Introduction: Combined horizontal and vertical alignments are frequently utilized in mountainous interstates in Wyoming. The roll stability of trucks on these challenging terrain conditions is of great concern for transportation officials. The impact of curve characteristics combined with truck configurations has not been considered in the literature due to data availability issues related to the weight and Center of Gravity (CG) payload height of trucks.
Method: High-fidelity vehicle dynamics simulation modeling is employed to investigate the rollover propensity of trucks navigating curves of varying geometric design and truck characteristics. A multinomial regression model was then developed to further quantify the impact of these key factors and the effect of their interactions on rollover safety margins.
Results: It was shown that complying with the assigned speed limits of the curved roadways is not enough to navigate a curve without experiencing a rollover under some circumstances. The CG payload height and the operating speeds have the highest impact on the safety margins of a truck rollover. Steeper downgrades would amplify the impact of the gross weight of a truck. Tighter curves would also raise the impact of the truck configurations.
Conclusions: This study assessed the curve speed limits and revealed that the exciting approach to assigning safe speed limits should be modified according to the aforementioned factors. For the first time, findings from this study shed light on the direction and magnitude of the impact of the truck configurations coupled with curve features that contribute to truck rollover safety margins. Practical Applications: This study revealed the impact of truck configurations on the roll stability of trucks and pointed out critical cases that should be treated very cautiously by drivers. This assists transportation agencies in assigning more appropriate speed limits of curved roadways according to truck conditions.
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http://dx.doi.org/10.1016/j.jsr.2021.11.012 | DOI Listing |
Accid Anal Prev
January 2025
Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China; School of Transportation, Southeast University, Nanjing 211189, China. Electronic address:
Blind spot collisions are a critical and often overlooked threat to pedestrian safety, frequently resulting in severe injuries. This study investigates the impact of automated vehicles equipped with external human-machine interfaces (eHMIs) on pedestrian crossing behavior and safety, focusing on scenarios where AVs create mutual blind spots between pedestrians and adjacent traffic. A virtual reality experiment with 51 participants simulated crossing situations in front of yielding trucks with obstructed pedestrian visibility, featuring three eHMIs: 'Walk,' 'Don't Walk,' and 'Caution! Blind Spots'.
View Article and Find Full Text PDFTraffic Inj Prev
January 2025
School of vehicle and mobility, Tsinghua University, Beijing, China.
Objective: Previous research has established the effectiveness of active pretensioning seatbelts (APS), also termed motorized pretensioning seatbelts, in mitigating forward leaning and out-of-position displacement during pre-crash scenarios. In the Chinese market, APS trigger times are typically set later than those reported in the literature. This study investigates the real-world performance of APS systems with delayed trigger times under emergency braking conditions.
View Article and Find Full Text PDFMaterials (Basel)
November 2024
Doctoral School of Engineering and Technical Sciences, Rzeszow University of Technology, al. Powst. Warszawy 12, 35-959 Rzeszów, Poland.
Commun Eng
November 2024
Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA, USA.
The transition to electric vehicles is driving a fundamental shift in the automobile design process. Changes in constraints afforded by the absence of a combustion engine create new opportunities for modifying vehicle geometries. Current approaches to optimizing vehicle aerodynamics require a vast amount of computational studies and physical experiments, which are expensive when performing parameter sweeps over conceivable geometric configurations, suggesting the need for more efficient surrogate models to assist analysis.
View Article and Find Full Text PDFData Brief
December 2024
Department of Electrical Engineering, Chalmers University of Technology, Gothenburg 41296, Sweden.
A synthetic dataset of 12 LG M50 cells was generated using physics-based models. The model parameters for this commercial NMC 811/graphite-SiOx cell were taken from multiple sources in the literature. In particular, five degradation parameters were varied from their default values as parameter sensitivity analysis.
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