@article {490, title = {Modeling Human Car-Following Behavior from Demonstration with Recurrent Neural Networks}, year = {2020}, abstract = {

The validity of simulation testing for autonomous vehicles depends on the ability to accurately simulate human driving behavior. This project seeks to train a model on an individual{\textquoteright}s driving data, and to test the ability of the model to predict trajectories that replicate the driver{\textquoteright}s style by using the model in a realistic simulated environment. Specifically, we deployed Recurrent Neural Network (RNN) modeling techniques to create a black-box model of an individual{\textquoteright}s driving behavior. We use our RNN-trained model to simulate a human-driven vehicle in the Robot Operating System (ROS) based CAT Vehicle simulator for autonomous vehicle validation. We hope this work is a step to improve testing environments for validating human behavior replicating car-following models and thereby improve testing environments for autonomous vehicles in general.

}, keywords = {car-following models, driving behavior, recurrent neural network, simulation, trajectory prediction}, author = {Iris Jones and Megan Walter}, editor = {Rahul Bhadani} } @conference {478, title = {A meta-metamodel for dynamic constraint feedback in modeling languages}, booktitle = {Proceedings of the 17th ACM SIGPLAN International Workshop on Domain-Specific Modeling}, year = {2019}, abstract = {

Complex design considerations of Cyber-Physical Systems (CPSs) are greatly aided through the use of high-level abstractions in a Domain-Specific Modeling Language (DSML). A DSML environment ensures that models will be correct by construction, however syntax correctness does not imply dynamic safety. Presented is an approach to define a meta-metamodel for DSML design with built in closed loop verification feedback for model correction based on dynamic constraint violations. Usage of this framework during DSML design can benefit CPSs such as autonomous vehicles by ensuring that designs are safe, through codified expert knowledge and verification tool integration. A case study is shown using a simple hybrid controller modeling language and reachability verification tools.

}, doi = {10.1145/3358501.3361239}, url = {https://doi.org/10.1145/3358501.3361239}, author = {Bunting, Matt and Sprinkle, Jonathan} } @inbook {463, title = {Model-based engineering with application to autonomy}, booktitle = {Complexity Challenges in Cyber Physical Systems: Using Modeling and Simulation (M\&S) to Support Intelligence, Adaptation and Autonomy}, year = {2019}, pages = {255-285}, publisher = {Wiley}, organization = {Wiley}, chapter = {10}, abstract = {

In this chapter we focus on where models fit into the verification and validation design cycle of autonomous cyber-physical systems. These systems typically make decisions through myriad of sensing loops, have implementations in multiple languages, and may have their logic represented in several different kinds of formal models. The use of code generation, along with software-in-the-loop and hardware-in-the-loop simulation (discussed further in Section\ 4), permits system designers to apply various agile techniques for the validation and verification of systems as requirements are implemented, tested, and demonstrated. The work in this chapter explores such a design cycle with application to autonomous driving. Examples are given for the implementation of various components that describe vehicle dynamics, control models, system identification, sensor/data acquisition, etc., which can be functionally de- scribed in models, and explored in simulation before utilizing code generation to deploy final solutions. The integration of simulation tools during functional design, software-in-the-loop testing, and hardware-in-the-loop testing, permits regression evaluation of use case scenarios. In addition to functional testing, we also describe how high-level domain- specific models can be used to include verification-in-the-loop toolboxes as part of the design cycle. All the examples in this chapter are based on an autonomous Ford Escape, which has a Robotic Operating System (ROS) API for its control and the integration of autonomous components{\textemdash}however, the results are applicable to other event-based and time-triggered middleware platforms. The implementation models in use include Simulink, MATLAB, StateFlow, and other domain-specific languages that specify high-level behaviors.

}, isbn = {978-1-119-55239-0}, author = {Rahul Bhadani and Matt Bunting and Jonathan Sprinkle} } @conference {sprinkle295, title = {Model Predictive Control for Space Missions}, booktitle = {The First American Model Predictive Control Summer School}, year = {2017}, author = {Bharani P. Malladi and Nathalie Risso and Yegeta Zeleke} } @proceedings {sprinkle285, title = {Model-based Fuzzy Logic Classifier Synthesis for Optimization of Data-Adaptable Embedded Systems}, year = {2016}, pages = {293-302}, address = {Hartford, CT}, doi = {10.1109/COMPSAC.2016.156}, author = {Adrian Lizarraga and Roman Lysecky and Jonathan Sprinkle} } @conference {sprinkle272, title = {Model-driven Optimization of Data-Adaptable Embedded Systems}, booktitle = {COMPSAC}, year = {2016}, pages = {293-302}, publisher = {IEEE}, organization = {IEEE}, abstract = {

Complex sensing and decision applications such as object tracking and classification, video surveillance, unmanned aerial vehicle flight decisions, and others operate on vast data streams with dynamic characteristics. As the availability and quality of the sensed data changes, the underlying models and decision algorithms should continually adapt in order to meet desired high-level requirements. Due to the complexity of such dynamic data-driven systems, traditional design time techniques are often incapable of producing a solution that remains optimal in the face of dynamically changing data, algorithms, and even availability of computational resources. To assist developers of these systems, we present a modeling and optimization methodology that enables developers to capture application task flows and data sources, define associated quality metrics with data types, specify each algorithm{\textquoteright}s data and quality requirements, and define a data quality estimation framework to optimize the application at runtime. We demonstrate each facet of the modeling and optimization process via a video-based vehicle tracking and collision avoidance application, and show how such an approach results in efficient design space exploration when selecting the optimal set of algorithm modalities. When searching for an application configuration within 1\% to 5\% of optimal, our model-guided approach can achieve speedups of up to 9.3X versus a standard genetic algorithm and speedups of up to 80X relative to a brute force algorithm.

}, doi = {10.1109/COMPSAC.2016.156}, url = {http://dx.doi.org/10.1109/COMPSAC.2016.156}, author = {Adrian Lizarraga and Roman Lysecky and Jonathan Sprinkle} } @conference {465, title = {Model-Driven Optimization of Data-Adaptable Embedded Systems}, booktitle = {2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, author = {Adrian Lizarraga and Roman Lysecky and Jonathan Sprinkle} } @mastersthesis { d:whitsitt-phd, title = {A Methodology for Mending Dynamic Constraint Violations in Cyber Physical Systems By Generating Model Transformations}, volume = {PhD}, year = {2014}, month = {12/2014}, school = {University of Arizona}, type = {mastersPhD Dissertation}, address = {Tucson, AZ}, author = {Sean Whitsitt} } @conference {sprinkle260, title = {A Mobile Interface designed for the Safety Verification of Autonomous Vehicle Trajectories}, booktitle = {ACM Mid-Southeast Conference}, year = {2014}, publisher = {ACM}, organization = {ACM}, address = {Gatlinburg, TN}, author = {Tarif Haque and Joanna De Los Santos and Duc Lam} } @article {214, title = {A Modular Framework to Enable Rapid Evaluation and Exploration of Energy Management Methods in Smart Home Platforms}, journal = {Energy Systems}, year = {2014}, month = {04/2014}, pages = {Online First}, abstract = {

Numerous efforts focus on developing smart grid and smart home plat- forms to provide monitoring, management, and optimization solutions. In order to more effectively manage energy resources, a holistic view is needed; however the involved platforms are complex and require integration of a multitude of parameters such as the end-user behavior, underlying hardware components, environment, etc., many of which operate on varying time scale at various levels of detail. A general and modular framework is presented to enable designers to focus on modeling, simulating, analyzing, or optimizing specific sub-components without requiring a detailed imple- mentation across all levels. We incorporate two case studies in which the proposed framework is utilized to help an end user evaluate platform configurations given an energy usage model, as well as integrate an energy optimization module to investigate rescheduling of appliance usage times in an effort to lower cost.\ 

}, issn = {1868-3967}, doi = {10.1007/s12667-014-0121-9}, url = {http://dx.doi.org/10.1007/s12667-014-0121-9}, author = {Xiao Qin and Lin Lin and Susan Lysecky and Janet Roveda and Young-Jun Son and Jonathan Sprinkle} } @article {213, title = {Motorized mobility scooters: The Use of Training/Intervention and Technology for Improving Driving Skills in Aging Adults - A Mini-Review}, journal = {Gerontology}, volume = {60}, year = {2014}, month = {06/2014}, pages = {357-365}, doi = {10.1159/000356766}, url = {http://www.karger.com/Article/FullText/356766}, author = {Nima Toosizadeh and Matthew Bunting and Carol Howe and Jane Mohler and Jonathan Sprinkle and Bijan Najafi} } @conference {234, title = {Mobile Device Software: Model-Based Architectures and Examples}, booktitle = {Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the}, year = {2013}, month = {April}, pages = {215}, keywords = {API, application program interfaces, canonical UML models, Computational modeling, computer science education, Computers, Conferences, high-level software concepts, mobile computing, mobile device apps, mobile device programming, mobile device software, Mobile handsets, model-based architectures, model-based design, model-based examples, object-oriented programming, Software, software architecture, software engineering, terminology points, Tutorials, unclear starting points, Unified modeling language}, doi = {10.1109/ECBS.2013.28}, author = {Jonathan Sprinkle} } @conference {235, title = {Model Based Development with the Skeleton Design Method}, booktitle = {20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems}, year = {2013}, pages = {12-19}, doi = {10.1109/ECBS.2013.16}, url = {http://dx.doi.org/10.1109/ECBS.2013.16}, author = {Sean Whitsitt and Jonathan Sprinkle and Roman Lysecky} } @conference {231, title = {Model-Based Software Synthesis for Self-Reconfigurable Sensor Network in Water Monitoring}, booktitle = {Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the}, year = {2013}, month = {April}, pages = {40-48}, keywords = {accelerometers, Code Generation, communication task, computation task, Computational modeling, concurrent engineering, concurrent tasks specification, control tasks, cyber-physical systems, domain-specific modeling language, drifters, embedded programming, environmental monitoring (geophysics), environmental science computing, floating sensor testbed, formal specification, Global Positioning System, GPS sensors, hand-written code, Instruction sets, mobile computing, mobile phone, mobile radio, mobile sensing platforms, model-based software synthesis, model-integrated computing, program compilers, Programming, self-reconfigurable sensor network, Smart phones, software synthesis, ubiquitous mobile device, Unified modeling language, water flow monitoring, wireless sensor networks}, doi = {10.1109/ECBS.2013.34}, url = {http://dx.doi.org/10.1109/ECBS.2013.34}, author = {Kun Zhang and Jonathan Sprinkle} } @article {j:whitsitt2012jacic, title = {Modeling Autonomous Systems}, journal = {AIAA Journal of Aerospace Information Systems}, volume = {10}, year = {2013}, pages = {396-413}, doi = {10.2514/1.I010039}, url = {http://dx.doi.org/10.2514/1.I010039}, author = {Sean Whitsitt and Jonathan Sprinkle} } @proceedings {226, title = {ME {\textquoteright}12: Proceedings of the 6th International Workshop on Models and Evolution}, year = {2012}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-1798-6}, editor = {Tamzalit, Dalila and Bernhard Sch{\"a}tz and Jonathan Sprinkle and Pierantonio, Alfonso} } @article { j:sprinkle-sosym-2012, title = {Metamodel-Based Metrics for Complexity of Using a DSML}, journal = {Software and Systems Modeling}, volume = {TBD}, number = {TBD}, year = {2012}, pages = {(in preparation)}, author = {Jonathan Sprinkle} } @article { j:smc-a-camera-controller, title = {Model-Based Configuration of a Heterogeneous Human-in-the-loop Command and Control Simulation Environment}, journal = {tbd}, volume = {tbd}, number = {tbd}, year = {2012}, pages = {(in preparation)}, author = {Diyang Chu and Jacob Gulotta and Jonathan Sprinkle and Himanshu Neema and Harmon Nine and Nicholas Kottenstette and Graham Hemingway and Janos Sztipanovits} } @conference {237, title = {Modeling and Code Generation with Autonomous Vehicles}, booktitle = {ACM/IEEE 15th International Conference on Model Driven Engineering Languages and Systems Doctoral Symposium}, year = {2012}, address = {Innsbruck Austria}, author = {Sean Whitsitt} } @proceedings {228, title = {{MPM {\textquoteright}12}: Proceedings of the 6th International Workshop on Multi-Paradigm Modeling}, year = {2012}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-1805-1}, editor = {Hardebolle, C{\'e}cile and Syriani, Eugene and Jonathan Sprinkle and M{\'e}sz{\'a}ros, Tam{\'a}s} } @conference { w:whitsitt-ecbs-mbd-2011, title = {Message Modeling for the Joint Architecture for Unmanned Systems (JAUS)}, booktitle = {Proceedings of the 8th IEEE Workshop on Model-Based Development for Computer-Based Systems}, year = {2011}, month = {April}, pages = {251{\textendash}259}, abstract = {The Joint Architecture for Unmanned Systems (JAUS) is a standard for sensing, control, and computational communication of components for unmanned systems. This paper presents a modeling environment capable of producing a domain-specific prototype of the software necessary for inter-computer communications. A metamodel is used to provide the domain-specific modeling language to model both the messages used in JAUS, and the shell interfaces for components that transmit and receive those messages. The produced artifacts are C and C++ code that can be used in unmanned systems and simulations of such systems, including tests that validate the structure and behavior of the generated code. The generated code is compatible with standard JAUS implementations, and is validated using the OpenJAUS open source API and framework. Future work describes the second spiral of features and behaviors (currently in the design phase). The case study and test environment for the software generated by this project is an autonomous ground vehicle, modeled on a Ford Escape Hybrid that is used in laboratory experiments.}, doi = {10.1109/ECBS.2011.17}, url = {http://dx.doi.org/10.1109/ECBS.2011.17}, author = {Sean Whitsitt and Jonathan Sprinkle} } @conference { c:sprinkle-multicore, title = {On the Mitigation of MultiCore-Induced Behavioral Deviations of an Autonomous Ground Vehicle}, booktitle = {Proceedings of the 18th IEEE International Conference and Workshops on Engineering of Computer-Based Systems}, year = {2011}, pages = {159-168}, publisher = {IEEE}, organization = {IEEE}, abstract = {

Complex systems such as autonomous vehicles frequently utilize a distributed network of computers for sensing, control, and supervisory tasks. A common way to abstract the deployment of the computational nodes that implement the system{\textquoteright}s behavior is through the utilization of middleware, which treats each atomic processing element as a component. Multiple components may execute on a single node, and nodes are typically heterogeneous in their processing power. For component implementations that use an event-driven model of computation, however, significant behavioral deviations may occur when a single-core computational node is replaced with a multicore node, especially if that computational node is running more than one component. This paper discusses the observed behavioral deviations through a series of simulations with identical initial conditions, performed on various single core and multicore processing platforms. In addition to the empirical demonstration, the paper provides a technique to mitigate the behavioral deviations by inserting a time-triggered buffer between a key set of components, enforcing a loosely time-triggered execution even though the system is still defined through event-triggered components. This preserves existing legacy code, but provides a time-triggered execution.

}, doi = {10.1109/ECBS.2011.29}, url = {http://dx.doi.org/10.1109/ECBS.2011.29}, author = {Jonathan Sprinkle and Brandon Eames} } @mastersthesis { a:hudson-ms, title = {Model Transformation by Domain-Specific Models}, year = {2011}, month = {December}, school = {University of Arizona}, type = {mastersmasters}, author = {Maribel Hudson} } @conference { w:vijay-ecbs-mbd-2011, title = {Modeling of Data Adaptable Reconfigurable Embedded Systems}, booktitle = {Proceedings of the 8th IEEE Workshop on Model-Based Development for Computer-Based Systems}, year = {2011}, month = {April}, pages = {276-285}, abstract = {

Many applications require high flexibility, high configurability and high processing speeds. The physical constraints of a highly flexible system{\textquoteright}s hardware implementation preclude a hardware solution that satisfies all configuration options. Similarly for pure software implementations, even if configurability is satisfied, process efficiency will be sacrificed. Thus for applications of any significant size, there can be no single hardware or software configuration that can efficiently support all the configurability options of the applications. The Data-Adaptable Reconfigurable Embedded System (DARES) approach tackles this problem through combination of the hardware-software co-design and reconfigurable computing methodologies. Data-adaptability means that as data streams change, the system is reconfigured along the baselines defined within the system{\textquoteright}s specifications. In this project we use the concepts of Model-Integrated Computing to implement a domain-specific modeling language for the DARES approach. The language captures all the configurability options of the application task(s), performs design-space exploration, and provides a template for source code generation.

}, doi = {10.1109/ECBS.2011.31}, url = {http://dx.doi.org/10.1109/ECBS.2011.31}, author = {Vijay Gopinath and Jonathan Sprinkle and Roman Lysecky} } @mastersthesis { a:whitsitt-ms, title = {Modeling the Messaging and Component Interfaces of Autonomous Systems}, year = {2011}, month = {August}, school = {University of Arizona}, type = {mastersmasters}, url = {http://bracton.ece.arizona.edu/svn/jmsgroup/trunk/public/whitsitt-thesis.pdf}, author = {Sean Whitsitt} } @inbook { j:sprinkle-mbeerts4-2009, title = {Metamodelling}, booktitle = {Model-Based Engineering of Embedded Real-Time Systems}, series = {Lecture Notes in Computer Science}, volume = {6100}, year = {2010}, pages = {59{\textendash}78}, publisher = {Springer}, organization = {Springer}, chapter = {4}, url = {http://www.springer.com/computer/swe/book/978-3-642-16276-3}, author = {Jonathan Sprinkle and Bernhard Rumpe and Hans Vangheluwe and G{\'a}bor Karsai} } @inbook { j:levendovszky-mbeerts14-2009, title = {Model Evolution and Management}, booktitle = {Model-Based Engineering of Embedded Real-Time Systems}, series = {Lecture Notes in Computer Science}, volume = {6100}, year = {2010}, pages = {243{\textendash}272}, publisher = {Springer}, organization = {Springer}, chapter = {10}, url = {http://www.springer.com/computer/swe/book/978-3-642-16276-3}, author = {T{\'\i}hamer Levendovszky and Bernhard Rumpe and Bernhard Sch{\"a}tz and Jonathan Sprinkle and Hans Vangheluwe} } @conference { c:sprinkle-ease-2010, title = {Modeling Languages Applied to Decision Controllers for Embedded Human Systems}, booktitle = {Seventh IEEE International Conference and Workshops on Engineering of Autonomic and Autonomous Systems (EAsE 2010)}, year = {2010}, month = {March}, pages = {129{\textendash}136}, publisher = {IEEE}, organization = {IEEE}, doi = {10.1109/EASe.2010.24}, url = {http://dx.doi.org/10.1109/EASe.2010.24}, author = {Jonathan Sprinkle and Diyang Chu} } @conference { w:sprinkle-oopsla-2009, title = {Model-Based Autosynthesis of Time-Triggered Buffers for Event-Based Middleware Systems}, booktitle = {9th OOPSLA Workshop on Domain-Specific Modeling}, year = {2009}, month = {October}, pages = {119{\textendash}124}, url = {http://www.dsmforum.org/events/DSM09/Papers/Sprinkle.pdf}, author = {Jonathan Sprinkle and Brandon Eames} } @article { j:sprinkle-sosym-2009, title = {Model-based design: a report from the trenches of the {DARPA} Urban Challenge}, journal = {Software and Systems Modeling}, volume = {8}, number = {4}, year = {2009}, month = {September}, pages = {551-566}, publisher = {Springer Berlin / Heidelberg}, abstract = {The impact of model-based design on the software engineering community is impressive, and recent research in model transformations, and elegant behavioral specifications of systems has the potential to revolutionize the way in which systems are designed. Such techniques aim to raise the level of abstraction at which systems are specified, to remove the burden of producing application-specific programs with general-purpose programming. For complex real-time systems, however, the impact of model-driven approaches is not nearly so widespread. In this paper, we present a perspective of model-based design researchers who joined with software experts in robotics to enter the DARPA Urban Challenge, and to what extent model-based design techniques were used. Further, we speculate on why, according to our experience and the testimonies of many teams, the full promises of model-based design were not widely realized for the competition. Finally, we present some thoughts for the future of model-based design in complex systems such as these, and what advancements in modeling are needed to motivate small-scale projects to use model-based design in these domains.}, issn = {1619-1366 (Print) 1619-1374 (Online)}, doi = {10.1007/s10270-009-0116-5}, url = {http://dx.doi.org/10.1007/s10270-009-0116-5}, author = {Jonathan Sprinkle and J. Mikael Eklund and Humberto Gonzalez and Esten Ingar Gr{\o}tli and Ben Upcroft and Alex Makarenko and Will Uther and Michael Moser and Robert Fitch and Hugh Durrant-Whyte and S. Shankar Sastry} } @article {p:sprinkleEmbeddedSystems, title = {Model Based Systems Engineering}, year = {2006}, author = {Jonathan Sprinkle} } @article {j:SprinklePotentials2004, title = {Model-Integrated Computing}, journal = {IEEE Potentials}, volume = {23}, number = {1}, year = {2004}, month = {February}, pages = {28{\textendash}30}, doi = {10.1109/MP.2004.1266937}, url = {http://dx.doi.org/10.1109/MP.2004.1266937}, author = {Jonathan Sprinkle} } @conference {w:SprinkleUML2003, title = {Managing Intent: The Driving Forces of Model Transformations}, booktitle = {{UML} 2003, Workshop in Software Model Engineering}, year = {2003}, month = {October}, url = {http://www.isis.vanderbilt.edu/publications/archive/Sprinkle_J_10_21_2003_Managing_I.pdf}, author = {Jonathan Sprinkle} } @article {a:MyAreaPaper, title = {Metamodel Based Model Migration}, year = {2003}, month = {February}, publisher = {Vanderbilt University}, address = {2015 Terrace Place}, url = {http://www.isis.vanderbilt.edu/publications/archive/Sprinkle_JM_2_5_2003_Metamodel_.pdf}, author = {Jonathan Sprinkle} } @mastersthesis {a:MyDissertation, title = {Metamodel Driven Model Migration}, year = {2003}, month = {August}, school = {Vanderbilt University}, type = {mastersphd}, address = {Nashville, TN 37203}, url = {http://www.isis.vanderbilt.edu/sites/default/files/Sprinkle_JM_8_0_2003_Metamodel_.pdf}, author = {Jonathan Sprinkle} } @conference {w:SprinkleOOPSLA2003, title = {Model Migration through Visual Modeling}, booktitle = {OOPSLA, 3rd ACM Workshop on Domain-Specific Modeling}, year = {2003}, month = {October}, url = {http://www.isis.vanderbilt.edu/publications/archive/Sprinkle_J_10_26_2003_Model_Migr.pdf}, author = {Jonathan Sprinkle and G{\'a}bor Karsai} } @mastersthesis {a:MyMsThesis, title = {Model Integrated Program Synthesis of Agent Negotiation Protocols}, year = {2000}, month = {August}, school = {Vanderbilt University}, type = {mastersmasters}, address = {Nashville, TN 37203}, author = {Jonathan Sprinkle} } @conference {c:SprinkleSMC2000, title = {Modeling Agent Negotiation}, booktitle = {Proceedings of the 2000 IEEE International Conference on Systems, Man, and Cybernetics}, volume = {1}, year = {2000}, month = {October}, pages = {454{\textendash}459}, doi = {10.1109/ICSMC.2000.885034}, url = {http://dx.doi.org/10.1109/ICSMC.2000.885034}, author = {Jonathan Sprinkle and Christopher P. van Buskirk and G{\'a}bor Karsai} }