Rodionova, Alena

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2017 - 20182
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  • Publication
    Safe At Any Speed: A Simulation-Based Test Harness for Autonomous Vehicles
    (2017-10-19) Abbas, Houssam; O'Kelly, Matthew; Rodionova, Alena; Mangharam, Rahul
    The testing of Autonomous Vehicles (AVs) requires driving the AV billions of miles under varied scenarios in order to find bugs, accidents and otherwise inappropriate behavior. Because driving a real AV that many miles is too slow and costly, this motivates the use of sophisticated `world simulators', which present the AV's perception pipeline with realistic input scenes, and present the AV's control stack with realistic traffic and physics to which to react. Thus the simulator is a crucial piece of any CAD toolchain for AV testing. In this work, we build a test harness for driving an arbitrary AV's code in a simulated world. We demonstrate this harness by using the game Grand Theft Auto V (GTA) as world simulator for AV testing. Namely, our AV code, for both perception and control, interacts in real-time with the game engine to drive our AV in the GTA world, and we search for weather conditions and AV operating conditions that lead to dangerous situations. This goes beyond the current state-of-the-art where AVs are tested under ideal weather conditions, and lays the ground work for a more comprehensive testing effort. We also propose and demonstrate necessary analyzes to validate the simulation results relative to the real world. The results of such analyses allow the designers and verification engineers to weigh the results of simulation-based testing.
  • Publication
    Real-time Decision Policies with Predictable Performance
    (2018-01-06) Abbas, Houssam; Mamouras, Konstantinos; Alur, Rajeev; Rodionova, Alena; Mangharam, Rahul
    As methods and tools for Cyber-Physical Systems grow in capabilities and use, one-size-fits-all solutions start to show their limitations. In particular, tools and languages for programming an algorithm or modeling a CPS that are specific to the application domain are typically more usable, and yield better performance, than general-purpose languages and tools. In the domain of cardiac arrhythmia monitoring, a small, implantable medical device continuously monitors the patient's cardiac rhythm and delivers electrical therapy when needed. The algorithms executed by these devices are streaming algorithms, so they are best programmed in a streaming language that allows the programmer to reason about the incoming data stream as the basic object, rather than force her to think about lower-level details like state maintenance and minimization. Because these devices are resource-constrained, it is useful if the programming language allowed predictable performance in terms of processing runtime and energy consumption, or more general costs. StreamQRE is a declarative streaming programming language, with an efficient and portable implementation and strong theoretical guarantees. In particular, its evaluation algorithm guarantees constant cost (runtime, memory, energy) per data item, and also calculates upper bounds on the per-item cost. Such an estimate of the cost allows early exploration of the algorithmic possibilities, while maintaining a handle on worst-case performance, on the basis of which hardware can be designed and algorithms can be tuned.