Evaluation of the Application of Maximum Radius in Horizontal Curves Using Vehicle Dynamic Simulation
Author(s): |
Asame Sharf Aldeen
Ali Abdi Kordani Seyed Mohsen Hosseinian Mehdi Mehdi Nazar |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2022, v. 2022 |
Page(s): | 1-19 |
DOI: | 10.1155/2022/5237541 |
Abstract: |
Most road design standards recommend using a spiral curve for transitions. The main advantages of using this curve are the gradual increase in the centrifugal force, creating a suitable space for presenting superelevation, and providing a correct perception of the curve for the driver. In this research, vehicle dynamic simulation software CarSim and TruckSim is used to assess the forces imposed on the vehicles. In this regard, 360 scenarios are considered for sedans, SUVs, and trucks, which consist of variations of the road geometry (simple or spiral horizontal curve), curve radius, and type and speed of the vehicle. In addition, the regression analysis is performed to examine the relationships between the lateral acceleration (as a dependent variable) and the vehicle speed, curve radius, and vehicle type (as independent variables). The results indicate that in all cases, safety in the spiral horizontal curve is greater than that in the simple horizontal curve, and the maximum side friction factor, lateral acceleration, roll rate, roll angle, yaw rate, and lateral distance in the simple horizontal curve are higher than those in the spiral horizontal curve. Moreover, the difference percentage of the side friction factor, lateral acceleration, yaw rate, and lateral distance between the simple and spiral horizontal curves is the highest in SUVs, followed by sedans and trucks, while the difference percentage of the roll rate and roll angle is the highest in sedans, followed by SUVs and trucks. The results of regression analysis illustrate that the coefficient of determination (R2) in the proposed model is 0.972, 0.964, and 0.981 for sedans, SUVs, and trucks, respectively, indicating the strong relationships between the dependent and the explanatory variables as well as the capability of the model to cover the data. |
Copyright: | © Asame Sharf Aldeen et al. et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10663870 - Published on:
09/05/2022 - Last updated on:
01/06/2022