Situational Hazard Recognition and Risk Assessment Within Safety-Driven Behavior Management in the Context of Automated Driving

Hagele, Georg; Sarkheyli-Hägele, Arezoo

doi:10.1109/cogsima49017.2020.9216183

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Many studies concentrated on human factors, some focused on one specific manner, while others focused on combined manners. [8] conducted a study to reduce the traffic risk by supporting decision making and action selection through risk assessment of the non-predicted environment. [9] studied the drivers' behaviors in emergency situations due to man-made or naturally occurring disasters including adverse weather conditions or freeway incidents like vehicle crashes.…”

Section: Literature Reviewmentioning

confidence: 99%

Adverse weather impact on driver performance in the UAE

et al. 2022

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Road traffic accident is a significant cause of death around the world. Many factors cause accidents, such as demographic factors, humane factors, road design factors, and weather factors. This paper will investigate the adverse weather impact on driver performance by analyzing the impact of weather conditions on drivers' behaviors. Statistical analysis was conducted using one-way ANOVA test, correlation analysis, and Artificial Neural Network. The data was collected using a questionnaire for the people live in the United Arab Emirates. The survey includes two parts; the first part is about driver characteristics (Gender, Age, Nationality, Marital status, Education level, Monthly income, and Driver experience). The second part contains three questions related to the reaction and attitude of drivers due to bad weather conditions. The results showed that 45% of drivers involved in accidents during bad weather conditions although the majority (more than 75%) of them reduced the speed during the bad weather conditions. Overall, more research is needed to be done to evaluate the dust impact on driver performance as well as using real traffic accident data and compare it with this study to reach a solid conclusion and recommend the best solutions to improve traffic safety.

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Section: Literature Reviewmentioning

confidence: 99%

Adverse weather impact on driver performance in the UAE

et al. 2022

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“…This article presents an advanced technique known as Safety-Driven Behavior Control that centers on situation reenactment and the subject of the depiction of data in its sub-capacities in the light of situational hazards. [8] The steady properties of fluffy thinking and neural organizations are combined with FCM. A decent learning method for unaided instructing might be applied to deliver the disadvantages and to expand the presentation of FCM.…”

Section: Literature Reviewmentioning

confidence: 99%

Experimental Analysis using Deep Learning Techniques for Safety and Riskless Transport - A Sustainable Mobility Environment for Post Covid-19

Selvakarthi¹,

Sivabalaselvamani²,

Ashwath³

et al. 2021

2021 6th International Conference on Inventive Computation Technologies (ICICT)

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Safety living in the society is the greatest challenge due to COVID-19. Transportation has a crucial role in ensuring the safety of society. To bring back the normality of the society after COVID-19, proper wearing of a mask and strict distancing can play a vital role in the solutions of environment and health. Hence the development of smart and riskless transport with active surveillance of passengers to enforcing the wear of mask and maintaining the social distance can be attained through deep learning algorithms (thermal imaging and sensor technologies). In this proposed work, the various image patterns have analyzed using deep learning algorithms. Passengers' health and count inside the bus are measured using sensor technologies. Hence the development of this model has capable of ensuring social distancing among the people and avoiding the crowd for riskless transport.

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“…The Chinese Ministry of Education has released a series of policies on teaching quality and reform, calling for the construction of high-quality online open courses. Thanks to the efforts of domestic colleges, a total of 2,000 high-quality online open courses have gone live, all are freely accessible by the public [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Recognition of Teaching Features and Behaviors in Online Open Courses Based on Image Processing

Li¹,

Chai²

2021

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High-quality online open courses have a wide audience. To further improve the quality of these courses, it is critical to analyze the teaching behaviors in class, which are the manifestation of the overall quality of the teacher. Considering the popularity of image processing-based behavior recognition in many disciplines, this paper explores deep into the teaching features and behaviors in online open courses based on image processing. Firstly, a coding scale was designed for teaching behaviors in online open courses. Next, the principle of optical flow solving was explained for teaching video images. Then, a teaching behavior feature extraction model was established based on dual-flow deep CNN, and used to extract the key points of teacher body and the behavior features of the teacher. After that, a teaching behavior recognition method was developed combining histogram of oriented gradients (HOG) and support vector machine (SVM) to accurately allocate the teaching features and behaviors to the corresponding teaching links. Finally, the proposed model was proved effective through experiments. Based on the recognized teaching behaviors, the frequency and duration of such behaviors were subject to comparative analysis, revealing the teaching features in high-quality online open courses.

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Situational Hazard Recognition and Risk Assessment Within Safety-Driven Behavior Management in the Context of Automated Driving

Cited by 6 publications

References 12 publications

Adverse weather impact on driver performance in the UAE

Adverse weather impact on driver performance in the UAE

Experimental Analysis using Deep Learning Techniques for Safety and Riskless Transport - A Sustainable Mobility Environment for Post Covid-19

Recognition of Teaching Features and Behaviors in Online Open Courses Based on Image Processing

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