Modeling operating speed of mixed vehicular classes at horizontal curves on two-lane undivided rural highways
Abstract Accurate modeling of vehicle operating speeds at horizontal curves on two-lane undivided rural highways is vital for enhancing geometric design consistency and driver safety. This study develops vehicle-class-specific operating speed prediction models at critical curve segments—point of cur...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Discover Civil Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44290-025-00306-9 |
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| Summary: | Abstract Accurate modeling of vehicle operating speeds at horizontal curves on two-lane undivided rural highways is vital for enhancing geometric design consistency and driver safety. This study develops vehicle-class-specific operating speed prediction models at critical curve segments—point of curvature (PC) and middle of curve (MC)—based on extensive empirical data collected from twenty geometrically varied rural highway curves in Maharashtra and Telangana, India. Continuous speed profiles for two-wheelers (2 W), three-wheelers (3 W), four wheeler cars (4 W cars), and light commercial vehicles (LCV) were extracted using V-box instrumented vehicle tests, while spot speeds were obtained via video surveys. Revealed preference surveys (N = 1,574) provided behavioral insights and were analyzed using structural equation modeling (SEM) to link latent constructs—such as roadway perception, norms, and environmental conditions—with speed behavior. Stepwise multiple regression revealed that geometric parameters such as curve radius (R), curve length (L), chord length (LC), and preceding tangent length (PTL) positively influence operating speed, while longitudinal gradient (LG) and deflection angle (Δ) impose a negative impact, particularly for lighter vehicles. Comfort threshold values, derived from acceleration data, ranged from 0.331LG to 0.576LG, decreasing with smaller curve radii. The SEM analysis identifies key factors affecting driver comfort and behaviour on curves. Significant influences include sight distance, curve geometry, normative measures like speed compliance, and environmental conditions. Notably, sharp curve features and poor pavement reduce comfort, while adherence to regulations and better visibility enhance driver behaviour. These models can be utilized by rural highway designers (public works department) to find maximum speed reduction criteria for vehicle population plying from curve to tangent sections. |
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| ISSN: | 2948-1546 |