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Browse AllThis SAE Recommend Practice establishes for passenger cars, light trucks, and multipurpose vehicles with GVW of 4500 kg (10000 pounds) or less, as defined by the EPA, and M1 category vehicles, as defined by the European Commission:
This specification covers an aluminum alloy in the form of sheet from 0.063 to 0.249 inch (1.60 to 6.30 mm) in nominal thickness (see 8.6).
This specification covers a low-alloy steel in the form of sheet, strip, and plate 4.00 inches (101.6 mm) and under in thickness.
This specification covers a copper-zinc alloy (brass) in the form of sheet, strip, and plate (see 8.6).
This specification covers a magnesium alloy in the form of investment castings (see 8.6).
This procedure describes a method of measuring the resistance to wet color transfer of materials such as textiles, leather, and composites.
This SAE Aerospace Recommended Practice (ARP) provides the user with standardized guidelines for the measurement of effective intensity of short pulse width strobe anticollision lights for aircraft in the laboratory, in maintenance facilities, and in the field. A common source of traceability for calibration of the measurement systems, compensation for known causes of variation in light output such as the use of colored lenses, and recommendations which minimize sources of errors and uncertainties are included in this document. Estimates of uncertainty and error sources for each class of measurement are discussed.
Despite remarkable advances in vehicle technology - enhancing comfort, safety, and automation – productivity of transportation over the road continues to decline. Stop-and-go driving remains one of the most persistent inefficiencies in modern mobility systems, leading to greater travel delays, energy waste, emissions, and accident risk. As vehicle volumes rise, these effects compound into systemic challenges, including driver frustration, unstable flow dynamics, and elevated greenhouse gas (GHG) emissions. To address these issues, an extensive data-driven evaluation was performed characterizing the underlying causes of traffic instability and uncovering hidden behavioral parameters influencing traffic flow. This research led to the identification of a previously unrecognized metric - the Driver Comfort Index (DCI) - which quantifies an inter-vehicle spacing behavior that reflects intrinsic human driving behavior. Building on this discovery, mixed traffic is explored to identify its
This paper proposes HaloBus, an innovative, edge-computing solution designed to mitigate this risk by detecting student boarding and exiting in real time using lightweight AI based methods. A persistent challenge in elementary school transportation is the issue of missing students after they exit their buses, which disproportionately impacts low-income households. Current safety systems place the burden of implementation on individual households, often requiring independent methods. Common methods include applications on a personal device or a small tracker. However, not everyone can afford these options, and ensuring child safety is a primary concern for parents and caregivers. That is why HaloBus was invented. The system employs YOLOv5us—an Ultralytics-enhanced, anchor-free, split-head architecture that offers a superior accuracy speed trade-off. By providing real-time, on-device alerts, HaloBus enables immediate intervention to prevent a student from being left behind, thereby