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Vehicles with advanced active safety technology can decrease the significant traffic accidents that can lead to death. This active safety frontier falls under primary safety in the European New Car Assessment Program (Euro NCAP) 2025 Roadmap, which has become one of the overall safety rating initiatives toward safer vehicles. Some frontier active safety technologies will be assessed, including autonomous emergency steering (AES) and autonomous emergency braking (AEB). However, the New Car Assessment Program in Southeast Asian Countries (ASEAN NCAP) only focuses on AEB technologies. Hence, this work discusses the existing papers on AES assessment, AES demand, AES control, AES system with Artificial intelligence, and AES testing methodology. Three articles from the industry discussing the AES function in passenger automobiles were found as a result of an article search using the Google search platform. Other terminologies like emergency steering control and emergency steering assist are used instead of AES. However, the principle remains the same. The three categories have been recognized from all of the document results: road adhesion condition, driver condition identification, and rear-end collision. However, only the rear-end collision situations are further investigated in this work to recognize the currently available approach used by previous studies. According to the review findings, just a few AEB intervention systems are now accessible, while AES technology is still in its early phases. That might explain the lack of exact evaluations and effective remedies. As a result, this research aims to offer evidence supporting the proposed methodology for assessing and evaluating AES in the ASEAN NCAP rating scheme. Besides that, this study can also help industries such as automakers and automotive vendors leverage the guidelines to fit the AES in their future models.

The effect of graphite (Gr) based magnetorheological elastomer (MRE) on resistance is experimentally evaluated in this research. Isotropic and anisotropic MRE samples are prepared by utilizing Gr as a filler in MRE fabrication. The physical, rheological and resistance properties of Gr-MRE are investigated and compared to those of typical or conventional MREs without Gr. Morphological aspects of Gr-MRE are characterized by field emission scanning electron microscope (FESEM), scanning electron microscope and energy dispersive x-ray spectroscopy, while rheological properties are evaluated using a rheometer. Subsequently, the resistance properties are investigated by using the designated test-rig. Based on the resistance evaluation, a curve describing the relationship of resistance (R) under different applied forces (F) and different magnetic fields (B) are established and plotted. Moreover, it is observed that the FESEM images shows the presence of Gr fractions, which contributes to the conductivity property of MRE. It is also observed that with the addition of Gr, the rheological and conductivity properties such as the storage modulus and resistance response are improved parallel with the increment of magnetic field. It is also demonstrated that the addition of Gr in MRE can contribute to the use of force detection in sensing devices. [ABSTRACT FROM AUTHOR]

In this paper, a new gender recognition framework based on fusion of features extracted from healthy people electromyogram (EMG) and heart rate variability (HRV) during stepping activity using a stepper machine is proposed. An approach is investigated for the fusion of EMG and HRV which is feature fusion. The feature fusion is carried out by concatenating the feature vector extracted from the EMG and HRV signals. A proposed framework consists of a sequence of processing steps which are preprocessing, feature extraction, feature selection and lastly the fusion. The results shown that the fusion approach had improved the performance of gender recognition compared to solely on EMG or HRV based gender identifier. [ABSTRACT FROM AUTHOR]

In this study, the development of motion planning and control for collision avoidance driver assistance systems is presented. A potential field approach has been used in formulating the collision avoidance algorithm based on predicted vehicle motion. Then, to realize the advanced driver assistance systems (ADAS) for collision avoidance, steering control system and direct yaw moment control (DYC) is designed to follow the desired vehicle motion. Performance evaluation is conducted in simulation environment in term of its performance in avoiding the obstacles. Simulation results show that the vehicle collision avoidance assistance systems can successfully complete the avoidance behavior without colliding. [ABSTRACT FROM AUTHOR]

Gender recognition is trivial for a physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) (Hsu et al.) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SVM). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient and effective for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Barani's work (90.34%), Nazarloo's work (92.50%), and other classifiers. [ABSTRACT FROM AUTHOR]