Fast Functional Safety Verification for Distributed Automotive Applications During Early Design Phase

Xie, Guoqi; Zeng, Gang; Liu, Yan; Zhou, Jia; Li, Renfa; Li, Keqin

doi:10.1109/tie.2017.2762621

Cited by 59 publications

(26 citation statements)

References 20 publications

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“…Risk matrix is established to define the influence level of knowledge transfer risks and occurrence probability [26]. Missing response-time constraint (i.e., real-time constraint, timing requirement, and deadline) is considered a typical systematic failure of risk control [43]- [44]. Szulanski et al demonstrate that the choice of wise opportunity can reduce knowledge transfer risk by using empirical methods [45].…”

Section: B Control Methods Of Knowledge Transfer Risksmentioning

confidence: 99%

Risk Control for Knowledge Transfer in the Big Data Environment

Lee

Yang

et al. 2024

IEEE Access

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Firms need to continuously carry out product innovation to survive in dynamic market. In the big data environment, most firms, especially internet firms, realize new product innovation by taking imitation innovation as a stepping stone leading to independent innovation. Knowledge transfer, one of the main methods that firms acquire knowledge from external environment for imitation innovation, is a complex process of multiple knowledge transfer among different organizations and subject to various risks. Thus, it is necessary to understand knowledge transfer risks in the big data environment and help firms to carry out effective knowledge transfer in the process of new product innovation. Based on the influence factors of knowledge transfer risks and development process of innovation, a theoretical framework for risk control of knowledge transfer in the big data environment is proposed and a risk control model of knowledge transfer is presented. The model can be used to determine the maximum profit of a new product, the optimal time of knowledge transfer, and the update time of independent innovation knowledge in the big data environment. The results of simulation experiments are in line with the actual economic situation, and the model is valid. INDEX TERMS Big data, knowledge transfer, risk control, independent innovation, imitation innovation I. INTRODUCTION A. BACKGROUND VOLUME 4, 2016

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Section: B Control Methods Of Knowledge Transfer Risksmentioning

confidence: 99%

Risk Control for Knowledge Transfer in the Big Data Environment

Lee

Yang

et al. 2024

IEEE Access

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“…Past studies on safety issues of freeway exit ramp areas were focusing on crash risks evaluation and safety evaluation. In general, risk refers to the combination of probability of occurrence of harm and the severity of that harm, and safety refers to the absence of unreasonable risk [10]- [12]. These studies were conducted by developing a number of crash prediction models based on count data modeling technique and discrete choice modeling technique [13], [14].…”

Section: Literature Review a Safety Studies On Freeway Exit Rampmentioning

confidence: 99%

Exploring Risk Factors With Crashes by Collision Type at Freeway Diverge Areas: Accounting for Unobserved Heterogeneity

Guo

Liu

et al. 2019

IEEE Access

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The objective of this paper is to evaluate the impact of various risk factors on traffic crashes presenting different collision types at freeway diverge areas. Three-year period crash data from 367 freeway diverge areas were obtained. Three types of collisions, including rear-end, sideswipe, and angle collisions, were considered. A random parameters multivariate Poisson-lognormal (RP-MVPLN) model was developed to accommodate both correlations between crashes across collision type and the unobserved heterogeneity across observations. For the performance comparison, an MVPLN was developed and compared with the RP-MVPLN model under the Bayesian framework. The result showed that the RP-MVPLN model outperformed the MVPLN model, which highlighted that accounting for the unobserved heterogeneous effects of risk factors could improve the model fit. The model estimation result showed that the risk factors, as well as their impacts on different collision types, were different. The mainline annual average daily traffic (AADT), the lane-balanced design, and the number of lanes on the mainline were found to be significantly associated with all types of collisions, whereas the deceleration lane length and road surface type only affected rear-end crashes. The exit ramp length and ramp AADT had significant impact on rear-end crashes and sideswipe crashes, but they did not affect angle crashes. The speed limit was negatively related with rear-end crashes and angle crashes, while it had no impact on sideswipe crashes. Three risk factors, which are the mainline AADT, ramp AADT, and speed limit, were found to have significant heterogeneous effects on crashes across observations. INDEX TERMS Collision type, freeway diverge area, random parameters, multivariate model, full Bayesian estimation.

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“…With the rapid development of embedded systems, MC systems applications are more and more widely used. Typical applications include cyber-physical systems (CPSs), automotive systems, 99 grids and so on. We will introduce some main applications in MC systems below.…”

Section: Speci¯c Applications In MC Systemsmentioning

confidence: 99%

A Review of Recent Techniques in Mixed-Criticality Systems

Chai

Zhang

Sun

et al. 2019

J CIRCUIT SYST COMP

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Unlike traditional embedded systems that almost have only one criticality level, many complex embedded systems nowadays are mixed-critical and are more and more widely used. There has been a lot of research on mixed-criticality (MC) systems. In this paper, we present a survey on the MC systems on these research. First, we discuss the exaltation of the schedulability of MC systems. As improving schedulability may lead to quality-of-service (QoS) reduction of MS systems. Therefore, we investigate the approaches to solve this problem. Improving QoS of MS systems may inevitably increase the energy consumption. Then, we introduce the researches that take the energy efficiency as a design requirement of MC systems. Few MC systems regard fault-tolerance as the design requirement, thus, we extensively investigate fault-tolerance of MC systems. In addition, we introduce some of the main applications for MC systems.

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Fast Functional Safety Verification for Distributed Automotive Applications During Early Design Phase

Cited by 59 publications

References 20 publications

Risk Control for Knowledge Transfer in the Big Data Environment

Risk Control for Knowledge Transfer in the Big Data Environment

Exploring Risk Factors With Crashes by Collision Type at Freeway Diverge Areas: Accounting for Unobserved Heterogeneity

A Review of Recent Techniques in Mixed-Criticality Systems

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