use of assistive systems that monitor a driver’s level of vigilance and alert the fatigue driver can be significant in the prevention of accidents. This thesis introduces three different methods towards the detection of drivers’ drowsiness based on yawning measurement. All three approaches involve several steps, including the real time detection of the driver’s face, mouth and yawning. The last approach, which is the most accurate, is based on the Viola-Jones theory for face and mouth detection and the back projection theory for measuring both the rate and the amount of changes in the mouth for yawning detection. Test results demonstrate that the proposed system can efficiently measure the aforementioned parameters and detect the yawning state as a sign of a driver’s drowsiness.
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Kuwabara, Kristina Marie. "Design and Development of a Virtual Driver Model and a Hybrid Supervisory Controller." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595368947251449.
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Braghieri, Giovanni. "Application of robust nonlinear model predictive control to simulating the control behaviour of a racing driver." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/275524.
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The work undertaken in this research aims to develop a mathematical model which can replicate the behaviour of a racing driver controlling a vehicle at its handling limit. Most of the models proposed in the literature assume a perfect driver. A formulation taking human limitations into account would serve as a design and simulation tool for the automotive sector. A nonlinear vehicle model with five degrees of freedom under the action of external disturbances controlled by a Linear Quadratic Regulator (LQR) is first proposed to assess the validity of state variances as stability metrics. Comparison to existing stability and controllability criteria indicates that this novel metric can provide meaningful insights into vehicle performance. The LQR however, fails to stabilise the vehicle as tyres saturate. The formulation is extended to improve its robustness. Full nonlinear optimisation with direct transcription is used to derive a controller that can stabilise a vehicle at the handling limit under the action of disturbances. The careful choice of discretisation method and track description allow for reduced computing times. The performance of the controller is assessed using two vehicle configurations, Understeered and Oversteered, in scenarios characterised by increasing levels of non- linearity and geometrical complexity. All tests confirm that vehicles can be stabilised at the handling limit. Parameter studies are also carried out to reveal key aspects of the driving strategy. The driver model is validated against Driver In The Loop simulations for simple and complex manoeuvres. The analysis of experimental data led to the proposal of a novel driving strategy. Driver randomness is modelled as an external disturbance in the driver Neuromuscular System. The statistics of states and controls are found to be in good agreement. The prediction capabilities of the controller can be considered satisfactory.
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Özbay, Kaan. "A dynamic traffic simulation/assignment model in the context of Advanced Driver Information Systems /." This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-10222009-125053/.
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Gebretsadik, Rahel Hadgu. "Statistical Analysis of Driver Behaviour and Eco-Driving model based on CAN bus Data." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-28091.
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The objective of this thesis is to analyse driving behaviour and to characterize the effectsof an efficient way of driving, termed eco-driving, that enables the driver to reduce fuelconsumption and CO2emissions.The approach used to assess driving style is a collection of data from a CAN bus of acar equipped with OBD-II (on-board diagnostic) system. The driving experiment wasperformed for nine drivers who drove in a normal way or regular driving style and onedriver was an eco-driver who drove in an economical driving style. The driving routewas approximately 18.7 kms (which took between 25 to 30 minutes) in Halmstad city,Sweden.The drivers are compared using a statistical analysis of the driving parameters such as,speed, accelerator (gas pedal) and brake pressure, which are obtained from CAN busdata. A hierarchical clustering algorithm also used to classify the drivers based on theaverage result of the signals.In the results, a driving difference between the eco-driver and the normal drivers is visi-ble, most of the normal drivers have more or less similar behaviour. The average speed ofthe eco-driver lower than the normal drivers and the accelerator (gas pedal) result is alsoshown less usage by the eco-driver than the normal drivers. On the other hand, the eco-driver has braked more often than the normal drivers, but gently. Nevertheless, differenttraffic conditions during the experiment obstructs comparisons between the drivers.
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Ozbay, Kaan. "A dynamic traffic simulation/assignment model in the context of Advanced Driver Information Systems." Thesis, Virginia Tech, 1991. http://hdl.handle.net/10919/45254.
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Growing congestion problems of many metropolitan areas which cause excessive traffic delay, instability of travel time generated the need for the development of an Intelligent Vehicle Highway System (IVHS) program that is capable of making significant improvements in mobility, highway safety, and productivity on highways and urban streets. The success of such real time control system highly depends on the new methods that address dynamic traffic assignment. Thus there is an urgent need for an effective dynamic assignment model.
The main objective of this research is to emphasize the importance of dynamic traffic assignment for Advanced Driver Information Systems (ADIS) which is one of the major components of IVHS and to present a practical traffic assignment model that is capable of running in real time and which can accurately predict link travel times, queue build up, and network performance. DYNTRAS (DYNamic Traffic Simulation Assignment), a simulation /assignment model is developed. The model uses an incremental loop that assigns a portion of the Origin-Destination matrix, and simulates the movement of the vehicles. Then, it updates travel times and assigns an additional portion of the O-D matrix. In contrast to traditional traffic assignment models like "capacity restraint" and “incremental assignment" techniques that do not consider time dimension, DYNTRAS incorporates time as a third dimension by keeping track of the vehicle movements in time. As a result, it is capable of predicting time-dynamic impacts of congestion and effects of diverted traffic on traffic flow more realistically.
The model is applied to a test network. “Several experimental factors are varied to test the sensitivity of the model. The results obtained are presented and general conclusions are derived. The differences between dynamic and static traffic assignment results are also discussed by considering results obtained from both methods.
The model needs to be calibrated using real traffic data. According to the results obtained, it needs to be validated. In addition, its long computation time should be reduced to be able to use it for real time applications.Master of Science
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Tchankue-Sielinou, Patrick. "A model for mobile, context-aware in-car communication systems to reduce driver distractions." Thesis, Nelson Mandela Metropolitan University, 2015. http://hdl.handle.net/10948/4144.
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Driver distraction remains a matter of concern throughout the world as the number of car accidents caused by distracted driving is still unacceptably high. Industry and academia are working intensively to design new techniques that will address all types of driver distraction including visual, manual, auditory and cognitive distraction. This research focuses on an existing technology, namely in-car communication systems (ICCS). ICCS allow drivers to interact with their mobile phones without touching or looking at them. Previous research suggests that ICCS have reduced visual and manual distraction. Two problems were identified in this research: existing ICCS are still expensive and only available in limited models of car. As a result of that, only a small number of drivers can obtain a car equipped with an ICCS, especially in developing countries. The second problem is that existing ICCS are not aware of the driving context, which plays a role in distracting drivers. This research project was based on the following thesis statement: A mobile, context-aware model can be designed to reduce driver distraction caused by the use of ICCS. A mobile ICCS is portable and can be used in any car, addressing the first problem. Context-awareness will be used to detect possible situations that contribute to distracting drivers and the interaction with the mobile ICCS will be adapted so as to avert calls and text messages. This will address the second problem. As the driving context is dynamic, drivers may have to deal with critical safety-related tasks while they are using an existing ICCS. The following steps were taken in order to validate the thesis statement. An investigation was conducted into the causes and consequences of driver distraction. A review of literature was conducted on context-aware techniques that could potentially be used. The design of a model was proposed, called the Multimodal Interface for Mobile Info-communication with Context (MIMIC) and a preliminary usability evaluation was conducted in order to assess the feasibility of a speech-based, mobile ICCS. Despite some problems with the speech recognition, the results were satisfying and showed that the proposed model for mobile ICCS was feasible. Experiments were conducted in order to collect data to perform supervised learning to determine the driving context. The aim was to select the most effective machine learning techniques to determine the driving context. Decision tree and instance-based algorithms were found to be the best performing algorithms. Variables such as speed, acceleration and linear acceleration were found to be the most important variables according to an analysis of the decision tree. The initial MIMIC model was updated to include several adaptation effects and the resulting model was implemented as a prototype mobile application, called MIMIC-Prototype.
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Yekhshatyan, Lora. "Detecting distraction and degraded driver performance with visual behavior metrics." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/910.
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Driver distraction contributes to approximately 43% of motor-vehicle crashes and 27% of near-crashes. Rapidly developing in-vehicle technology and electronic devices place additional demands on drivers, which might lead to distraction and diminished capacity to perform driving tasks. This situation threatens safe driving. Technology that can detect and mitigate distraction by alerting drivers could play a central role in maintaining safety. Correctly identifying driver distraction in real time is a critical challenge in developing distraction mitigation systems, and this function has not been well developed. Moreover, the greatest benefit may be from real-time distraction detection in advance of dangerous breakdowns in driver performance.
Based on driver performance, two types of distraction - visual and cognitive - are identified. These types of distraction have very different effects on visual behavior and driving performance; therefore, they require different algorithms for detection. Distraction detection algorithms typically rely on either eye measures or driver performance measures because the effect of distraction on the coordination of measures has not been established. Combining both eye glance and vehicle data could enhance the ability of algorithms to detect and differentiate visual and cognitive distraction.
The goal of this research is to examine whether poor coordination between visual behavior and vehicle control can identify diminished attention to driving in advance of breakdowns in lane keeping. The primary hypothesis of this dissertation is that detection of changes in eye-steering relationship caused by distraction could provide a prospective indication of vehicle state changes. Three specific aims are pursued to test this hypothesis. The first aim examines the effect of distracting activity on eye and steering movements to assess the degree to which the correlation parameters are indicative of distraction. The second aim applies a control-theoretic system identification approach to the eye movement and steering data to distinguish between distracted and non-distracted conditions. The third aim examines whether changes of eye-steering coordination associated with distraction provide a prospective indication of breakdowns in driver performance, i.e., lane departures.
Together, the three aims show how that a combination of visual and steering behavior, i.e., eye-steering model, can differentiate between non-distracted and distracted state. This model revealed sensitivity to distraction associated with off-road glances. The models derived for different drivers have similar structure and fit to data from other drivers reasonably well. In addition, the differences in model order and model coefficients indicate the variability in driving behavior: some people generate more complex behavior than others. As was expected, eye-steering correlation on straight roads is not as strong as observed on curvy roads. However, eye-steering correlation measured through correlation coefficient and time delay between two movements is sensitive to different types of distraction. Time delay mediates changes in lane position and the eye-steering system predicts breakdowns in lane keeping. This dissertation contributes to developing a distraction detection system that integrates visual and steering behavior. More broadly, these results suggest that integrating eye and steering data can be helpful in detecting and mitigating impairments beyond distraction, such as those associated with alcohol, fatigue, and aging.
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Li, Shi. "Hyper-heuristic cooperation based approach for bus driver scheduling." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2013. http://tel.archives-ouvertes.fr/tel-00976554.
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The design of public transport system must take into account different dimensions to solve two main problems of optimization: the vehicles scheduling and driver scheduling. In our work, we focused on bus driver scheduling. Its objective is to minimize the number of drivers in accordance with social and environmental constraints. By its combinatorial nature, bus driver scheduling is considered a complex task in the design process of network transport. We have proposed an approach based on hyper-heuristics whose main advantage lies in their ability to adapt to different problems. We are particularly interested in a cooperative approach, which is able to take into account changes in the resolution process. We have extended the functionality and improved performance of the traditional framework of hyper- heuristics by proposing a pattern based on an organizational model. The proposed algorithm consists of a combination of several phases and several levels. The metaphor of the coalition is used to make cooperate several hyper-heuristics. The coalition is intended to favor diversified solutions and expand search capacity with decentralized control where each hyper-heuristic has certain autonomy. It is thus possible to consider different ways of cooperation between the hyper-heuristics: sharing solutions, learning by mimetism or carrying out different competitive search strategies. The experiment was carried out both on real-world instances and benchmarks. It gave good results on both quality of solution and execution time
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Yan, Fei [Verfasser]. "Developing a model-based lane change decision aid system by integrating driver uncertainty / Fei Yan." Ulm : Universität Ulm, 2018. http://d-nb.info/1174251867/34.
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Mauk, Jake W. "Eye Tracker Analysis of Driver Visual Focus Areas at Simulated Intersections." Youngstown State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1607590119438536.
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Smith, Porsha L. "Protein Arginine Methyltransferase 5 as a Driver of Lymphomagenesis." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468975682.
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Darby, Phillip. "The assessment of driver and manager training in the context of work-related road safety interventions." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/20900.
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Vehicles being driven for work purposes represent a large proportion of road collision and deaths in the workplace. These observations mean that people driving for work can impose a large burden on organisations and on society. In addition, previous studies identified a fleet driver effect for which there was greater collision risk for those who drive for work compared to the general driving population, even after controlling for exposure. This accentuates the need for both organisational and government policy makers to take steps to reduce the impact of these collisions. No single intervention has been found to solve issues around work-related road safety therefore a range of initiatives have been directed towards the risks associated with drivers, vehicles, journeys and organisations. Many of the interventions, however, lack robust evidence to support their use. The aim of this thesis is to assess organisational interventions to improve work-related road safety by using econometric models on real-world data. The data represents driving claims made between 2005 and 2012 by employees of a large UK company, with a fleet of approximately 35,000 vehicles. The drivers were employed in a variety of roles such as working in technical positions at customer sites or making sales visits. The company has applied a range of strategies to road safety resulting in annual claim reductions of 7.7% compared to only a 4.5% reduction in collisions nationally. The company s data are used to undertake three studies which focused on driver training, manager training and claim segmentation. Statistical models were employed to investigate the effect of two different driver training courses on the frequency of claims while controlling for other factors. The results indicated that driver training courses significantly reduced both the total number of claims and the claim types targeted by the training. The impacts of the interventions were also adjusted for the effects of non-random driver selection and other safety improvements initiated by the company or other agencies. An important finding of this work was that randomly inflated pre-training events accounted for between a third and a quarter of the observed reduction in claims following training. The second study evaluated the impact of management training on claims using multilevel models which allowed for correlation between observations. The study could not confirm that this training was an effective safety intervention. This null result provides an incentive to re-evaluate the implementation of the scheme. The final study identified homogeneous claim segments using statistical models and the impact of training was evaluated on these segments. Such claims were estimated to be reduced by between 32% to 55% following existing driver training courses. This thesis has helped close important gaps and contributed to knowledge in terms of both intervention methodology and the understanding of the effectiveness of work-related road safety interventions. The results, which are already being applied in the case study organisation, demonstrated that training employees in either safe and fuel efficient driving, or low speed manoeuvring, reduced vehicle insurance claims. Further work is necessary to verify the safety value of manager training including gathering detailed information on interactions between managers and drivers.
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Becová, Lucia. "Měření parametrů lidského operátora." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400558.
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This work focuses on evaluating the parameters of the human operator as the driver of the vehicle simulator. In the first part, the thesis focuses on the examination of human operator parameters evaluation. In the second part of the thesis is a proposal of various scenarios focused on a specific area of measurement. At the end, the work focuses on the processing and evaluation of measured data obtained from the drivers tested.
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Pořízek, David. "Transparentní šifrování pro koncová zařízení." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-399169.
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Cílem této práce je návrh a implementace řešení transparentního šifrování pro platformu Microsoft Windows. Řešení by mělo být propojitelné s produktem prevence proti úniku dat (DLP) a rozšiřovat jej. K implementaci byl využit framework Microsoft File System Minifilter Driver, s jehož pomocí je možné sledovat a upravovat přístup k jednotlivým souborům na externích zařízeních nebo discích za běhu systému. Soubory jsou zabezpečeny na pozadí tak, aby uživatel nebyl neovlivněn při práci. Ovladač zajišťuje, že uživatel vždy pracuje s rozšifrovanými daty. Dále bude také vyvinuta externí aplikace, která umožňuje uživateli přistoupit k zašifrovaným datům, aniž by musel být v síti, kde DLP produkt běží.
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Tillyer, Rob. "Social Conditioning of Police Officers: Exploring the interactive effects of driver demographics on traffic stop outcomes." Cincinnati, Ohio : University of Cincinnati, 2008. http://rave.ohiolink.edu/etdc/view.cgi?acc_num=ucin1222898894.
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Thesis (Ph.D.)--University of Cincinnati, 2008.Advisor: Robin Engel. Title from electronic thesis title page (viewed Feb.25, 2009). Keywords: Policing; Racial Profiling; Social Conditioning Model. Includes abstract. Includes bibliographical references.
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Jomaa, Diala. "A data driven approach for automating vehicle activated signs." Doctoral thesis, Högskolan Dalarna, Datateknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:du-21504.
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Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.
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Shaaban, Sarah, and Sumera Magsi. "Digital business strategy : The driver for change in internal and external business environment." Thesis, Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159938.
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Title: Digital business strategy - The driver for change in internal and external business environment Authors: Sumera Magsi and Sarah Shaaban Advisor: Andrea Fried Master thesis, 30 credits Background:The effects resulting from a more intense use of digital technologies in companies is visible in the integration between business and IT strategies which creates an urge for digital business strategies to emerge. Thesis aim: The aim is to investigate the current state of digital business strategies which includes highlighting benefits and challenges. By doing that we also are aiming towards answering, in what way ITBA can be questioned due to DBS. Methodology: A qualitative research based on a multiple case study by conducting semi- structured interviews. All the selected case companies are using digital business strategies as a part of their internal and external business environment (IEBE). The respondents have a role in the chosen case companies of being responsible for the implementation and use of strategies, digital business strategies and digital technologies. Findings: This study identifies that their exits a linkage between business strategy and ITBA. The main finding about the current state of DBS involves both internal and external DBS activities. Further findings show that benefit of digital business strategy to be the opportunity to levering costumers and challenges to be connected to the different IT maturity levels of the employees. The way that digital business strategy can question ITBA is based on that it is the driver for change for the case companies.
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Fenzel, Mark. "The Business Model Concept and the Sharing Economy : An Overview." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-76717.
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The aim of this article is to give an overview of the business model concept and theories focussing on the sharing economy. Selected concepts and studies are presented, and its application, usefulness and limitations are discussed. The concepts and models that are presented in more detail build the foundation for the realisation of a digital business plan. The plan was part of the overall examination for the course ‘Digital Business Development’ at Linnæus University. The theories and studies concerning business models are being traced back to 1975. With the advent of the Internet mid-1990s the academic community picked up on the business model concept and an increasing number of articles, publications and studies were published. Although the huge interest in the concept, there is still no common theoretical foundation and established researchers such as Michael E. Porter even argue that the business model doesn’t help a company to develop or to assess competitive advantage instead it only helps to understand basic questions. Airbnb and Uber have been the companies mostly cited when articles were written about the ‘sharing economy’. The research field of the sharing economy is rather new and most of the theoretical foundation is rooted in the concept of ownership. Recently, researchers have begun to investigate frameworks around the sharing economy i.e. understanding the determinants of a successful sharing model from a marketing and technological perspective. The literature related to the sharing economy is still in its formation phase. The theory must reach a higher level of generalizability and move away from pure descriptions of ‘successful companies in the sharing economy’. Most studies have focused on identifying motivational factors for consumers and companies to participate in the sharing economy. In conclusion, both concepts have its strengths and weaknesses, but they provide useful insights for analyzing current situations and developing potential strategic directions.
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Stork, Emily J. "INVASIVENESS AND INVASIBILITY IN THE DOLOMITE PRAIRIE PLANT COMMUNITY." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/839.
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Invasive species are cited as a major threat to native community composition and biodiversity throughout the world. Some recent studies have focused on whether invasive species are the drivers or passengers of change in degraded systems. A strongly-interactive community is supposed to resist invasion by all but the most strong invasive competitors (`drivers') which can establish there without the aid of disturbance and actively reduce the abundance of natives. A weakly-interactive community, impaired by some anthropogenic disruption, is invasible by weaker exotics which are merely `passengers' of the habitat degradation that is more constraining to natives. Though competitive and disturbance-adapted species fit into this model, there is no correlate for species with superior toleration of stress. Systems with high degrees of natural abiotic stress are weakly-interactive and as a result may be invasible by an exotic `tolerator' in the same way that anthropogenically-weak systems are invasible by passengers. Dolomite prairie, differentiated from typic tallgrass prairie by its shallow soils, represents a relatively stressful system. A study of its plant community composition and relationships to environmental variables was done to get a better understanding of the natural abiotic drivers of composition. Compositional patterns were most closely associated with the soil depth gradient. Exotic Poa species were by far the most frequent invaders, a finding more typical of Great Lakes alvars than of typic tallgrass prairie of which the dolomite prairie is a subset. I hypothesized that Poa species dominated dolomite prairie via the tolerator model. In a series of removal treatments, I determined that Poa is neither a driver nor a tolerator, but a passenger of environmental degradation. My results suggest that historic anthropogenic degradation rather than specific competitive ability is a common explanation for exotic dominance on the landscape today. More empirical work needs to be conducted in other stressful (particularly relatively undisturbed) systems to further investigate the tolerator model.
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Ding, Yonglian. "Quantifying the Impact of Traffic-Related and Driver-Related Factors on Vehicle Fuel Consumption and Emissions." Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/33350.
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The transportation sector is the dominant source of U.S. fuel consumption and emissions. Specifically, highway travel accounts for nearly 75 percent of total transportation energy use and slightly more than 33 percent of national emissions of EPA's six Criteria pollutants. Enactment of the Clean Air Act Amendment of 1990 (CAAA) and the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) have changed the ways that most states and local governments deal with transportation problems. Transportation planning is geared to improve air quality as well as mobility. It is required that each transportation activity be analyzed in advance using the most recent mobile emission estimate model to ensure not to violate the Conformity Regulation.Several types of energy and emission models have been developed to capture the impact of a number of factors on vehicle fuel consumption and emissions. Specifically, the current state-of-practice in emission modeling (i.e. Mobile5 and EMFAC7) uses the average speed as a single explanatory variable. However, up to date there has not been a systematic attempt to quantify the impact of various travel and driver-related factors on vehicle fuel consumption and emissions.
This thesis first systematically quantifies the impact of various travel-related and driver-related factors on vehicle fuel consumption and emissions. The analysis indicates that vehicle fuel consumption and emission rates increase considerably as the number of vehicle stops increases especially at high cruise speed. However, vehicle fuel consumption is more sensitive to the cruise speed level than to vehicle stops. The aggressiveness of a vehicle stop, which represents a vehicle's acceleration and deceleration level, does have an impact on vehicle fuel consumption and emissions. Specifically, the HC and CO emission rates are highly sensitive to the level of acceleration when compared to cruise speed in the range of 0 to 120 km/h. The impact of the deceleration level on all MOEs is relatively small. At high speeds the introduction of vehicle stops that involve extremely mild acceleration levels can actually reduce vehicle emission rates. Consequently, the thesis demonstrated that the use of average speed as a sole explanatory variable is inadequate for estimating vehicle fuel consumption and emissions, and the addition of speed variability as an explanatory variable results in better models.
Second, the thesis identifies a number of critical variables as potential explanatory variables for estimating vehicle fuel consumption and emission rates. These explanatory variables include the average speed, the speed variance, the number of vehicle stops, the acceleration noise associated with positive acceleration and negative acceleration noise, the kinetic energy, and the power exerted. Statistical models are developed using these critical variables. The statistical models predict the vehicle fuel consumption rate and emission rates of HC, CO, and NOx (per unit of distance) within an accuracy of 88%-96% when compared to instantaneous microscopic models (Ahn and Rakha, 1999), and predict emission rates of HC, CO, and NOx within 95 percentile confidence limits of chassis dynamometer tests conducted by EPA.
Comparing with the current state-of-practice, the proposed statistical models provide better estimates for vehicle fuel consumption and emissions because speed variances about the average speed along a trip are considered in these models. On the other hand, the statistical models only require several aggregate trip variables as input while generating reasonable estimates that are consistent with microscopic model estimates. Therefore, these models could be used with transportation planning models for conformity analysis.
Master of Science
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Tmejová, Tereza. "Model řidiče pro simulační algoritmy." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417521.
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This diploma thesis deals with the creation of a computation driver model. In the first part, there is an overview on driver models for longitudinal and lateral control. Next, driving maneuvres that could be selected for testing of driver model are described. In the practical part, there is created a computational driver model, whose task is to follow required path. The resulting model is tested on three driving maneuvers - steady turning, moose test and slalom. Finally, this model is tested on the passage of a real track. For all these tracks, a comparison is made and the success of the model is evaluated.
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Ponsa, Mussarra Daniel. "Model-Based Visual Localisation Of Contours And Vehicles." Doctoral thesis, Universitat Autònoma de Barcelona, 2007. http://hdl.handle.net/10803/5782.
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El treball d'aquesta tesi es centra en l'anàlisi de seqüències de vídeo, aplicant tècniques basades en models per extreure'n informació quantitativa. En concret, es realitzen diferents propostes en dues àrees d'aplicació: el seguiment de formes basat en models de contorns, i la detecció i seguiment de vehicles en imatges proveïdes per una camera instal·lada en una plataforma mòbil.El treball dedicat al seguiment de formes s'enquadra en el paradigma de contorns actius, del qual presentem una revisió de les diferents propostes existents. En primer lloc, mesurem el rendiment obtingut pels algorismes de seguiment més comuns (filtres basats en Kalman i filtres de partícules), i en segon lloc avaluem diferents aspectes de la seva implementació en un extens treball experimental on es consideren múltiples seqüències sintètiques, distorsionades amb diferents graus de soroll. Així, mitjançant aquest estudi determinem la millor manera d'implementar a la pràctica els algorismes de seguiment clàssics, i identifiquem els seus pros i contres.
Seguidament, el treball s'orienta cap a la millora dels algoritmes de seguiment de contorns basats en filtres de partícules. Aquest algorismes aconsegueixen bons resultats sempre que el número de partícules utilitzades sigui suficient, però malauradament la quantitat de partícules requerides creix exponencialment amb el número de paràmetres a estimar. Per tant, i en el context del seguiment de contorns, presentem tres variants del filtre de partícules clàssic, corresponents a tres noves estratègies per tractar aquest problema. En primer lloc, proposem millorar el seguiment de contorns mirant de propagar més acuradament les partícules emprades per l'algorisme d'una imatge a la següent. Això ho duem a terme utilitzant una aproximació lineal de la funció de propagació òptima. La segona estratègia proposada es basa en estimar part dels paràmetres de manera analítica. Així, es pretén fer un ús més productiu de les partícules emprades, reduint la part dels paràmetres del model que s'han d'estimar amb elles. El tercer mètode proposat té com a objectiu treure profit del fet de que, en aplicacions de seguiment de contorns, sovint els paràmetres relatius a la transformació rígida es poden estimar prou acuradament independentment de la deformació local que el contorn presenti. Això s'utilitza per realitzar una millor propagació de les partícules, concentrant-les més densament en la zona on el contorn seguit es troba. Aquestes tres propostes es validen de manera extensiva en seqüències amb diferents nivells de soroll, amb les que es mesura la millora aconseguida.
A continuació proposem tractar directament l'origen del problema anterior mitjançant la reducció del nombre de paràmetres a estimar per tal de seguir una determinada forma d'interès. Per aconseguir això, proposem modelar aquesta forma usant múltiples models, on cadascun requereix una quantitat de paràmetres inferior a la requerida per un únic model. Es proposa un nou mètode per aprendre aquests models a partir d'un conjunt d'entrenament, així com un nou algorisme per emprar-los en el seguiment dels contorns. Els resultats experimentals certifiquen la validesa d'aquesta proposta.
Finalment, la tesi es centra en el desenvolupament d'un sistema de detecció i seguiment de vehicles. Les propostes realitzades comprenen: un mòdul de detecció de vehicles, un mòdul dedicat a determinar la posició i velocitat 3D dels vehicles detectats, i un mòdul de seguiment per actualitzar la localització dels vehicles a la carretera de manera precisa i eficient. Es realitzen diverses aportacions originals en aquests tres temes, i se n'avalua el rendiment.
This thesis focuses the analysis of video sequences, applying model-based techniques for extracting quantitative information. In particular, we make several proposals in two application areas: shape tracking based on contour models, and detection and tracking of vehicles in images acquired by a camera installed on a mobile platform.
The work devoted to shape tracking follows the paradigm of active contours, from which we present a review of the existent approaches. First, we measure the performance of the most common algorithms (Kalman based filters and particle filters), and then we evaluate its implementation aspects trough an extensive experimental study, where several synthetic sequences are considered, distorted with different degrees of noise. Thus, we determine the best way to implement in practice these classical tracking algorithms, and we identify its benefits and drawbacks.
Next, the work is oriented towards the improvement of contour tracking algorithms based on particle filters. These algorithms reach good results provided that the number of particles is high enough, but unfortunately the required number of particles grows exponentially with the number of parameters to be estimated. Therefore, and in the context of contour tracking, we present three variants of the classical particle filter, corresponding to three new strategies to deal with this problem. First, we propose to improve the contour tracking by propagating more accurately the particles from one image to the next one. This is done by using a linear approximation of the optimal propagation function. The second proposed strategy is based in estimating part of the parameters analytically. Thus, we aim to do a more productive use of the particles, reducing the amount of model parameters that must be estimated through them. The third proposed method aims to exploit the fact that, in contour tracking applications, the parameters related to the rigid transform can be estimated accurately enough independently from the local deformation presented by the contour. This is used to perform a better propagation of the particles, concentrating them more densely in the zone where the tracked contour is located. These three proposals are validated extensively in sequences with different noise levels, on which the reached improvement is evaluated.
After this study, we propose to deal directly with the origin of the previous problem by reducing the number of parameters to be estimated in order to follow a given shape of interest. To reach that, we propose to model the shape using multiple models, where each one requires a lower quantity of parameters than when using a unique model. We propose a new method to learn these models from a training set, and a new algorithm to use the obtained models for tracking the contours. The experimental results certify the validity of this proposal.
Finally, the thesis focuses on the development of a system for the detection and tracking of vehicles. The proposals include: a vehicle detection module, a module devoted to the determination of the three-dimensional position and velocity of the detected vehicles, and a tracking module for updating the location of vehicles on the road in a precise and efficient manner. Several original contributions are done in these three subjects, and their performance is evaluated empirically.
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van, Lint J. W. C., and S. C. Calvert. "A generic multi-level framework for microscopic traffic simulation—Theory and an example case in modelling driver distraction." Elsevier, 2018. https://publish.fid-move.qucosa.de/id/qucosa%3A72789.
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Incorporation of more sophisticated human factors (HF) in mathematical models for driving behavior has become an increasingly popular and important research direction in the last few years. Such models enable us to simulate under which conditions perception errors and risk-taking lead to interactions that result in unsafe traffic conditions and ultimately accidents. In this paper, we present a generic multi-level microscopic traffic modelling and simulation framework that supports this important line of research. In this framework, the driving task is modeled in a multi-layered fashion. At the highest level, we have idealized (collision-free) models for car following and other driving tasks. These models typically contain HF parameters that exogenously “govern the human factor”, such as reaction time, sensitivities to stimuli, desired speed, etc. At the lowest level, we define HF variables (task demand and capacity, awareness) with which we maintain what the information processing costs are of performing driving tasks as well as non-driving related tasks such as distractions. We model these costs using so-called fundamental diagrams of task demand. In between, we define functions that govern the dynamics of the high-level HF parameters with these HF variables as inputs. When total task demand increases beyond task capacity, first awareness may deteriorate, where we use Endsley's three-level awareness construct to differentiate between effects on perception, comprehension, anticipation and reaction time. Secondly, drivers may adapt their response in line with Fullers risk allostasis theory to reduce risk to acceptable levels. This framework can be viewed as a meta model, that provides the analyst possibilities to combine and mix a wide variety of microscopic models for driving behavior at different levels of sophistication, depending on which HF are studied, and which phenomena need to be reproduced. We illustrate the framework with a distraction (rubbernecking) case. Our results show that the framework results in endogenous mechanisms for inter- and intra-driver differences in driving behavior and can generate multiple plausible HF mechanisms to explain the same observable traffic phenomena and congestion patterns that arise due to the distraction. We believe our framework can serve as a valuable tool in testing hypotheses related to the effects of HF on traffic efficiency and traffic safety in a systematic way for both the traffic flow and HF community.
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Terada, Yukinori. "Human Pluripotent Stem Cell-Derived Tumor Model Uncovers the Embryonic Stem Cell Signature as a Key Driver in Atypical Teratoid/Rhabdoid Tumor." Kyoto University, 2019. http://hdl.handle.net/2433/243299.
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Filla, Reno. "Operator and Machine Models for Dynamic Simulation of Construction Machinery." Licentiate thesis, Linköping : Linköpings universitet, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-4092.
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Vadeby, Anna. "Computer based statistical treatment in models with incidental parameters : inspired by car crash data." Doctoral thesis, Linköping : Univ, 2003. http://www.bibl.liu.se/liupubl/disp/disp2003/tek814s.pdf.
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Loy, James Michael. "RELATING NATURALISTIC GLOBAL POSITIONING SYSTEM (GPS) DRIVING DATA WITH LONG-TERM SAFETY PERFORMANCE OF ROADWAYS." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1078.
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This thesis describes a research study relating naturalistic Global Positioning System (GPS) driving data with long-term traffic safety performance for two classes of roadways. These two classes are multilane arterial streets and limited access highways. GPS driving data used for this study was collected from 33 volunteer drivers from July 2012 to March 2013. The GPS devices used were custom GPS data loggers capable of recording speed, position, and other attributes at an average rate of 2.5 hertz.
Linear Referencing in ESRI ArcMAP was performed to assign spatial and other roadway attributes to each GPS data point collected. GPS data was filtered to exclude data with high horizontal dilution of precision (HDOP), incorrect heading attributes or other GPS communication errors.
For analysis of arterial roadways, the Two-Fluid model parameters were chosen as the measure for long-term traffic safety analysis. The Two-Fluid model was selected based on previous research which showed correlation between the Two-Fluid model parameters n and Tm and total crash rate along arterial roadways. Linearly referenced GPS data was utilized to obtain the total travel time and stop time for several half-mile long trips along two arterial roadways, Grand Avenue and California Boulevard, in San Luis Obispo. Regression between log transformed values of these variables (total travel time and stop time) were used to derive the parameters n and Tm. To estimate stop time for each trip, a vehicle “stop” was defined when the device was traveling at less than 2 miles per hour. Results showed that Grand Avenue had a higher value for n and a lower value for Tm, which suggests that Grand Avenue may have worse long-term safety performance as characterized by long-term crash rates. However, this was not verified with crash data due to incomplete crash data in the TIMS database. Analysis of arterial roadways concluded by verifying GPS data collected in the California Boulevard study with sample data collected utilizing a traditional “car chase” methodology, which showed that no significant difference in the two data sources existed when trips included noticeable stop times.
For analysis of highways the derived measurement of vehicle jerk, or rate of change of acceleration, was calculated to explore its relationship with long-term traffic safety performance of highway segments. The decision to use jerk comes from previous research which utilized high magnitude jerk events as crash surrogate, or near-crash events. Instead of using jerk for near-crash analysis, the measurement of jerk was utilized to determine the percentage of GPS data observed below a certain negative jerk threshold for several highway segments. These segments were ¼-mile and ½-mile long. The preliminary exploration was conducted with 39 ¼-mile long segments of US Highway 101 within the city limits of San Luis Obispo. First, Pearson’s correlation coefficients were estimated for rate of ‘high’ jerk occurrences on these highway segments (with definitions of ‘high’ depending on varying jerk thresholds) and an estimate of crash rates based on long-term historical crash data. The trends in the correlation coefficients as the thresholds were varied led to conducting further analysis based on a jerk threshold of -2 ft./sec3 for the ¼-mile segment analysis and -1 ft./sec3 for the ¼-mile segment analysis. Through a negative binomial regression model, it was shown that utilizing the derived jerk percentage measure showed a significant correlation with the total number of historical crashes observed along US Highway 101. Analysis also showed that other characteristics of the roadway, including presences of a curve, presence of weaving (indicated by the presence of auxiliary lanes), and average daily traffic (ADT) did not have a significant correlation with observed crashes. Similar analysis was repeated for 19 ½-mile long segments in the same study area, and it was found the percentage of high negative jerk metric was again significant with historical crashes. The ½-mile negative binomial regression for the presence of curve was also a significant variable; however the standard error for this determination was very high due to a low sample size of analysis segments that did not contain curves.
Results of this research show the potential benefit that naturalistic GPS driving data can provide for long-term traffic safety analysis, even if data is unaccompanied with any additional data (such as live video feed) collected with expensive vehicle instrumentation. The methodologies of this study are repeatable with many GPS devices found in certain consumer electronics, including many newer smartphones.