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- Creators: Shrivastava, Aviral
Description
Cyber-Physical Systems (CPS) are being used in many safety-critical applications. Due to the important role in virtually every aspect of human life, it is crucial to make sure that a CPS works properly before its deployment. However, formal verification of CPS is a computationally hard problem. Therefore, lightweight verification methods such as testing and monitoring of the CPS are considered in the industry. The formal representation of the CPS requirements is a challenging task. In addition, checking the system outputs with respect to requirements is a computationally complex problem. In this dissertation, these problems for the verification of CPS are addressed. The first method provides a formal requirement analysis framework which can find logical issues in the requirements and help engineers to correct the requirements. Also, a method is provided to detect tests which vacuously satisfy the requirement because of the requirement structure. This method is used to improve the test generation framework for CPS. Finally, two runtime verification algorithms are developed for off-line/on-line monitoring with respect to real-time requirements. These monitoring algorithms are computationally efficient, and they can be used in practical applications for monitoring CPS with low runtime overhead.
ContributorsDokhanchi, Adel (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2017
Description
Automated driving systems are in an intensive research and development stage, and the companies developing these systems are targeting to deploy them on public roads in a very near future. Guaranteeing safe operation of these systems is crucial as they are planned to carry passengers and share the road with other vehicles and pedestrians. Yet, there is no agreed-upon approach on how and in what detail those systems should be tested. Different organizations have different testing approaches, and one common approach is to combine simulation-based testing with real-world driving.
One of the expectations from fully-automated vehicles is never to cause an accident. However, an automated vehicle may not be able to avoid all collisions, e.g., the collisions caused by other road occupants. Hence, it is important for the system designers to understand the boundary case scenarios where an autonomous vehicle can no longer avoid a collision. Besides safety, there are other expectations from automated vehicles such as comfortable driving and minimal fuel consumption. All safety and functional expectations from an automated driving system should be captured with a set of system requirements. It is challenging to create requirements that are unambiguous and usable for the design, testing, and evaluation of automated driving systems. Another challenge is to define useful metrics for assessing the testing quality because in general, it is impossible to test every possible scenario.
The goal of this dissertation is to formalize the theory for testing automated vehicles. Various methods for automatic test generation for automated-driving systems in simulation environments are presented and compared. The contributions presented in this dissertation include (i) new metrics that can be used to discover the boundary cases between safe and unsafe driving conditions, (ii) a new approach that combines combinatorial testing and optimization-guided test generation methods, (iii) approaches that utilize global optimization methods and random exploration to generate critical vehicle and pedestrian trajectories for testing purposes, (iv) a publicly-available simulation-based automated vehicle testing framework that enables application of the existing testing approaches in the literature, including the new approaches presented in this dissertation.
One of the expectations from fully-automated vehicles is never to cause an accident. However, an automated vehicle may not be able to avoid all collisions, e.g., the collisions caused by other road occupants. Hence, it is important for the system designers to understand the boundary case scenarios where an autonomous vehicle can no longer avoid a collision. Besides safety, there are other expectations from automated vehicles such as comfortable driving and minimal fuel consumption. All safety and functional expectations from an automated driving system should be captured with a set of system requirements. It is challenging to create requirements that are unambiguous and usable for the design, testing, and evaluation of automated driving systems. Another challenge is to define useful metrics for assessing the testing quality because in general, it is impossible to test every possible scenario.
The goal of this dissertation is to formalize the theory for testing automated vehicles. Various methods for automatic test generation for automated-driving systems in simulation environments are presented and compared. The contributions presented in this dissertation include (i) new metrics that can be used to discover the boundary cases between safe and unsafe driving conditions, (ii) a new approach that combines combinatorial testing and optimization-guided test generation methods, (iii) approaches that utilize global optimization methods and random exploration to generate critical vehicle and pedestrian trajectories for testing purposes, (iv) a publicly-available simulation-based automated vehicle testing framework that enables application of the existing testing approaches in the literature, including the new approaches presented in this dissertation.
ContributorsTuncali, Cumhur Erkan (Author) / Fainekos, Georgios (Thesis advisor) / Ben Amor, Heni (Committee member) / Kapinski, James (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2019
Description
Reducing device dimensions, increasing transistor densities, and smaller timing windows, expose the vulnerability of processors to soft errors induced by charge carrying particles. Since these factors are inevitable in the advancement of processor technology, the industry has been forced to improve reliability on general purpose Chip Multiprocessors (CMPs). With the availability of increased hardware resources, redundancy based techniques are the most promising methods to eradicate soft error failures in CMP systems. This work proposes a novel customizable and redundant CMP architecture (UnSync) that utilizes hardware based detection mechanisms (most of which are readily available in the processor), to reduce overheads during error free executions. In the presence of errors (which are infrequent), the always forward execution enabled recovery mechanism provides for resilience in the system. The inherent nature of UnSync architecture framework supports customization of the redundancy, and thereby provides means to achieve possible performance-reliability trade-offs in many-core systems. This work designs a detailed RTL model of UnSync architecture and performs hardware synthesis to compare the hardware (power/area) overheads incurred. It then compares the same with those of the Reunion technique, a state-of-the-art redundant multi-core architecture. This work also performs cycle-accurate simulations over a wide range of SPEC2000, and MiBench benchmarks to evaluate the performance efficiency achieved over that of the Reunion architecture. Experimental results show that, UnSync architecture reduces power consumption by 34.5% and improves performance by up to 20% with 13.3% less area overhead, when compared to Reunion architecture for the same level of reliability achieved.
ContributorsHong, Fei (Author) / Shrivastava, Aviral (Thesis advisor) / Bazzi, Rida (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2011
Description
There has been exciting progress in the area of Unmanned Aerial Vehicles (UAV) in the last decade, especially for quadrotors due to their nature of easy manipulation and simple structure. A lot of research has been done on achieving autonomous and robust control for quadrotors. Recently researchers have been utilizing linear temporal logic as mission specification language for robot motion planning due to its expressiveness and scalability. Several algorithms have been proposed to achieve autonomous temporal logic planning. Also, several frameworks are designed to compose those discrete planners and continuous controllers to make sure the actual trajectory also satisfies the mission specification. However, most of these works use first-order kinematic models which are not accurate when quadrotors fly at high speed and cannot fully utilize the potential of quadrotors.
This thesis work describes a new design for a hierarchical hybrid controller that is based on a dynamic model and seeks to achieve better performance in terms of speed and accuracy compared with some previous works. Furthermore, the proposed hierarchical controller is making progress towards guaranteed satisfaction of mission specification expressed in Linear Temporal Logic for dynamic systems. An event-driven receding horizon planner is also utilized that aims at distributed and decentralized planning for large-scale navigation scenarios. The benefits of this approach will be demonstrated using simulations results.
This thesis work describes a new design for a hierarchical hybrid controller that is based on a dynamic model and seeks to achieve better performance in terms of speed and accuracy compared with some previous works. Furthermore, the proposed hierarchical controller is making progress towards guaranteed satisfaction of mission specification expressed in Linear Temporal Logic for dynamic systems. An event-driven receding horizon planner is also utilized that aims at distributed and decentralized planning for large-scale navigation scenarios. The benefits of this approach will be demonstrated using simulations results.
ContributorsZhang, Xiaotong (Author) / Fainekos, Georgios (Thesis advisor) / Ben Amor, Heni (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2016