We propose a reference architecture of safety-critical or industry-critical human cyber-physical systems (CPSs) capable of expressing essential classes of system-level interactions between CPS and humans relevant for the societal acceptance of such systems. To reach this quality gate, the expressivity of the model must go beyond classical viewpoints such as operational, functional, and architectural views and views used for safety and security analysis. The model does so by incorporating elements of such systems for mutual introspections in situational awareness, capabilities, and intentions to enable a synergetic, trusted relation in the interaction of humans and CPSs, which we see as a prerequisite for their societal acceptance. The reference architecture is represented as a metamodel incorporating conceptual and behavioral semantic aspects. We illustrate the key concepts of the metamodel with examples from cooperative autonomous driving, the operating room of the future, cockpit-tower interaction, and crisis management.
Smart City Concept Based on Cyber-Physical Social Systems with Hierarchical Ethical Agents Approach
A smart city is considered a sustainable city that manages needed resources and makes autonomous decisions to improve the quality of life of its citizens. On the other hand, Cyber-Physical Systems (CPS) have been implemented as isolated systems inside the city. For instance, the traffic lights, autonomous navigation for cars, and so on. Instead, consider a smart city with an integrated CPS for independent blocks that can be interconnected in a central unit. However, when a CPS makes decisions about the integration of ethical concepts based on human perception, social space must be added, and so a CPS must be transformed into a Cyber-Physical Social System (CPSS). Furthermore, a new type of social interaction between all the elements in a CPSS within a smart city presents human behavioral challenges such as virtual-morality. This paper first proposes an Artificial Moral Agent with machine learning algorithms to regulate the interaction within the CPSS, adding itself to all the subsystems’ communication. Additionally, a moral agent structure is proposed with a morality filter as its fundamental component.
more »
« less
- Award ID(s):
- 1828010
- NSF-PAR ID:
- 10344400
- Date Published:
- Journal Name:
- 23rd International Conference on Human-Computer Interaction (HCII 2021) - Universal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments
- Volume:
- 12769
- Page Range / eLocation ID:
- 424–437
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Chenyang Lu (Ed.)more » « less
-
With the development of sensing and communica- tion technologies in networked cyber-physical systems (CPSs), multi-agent reinforcement learning (MARL)-based methodolo- gies are integrated into the control process of physical systems and demonstrate prominent performance in a wide array of CPS domains, such as connected autonomous vehicles (CAVs). However, it remains challenging to mathematically characterize the improvement of the performance of CAVs with commu- nication and cooperation capability. When each individual autonomous vehicle is originally self-interest, we can not assume that all agents would cooperate naturally during the training process. In this work, we propose to reallocate the system’s total reward efficiently to motivate stable cooperation among autonomous vehicles. We formally define and quantify how to reallocate the system’s total reward to each agent under the proposed transferable utility game, such that communication- based cooperation among multi-agents increases the system’s total reward. We prove that Shapley value-based reward reallocation of MARL locates in the core if the transferable utility game is a convex game. Hence, the cooperation is stable and efficient and the agents should stay in the coalition or the cooperating group. We then propose a cooperative policy learning algorithm with Shapley value reward reallocation. In experiments, compared with several literature algorithms, we show the improvement of the mean episode system reward of CAV systems using our proposed algorithm.more » « less
-
Prototyping and validating hardware–software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible and open-access ecosystem. This work presents our attempt to develop such a comprehensive research and education ecosystem, called AutoDRIVE, for synergistically prototyping, simulating and deploying cyber-physical solutions pertaining to autonomous driving as well as smart city management. AutoDRIVE features both software as well as hardware-in-the-loop testing interfaces with openly accessible scaled vehicle and infrastructure components. The ecosystem is compatible with a variety of development frameworks, and supports both single- and multi-agent paradigms through local as well as distributed computing. Most critically, AutoDRIVE is intended to be modularly expandable to explore emergent technologies, and this work highlights various complementary features and capabilities of the proposed ecosystem by demonstrating four such deployment use-cases: (i) autonomous parking using probabilistic robotics approach for mapping, localization, path-planning and control; (ii) behavioral cloning using computer vision and deep imitation learning; (iii) intersection traversal using vehicle-to-vehicle communication and deep reinforcement learning; and (iv) smart city management using vehicle-to-infrastructure communication and internet-of-things.more » « less
-
Many Cyber-Physical Systems (CPS) have timing constraints that must be met by the cyber components (software and the network) to ensure safety. It is a tedious job to check if a CPS meets its timing requirement especially when they are distributed and the software and/or the underlying computing platforms are complex. Furthermore, the system design is brittle since a timing failure can still happen e.g., network failure, soft error bit flip, etc. In this paper, we propose a new design methodology called Plan B where timing constraints of the CPS are monitored at the runtime, and a proper backup routine is executed when a timing failure happens to ensure safety. We provide a model on how to express the desired timing behavior using a set of timing constructs in a C/C++ code and how to efficiently monitor them at the runtime. We showcase the effectiveness of our approach by conducting experiments on three case studies: 1) the full software stack for autonomous driving (Apollo), 2) a multi-agent system with 1/10th scale model robots, and 3) a quadrotor for search and rescue application. We show that the system remains safe and stable even when intentional faults are injected to cause a timing failure. We also demonstrate that the system can achieve graceful degradation when a less extreme timing failure happens.more » « less
-
null (Ed.)Cyber-Physical Systems (CPS) are important components of critical infrastructure and must operate with high levels of reliability and security. We propose a conceptual approach to securing CPSs: the Cyber-Physical Immune System (CPIS), a collection of hardware and software elements deployed on top of a conventional CPS. Inspired by its biological counterpart, the CPIS comprises an independent network of distributed computing units that collects data from the conventional CPS, utilizes data-driven techniques to identify threats, adapts to the changing environment, alerts the user of any threats or anomalies, and deploys threat-mitigation strategies.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-78095-1_31
