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Behavioral adaptation of drivers when driving among automated vehicles

Journal of Intelligent and Connected Vehicles 2022年第3期5卷 309-315页

作者： Maytheewat Aramrattana Jiali Fu Department of Traffic and Road Users Swedish National Road and Transport Research InstituteLinköpingSweden Selpi Department of Computer Science and Engineering Chalmers University of TechnologyGöteborgSweden and Department of Mechanics and Maritime SciencesChalmers University of TechnologyGöteborgSweden

Purpose–This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles(AVs)compared to driving among manually driven vehicles(MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic ***,mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional ***/methodology/approach–A driving simulator study is designed to explore whether such behavioral adaptations *** different driving scenarios were explored on a three-lane highway:driving on the main highway and merging from an *** this study,18 research participants were ***–Behavioral adaptation can be observed in terms of car-following speed,car-following time gap,number of lane change and overall driving *** adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or *** significant differences in behavior were found in more than 90%of the research participants,they adapted their behavior differently,and thus,magnitude of the behavioral adaptation remains ***/value–The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding *** finding differs from previous studies,which have shown that drivers tend to adapt their behaviors with respect to the surrounding ***,the surrounding vehicles in this study are more“free flow’”compared to previous studies with a fixed formation such as ***,long-term observations are required to further support this claim.

关键词： Automated vehicles Driver behaviors and assistance Human-robot interaction Behavioral adaptation Driving simulator experiment

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CBP: Coordinated management of cache partitioning, bandwidth partitioning and prefetch throttling 21

CBP: Coordinated management of cache partitioning, bandwidth...

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Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques

作者： Nadja Ramhöj Holtryd Madhavan Manivannan Per Stenström Miquel Pericàs Department of Computer Science and Engineering Chalmers University of Technology Göteborg Sweden

ISBN: (纸本)9781665442787

Reducing the average memory access time is crucial for improving the performance of applications running on multi-core architectures. With workload consolidation this becomes increasingly challenging due to shared resource contention. Techniques for partitioning of shared resources - cache and bandwidth - and prefetch throttling have been proposed to mitigate contention and reduce the average memory access time. However, existing proposals only employ a single or a subset of these techniques and are therefore not able to exploit the full potential of coordinated management of cache, bandwidth and prefetching. Our characterization results show that application performance, in several cases, is sensitive to prefetching, cache and bandwidth allocation altogether. Furthermore, the results show that managing these together provides higher performance potential during workload consolidation as it enables more resource trade-offs. In this paper, we propose CBP a coordination mechanism for dynamically managing prefetching throttling, cache and bandwidth partitioning, in order to reduce average memory access time and improve performance. CBP works by employing individual resource managers to determine the appropriate setting for each resource and a coordinating mechanism in order to enable inter-resource trade-offs. Our evaluation on a 16-core CMP shows that CBP, on average, improves performance by 11% compared to the state-of-the-art technique that manages cache partitioning and prefetching and by 50% compared to the baseline without cache partitioning, bandwidth partitioning and prefetch throttling.

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LLMSECCODE: EVALUATING LARGE LANGUAGE MODELS FOR SECURE CODING

arXiv

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arXiv 2024年

作者： Rydén, Anton Schiller, Elad Michael Näslund, Erik Almgren, Magnus Department of Computer Science and Engineering Chalmers University of Technology Gothenburg41296 Sweden

The rapid deployment of Large Language Models (LLMs) requires careful consideration of their effect on cybersecurity. Our work aims to improve the selection process of LLMs that are suitable for facilitating Secure Coding (SC). This raises challenging research questions, such as (RQ1) Which functionality can streamline the LLM evaluation? (RQ2) What should the evaluation measure? (RQ3) How to attest that the evaluation process is impartial? To address these questions, we introduce LLMSecCode, an open-source evaluation framework designed to assess LLM SC capabilities objectively. We validate the LLMSecCode implementation through experiments. When varying parameters and prompts, we find a 10% and 9% difference in performance, respectively. We also compare some results to reliable external actors, where our results show a 5% difference. We strive to ensure the ease of use of our open-source framework and encourage further development by external actors. With LLMSecCode, we hope to encourage the standardization and benchmarking of LLMs’ capabilities in security-oriented code and tasks. © 2024, CC BY.

关键词： Modeling languages

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Efficient Monitoring of CPS and IoT Systems: A Deployment Guide for Empirical Evaluations

Efficient Monitoring of CPS and IoT Systems: A Deployment Gu...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Jan Körner Samuel Bach Albin Karlsson Linus Sundkvist Romaric Duvignau Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg Sweden

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

As the digitalization of our world continues, the volume of data produced escalates rapidly. Communication often constitutes the most energy-intensive aspect of applications, making it a prime target for optimization. This paper studies the efficiency and precision of monitoring Cyber-Physical Systems (CPS) and Internet of Things (IoT) devices in real experimental deployment scenarios. We evaluate in this work the performance of six different monitoring algorithms concerning CPU utilization, memory usage, network traffic, energy consumption, and monitoring accuracy. Our experimental setup is a network consisting of 38 Raspberry Pis connected to a single host computer via Ethernet. Monitoring was conducted both on the devices themselves and on the host computer, which served as the metrics-receiving stack. We offer here a comprehensive deployment guide serving as a valuable resource for reproducing similar monitoring experiments on IoT devices. Additionally, our own empirical evaluation indicate notable differences among the tested algorithms, highlighting the importance of application constraints on the selection of a monitoring algorithm. Seeking those real-world experiments aim to add substantial value to existing surveys by offering deeper insights, practical findings and empirical evidence.

关键词： Surveys Performance evaluation Energy consumption Memory management Telecommunication traffic Ethernet Filtering algorithms

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Classifying 5G Encrypted Packet Traces

Classifying 5G Encrypted Packet Traces

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International Conference on Electrical, Communication, and computer engineering (ICECCE)

作者： José Armando Tesén Marañón Romaric Duvignau Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg Sweden

ISBN: (数字)9798331529437

ISBN: (纸本)9798331529444

In today's digital era, privacy concerns have raised and the further deployment of 5G technology in recent years has amplified some of these concerns. While encryption is undoubtedly the cornerstone for protecting user privacy, packet trace analysis has been shown to be capable of identifying web and mobile applications even when the network traffic is encrypted. We further extend previous studies by presenting an accurate traffic classifier for 5G packet traces that does not need any access to the network. Our novel classification method is based exclusively on traffic patterns and does not require any information from the network layer to function. We perform a preliminary experimental comparison study for the classification task with three machine learning models and eight popular mobile applications. Our best model reaches an accuracy of up to 87% in classifying one minute of captured 5G encrypted traffic. This prompts us to question if necessary measures need to be considered at the link layer so to alleviate to leak such information.

关键词： Privacy Accuracy 5G mobile communication Prevention and mitigation Telecommunication traffic Machine learning Traffic control Mobile applications Virtual private networks Testing

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Understanding User Experiences and Expectations Toward Patient Appointment Systems

Understanding User Experiences and Expectations Toward Patie...

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作者： Yibin Huai Computer Science and Engineering Department Chalmers University of Technology

Patient appointment systems are automated reservation systems which allow people to book healthcare services,such as doctor appointments or outpatient appointments online or in *** many cases,patient appointment systems are attached as a function in the websites of *** a kind of direct-to-user healthcare technology which build interactions with patients,the experiences the systems created can affect patients' emotion status and health ***,to investigate how user experience could be improved and how positive experience could be created through Human computer Interaction(HCI) and user experience design,Clincare,a prototype healthcare website making users feel supportive was *** characterize users' experience and expectations towards patient appointment systems,user experience study was then conducted using the *** results revealed 4aspects which could significantly influence participants' experience and emotions:Information Display,Aesthetics,Workflow,and Context of *** on the result,4design implications were proposed to inform future design works of patient appointment systems.

关键词： Human computer Interaction Patient Appointment System User Experience Study Designing User Experience Interaction Design

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Practical Software Development: Leveraging AI for Precise Cost Estimation in Lump-Sum EPC Projects

Practical Software Development: Leveraging AI for Precise Co...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Rimma Dzhusupova Mina Ya-alimadad Vasil Shteriyanov Jan Bosch Helena Holmström Olsson Engineering McDermott The Hague The Netherlands Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Computer Science and Media Technology Malmö University Malmö Sweden

ISBN: (数字)9798350330663

ISBN: (纸本)9798350330670

In the engineering, Procurement, and Construction (EPC) sector, accurate cost estimations during the tendering phase are crucial for maintaining competitiveness, especially with constrained project schedules and rising labor expenses. Typically, these estimations are labor-intensive, relying heavily on manual evaluations of engineering drawings, which are often shared in PDF format due to intellectual property concerns. This study introduces an innovative solution tailored for the energy industry, utilizing Artificial Intelligence (AI) - primarily deep learning (DL) and machine learning (ML) techniques - to streamline material quantity estimation, thereby saving engineering time and costs. Built on empirical data from a large EPC company operating in the energy sector, AI-based product development experiences, and academic research, our approach aims to enhance the efficiency and accuracy of engineering work, promoting better decision-making and resource distribution. While our focus is on enhancing a particular activity within the case company using AI, the method's broader applicability in the EPC sector potentially benefits both industry professionals and researchers. This study not only advances a practical application but also provides valuable insights for those seeking to develop AI -driven solutions across various engineering disciplines.

关键词： Procurement Industries Deep learning Costs Accuracy Decision making Estimation

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Robust Detection of Line Numbers in Piping and Instrumentation Diagrams (P&IDs)

Robust Detection of Line Numbers in Piping and Instrumentati...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Vasil Shteriyanov Rimma Dzhusupova Jan Bosch Helena Holmström Olsson Engineering McDermott The Hague Netherlands Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Computer Science and Media Technology Malmö University Malmö Sweden

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

The success of any engineering, Procurement, and Construction (EPC) project depends on the engineering deliverables developed during project execution. An important deliverable is the Line List document, produced by extracting pipeline numbers from Piping and Instrumentation Diagrams (P&IDs). As the creation of this document is time-consuming, the automation of this process could reduce manual engineering work. However, the complexity of the P&IDs renders traditional computer vision approaches unsuitable. Therefore, deep learning text detection could be utilized to achieve this task. This study assessed the applicability of text detection methods for automating pipeline number information extraction in P&IDs. Our findings indicate that the methods previously used to detect text on P&IDs have limitations in accurately capturing the entire line numbers. Furthermore, we propose a line number detection method achieving a recall rate of over 90% on our evaluation data, consisting of P&IDs from diverse industrial projects. Thus, we demonstrate our method's generalizability to different line number formats and its potential for industrial application. Moreover, the proposed method can be adapted to other types of engineering drawings beyond P&IDs. Thus, it could be used in additional applications for digitizing engineering drawings.

关键词： Procurement Costs Automation Shape engineering drawings Instruments Pipelines Text detection Manuals Portable document format

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Unraveling the Impact of Density and Noise on Symbol Recognition in engineering Drawings

Unraveling the Impact of Density and Noise on Symbol Recogni...

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International IEEE Conference on Intelligent Systems, IS

作者： Vasil Shteriyanov Rimma Dzhusupova Jan Bosch Helena Holmström Olsson Engineering McDermott The Hague The Netherlands Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Computer Science and Media Technology Malmö University Malmö Sweden

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

Applied Artificial Intelligence (AI) in engineering is gaining significant traction. AI object detection methods can be applied in the engineering industry to extract information from engineering drawings, offering immense benefits to engineers. A promising application of AI in industrial engineering is symbol recognition applied to engineering drawings. However, these drawings often exhibit areas with a high density of symbols, as well as noise in the form of markups, indicating revisions. These factors could cause symbol misclassification or omission, impacting applications reliant on accurate symbol recognition. This study evaluates the accuracy of a symbol recognition model on engineering drawings called Piping and Instrumen-tation Diagrams (P &IDs) exhibiting varying levels of density and markups causing noise. Despite the assumption that density poses a challenge for accurate symbol recognition in engineering drawings, our study reveals that density has no significant impact on recognition performance when a dense detector is employed. In addition, we quantitatively show that markup-induced noise on engineering drawings negatively influences recognition accuracy. Finally, we provide recommendations regarding the applicability of symbol recognition in engineering applications. The study's findings and recommendations apply to any P &IDs, regardless of the standard used, as they were evaluated on various worldwide projects. Moreover, the research not only contributes to the advancement of symbol recognition on P&IDs, but also can be applied to other types of engineering drawings. Thus, it holds the potential for enhancing symbol recognition in various real-world industrial applications and research.

关键词： Industries Accuracy Shape Reviews engineering drawings Noise Symbols Object detection Detectors Standards

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A Move Forward: Exploring National Identity Through Non-linear Principal Component Analysis in Germany

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Quality and Quantity 2023年第1期57卷 885-903页

作者： Bruinsma, Bastiaan Mußotter, Marlene Department of Computer Science and Engineering Chalmers University of Technology Göteborg 412 96 Sweden University of Passau Dr. Hans-Kapfinger-Straße 14b Passau 94032 Germany

In research on national identity, scholars have developed a wide variety of approaches to measure and better understand this ubiquitous yet complex concept. To date, most of these approaches have been theory-driven, while only a very few have been data-driven. In this article, we aim to contribute to the latter by introducing a new data-driven method that has not been applied yet—that of non-linear principal component analysis (NLPCA). In contrast to other commonly used methods such as factor analysis, NLPCA distinguishes itself by making relatively few assumptions about the data and by allowing for greater flexibility when discovering underlying dimensions of such a complex concept as national identity. Drawing on the 2013 ISSP National Identity module, our analysis focuses on the case of Germany, also taking into account Western and Eastern Germany. Running an NLPCA, we find four dimensions that cover the multidimensionality of national identity: nationalistic attitudes, national pride and attachment, cosmopolitan beliefs, and membership criteria defining national belonging. This article contributes to the empirical debate on measuring national identity by suggesting a new and flexible methodological approach that better grasps the concept’s complexity and which we believe can move empirical research on national identity forward in and beyond Germany. © 2022, The Author(s).

关键词： Germany ISSP Measures National identity Non-linear principal component analysis

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