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EN
This article presents a modified method for determining the activation timing of airbags in vehicles, which incorporates the real-time position of the driver’s and passengers’ heads. The primary objective of this modification is to improve the precision of airbag deployment by introducing an additional parameter—namely, the actual head position of the vehicle occupants, monitored in real time. The use of cameras and advanced image processing algorithms enables continuous tracking of head positions. As a result, the airbag system can adjust its activation timing according to the current positions of the occupants during a collision, significantly enhancing protective effectiveness. The results show that reducing the distance of the head from the normalized position by 70 mm requires the airbag activation to be advanced by an average of 28%. The largest correction occurs at a speed of 23 km/h and reaches 30%, decreasing at higher speeds. Conversely, increasing the distance by 70 mm necessitates the activation to be delayed by an average of 22%, with a maximum correction of 23% also observed at 23 km/h. These differences arise from the variable deceleration profile during a crash, which is influenced by specific collision dynamics. Unlike the conventional “13-30” model, which assumes a fixed head-to-airbag distance, the new method accounts for actual variations in occupant positioning, thereby improving protective performance. The proposed system uses infrared cameras and a lidar unit to track reference points on the head, such as the center of the forehead and the chin. Based on the collected data, the system dynamically adjusts the airbag deployment timing, reducing the risk of head injuries. This method can be integrated with other safety systems, such as seatbelt pretensioners and adaptive headrests, and is particularly applicable in autonomous vehicles, for which occupant positions may deviate significantly from standard seating postures. Adaptive airbag deployment has the potential to become a new standard in enhancing road safety.
EN
This study presents calculations of relative carbon dioxide emissions for different types of passenger cars (internal combustion engine vehicles, plug-in hybrid electric vehicles, battery electric vehicles, and fuel cell electric vehicles). Using a model based on the life cycle assessment methodology, carbon dioxide equivalent emissions were determined for these vehicles, taking into account three scenarios of energy diversification for Poland from 2025 to 2040. Based on the research, it was concluded that the most environmentally friendly vehicles (in terms of carbon dioxide emissions) are fuel cell electric vehicles. The least environmentally friendly vehicles during operation are plug-in hybrid electric vehicles.
EN
The article presents a heuristic model used to evaluate the level of disorder in the synchronization of airbag operation with a moving phantom head during a frontal collision caused by a change in the longitudinal stiffness. The article describes three areas of research. The first presents the results of the strength tests of longitudinal models: reference and welded joint. Based on these, the relative stiffness decrease coefficient (SDC) of the longitudinal was determined. The second presents an analytical model of the airbag activation algorithm and the impact of SDC on its operation. The third determined the contact time of the phantom head with the airbag, taking into account the SDC. Based on the selected case study, a spatiotemporal analysis was conducted, indicating the level of disorder in the synchronization of the airbag with the moving phantom head due to the change in longitudinal stiffness.
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