Earticle

This study aims to determine the optimal YOLO algorithm for object detection performance in PreScan simulation. YOLOv4, the current model used, is compared with five versions of YOLOv8 (v8n, v8s, v8m, v8l, v8x). The analysis focuses on simulation time, initial detection distance, and continuous detection distance to assess the suitability of each version for practical applications. YOLOv8n, designed for speed and efficiency, demonstrated significant improvements in reducing simulation time, while YOLOv8x showed exceptional performance in terms of detection accuracy and consistency. The various versions of YOLOv8 each present unique strengths, with YOLOv8n excelling in speed and YOLOv8x in accuracy. YOLOv8m offered a well-balanced approach, making it particularly suitable for scenarios where both speed and detection reliability are crucial. The study highlights the potential benefits of adopting YOLOv8 models in PreScan simulations, emphasizing their ability to enhance object detection performance in the tested scenario. While further testing is needed to confirm applicability across various conditions, the results suggest that each version has unique strengths that could be leveraged depending on specific requirements. Overall, YOLOv8m is identified as the optimal choice for balanced performance in the current test scenario, ensuring both effective simulation and reliable object detection capabilities.

In this paper, we proposed the intersection collision avoidance (ICA) algorithm for bicycle to vehicle (B2V) safety service and analyzed its performance by using ‘PreScan’ and ‘MATLAB’. As typical type accidents related with bicycles, we consider the bicycle to vehicle (B2V) communication. The derived analytical approach can explain the condition and effect of bicycle collisions. Furthermore, proposed algorithm has been confirmed by simulations. Consequently, the ICA developing methodology is verified to be used as a general tool to reduce the cost and the time consumption required for commercialization of safety services under IEEE 802.11p/wireless access in vehicular environments (WAVE) wireless networks.

In this paper, a novel approach of intelligent vehicle to interact and cooperate with other human driving vehicles is proposed at the freeway entrance ramp scenario. The system consists of a Safety Alert Module and Vehicle Control Module. The Safety Alert System module includes intention estimation and conflict judgment. A two dimension Hidden Markov Model (2DHMM) is used to estimate social vehicle’s driving intention in the intention estimation module. Then the conflict judgment module predicts the potential conflicts between the intelligent vehicle and social vehicle. Moreover, the hybrid state system (HSS) is introduced to control the intelligent vehicle while considering its decision making, states and dynamics. Co-simulation using PreScan and Simulink is conducted. The experiment results show that the intelligent vehicle performs well with a commendable social behavior in the freeway entrance ramp.

Purpose : To evaluate regional differences in relative metabolite ratios in the normal human brain by 1H MRspectroscopy (MRS), and compare the spectral quality obtained by the automated prescan method (PROBE) and themanual method. Materials and Methods : Localized 1H MRS was performed on a GE 1.5T SIGNA MRI/MRS system (version5.5) with active shielded gradients. For 20 normal volunteers aged 8-47 years, spectral parameters were adjustedby the auto-prescan routine provided by a PROBE package(N=34)and manually (N=33). Five regions of the human brainwere examined (N=PROBE,manual): frontal white matter(N=6,10), parietal white matter(N=8,9), basal ganglia(N=6,5),thalamus(N=4,5), and cerebellum(N=4,4). For all spectra, a STEAM localization sequence with three-pulse CHESS H2Osuppression was used, with the following acquisition parameters: TR=3.0 sec, TE=30 msec, TM=13,7 msec, SW=2500Hz,SI=2048 pts, AVG=48, and NEX=2. Results : A total of 61 reliable spectra were obtained by PROBE (28/34=82%success) and by the manual method (33/33=100% success). Regional differences in the spectral patterns of the fiveregions were clearly demonstrated by both PROBE and the manual methods. For prescanning, the manual method tookslightly longer than PROBE (3-5 mins and 2 mins,respectively). There were no significant differences in spectralpatterns and relative metabolic ratios between the two methods. However, auto-prescan by PROBE seemed to be veryvulnerable to slight movement by patients, and in three cases, an acceptable spectrum was thus not obtained.Conclusion : PROBE is a highly practical and reliable method for single voxel 1H MRS of the human brain; the twomethods of prescanning do not result in significantly different spectral patterns and the relative metaboliteratios. PROBE, however, is vulnerable to slight movement by patients, and if the success rate for obtainingquality spectra is to be increased, regardless of the patient's condition and the region of the brain, it must beused in conjunction with the manual method.