# Determining Factors Influencing Operating Speeds on Road Tangents
## 1 Introduction
The existing research on operating speeds has encompassed various types of roads, with single-carriageway and dual-carriageway roads being of particular interest. Moreover, operating speeds have been analyzed in multiple road segments, such as horizontal curves, vertical curves, tangents, and combinations of these. In studies examining factors influencing operating speed in horizontal curves across all road types, radius of horizontal curve has proven to be the most statistically significant variable [15; 16; 17; 18; 19; 20]. For instance, [PERSON] et al. (2018) [16] found that operating speeds significantly decrease when the curve radius is less than 300 m, and that vehicle speed stabilizes as the radius increases. Similarly, [PERSON] et al. (2016) [21] noted that a radius of horizontal curve greater than 400 m has a negligible impact on the operating speed. The existing research on tangent road sections is relatively limited compared to the studies conducted on horizontal curves. [PERSON] et al. (2005) [22] conducted a study in both urban and rural areas, identifying a strong correlation between posted speed limits and operating speed on tangents. Other parameters affecting operating speed included driveway density, median type, and the presence of parked vehicles and pedestrians. Notably, pedestrian presence was found to be inversely proportional to operating speed. Additionally, on rural tangents, lane width has been shown to proportionally increase operating speed. The Federal Highway Administration (FHWA) notes that wider lanes and shoulders result in faster operating speeds; for instance, methodologies in the Highway Capacity Manual predict an approximately 0.64 to 1.77 km/h increase in speeds on two-lane highways for every 0.3 m increase in lane width. [23]. [PERSON] et al. (2020) [15] conducted research across 251 locations in Oklahoma, developing three models to predict operating speed, including one for roads with higher speed limits (80-105 km/h), one for roads with lower speed limits (56-72 km/h), and a third for roads with varying speed limits, with the latter model proving most accurate. Among the most statistically significant variables were posted speed limits and pavement friction coefficients across all speed limit categories. Conversely, for roads with lower speed limits, only the posted speed limit proved to be statistically significant. Furthermore, the differences in predicting operating speeds can be attributed to varying driving behavior patterns. [PERSON] et al. (2006) [24] compared aggressive driving behavior across different nationalities and cultures, specifically between Finnish, British, Greek, Iranian, Dutch, and Turkish drivers. They found that Greek drivers engaged in aggressive violations more frequently and expressed greater anger and impatience towards other road users. British, Dutch, and Finnish drivers exhibited the least aggression, while Iranian and Turkish drivers fell between these groups. In light of the aforementioned considerations, it may be presupposed that driving behavior varies among nationalities and cultures, therefore influencing operating speed [25]. The existing studies on operating speeds on road tangents have identified several factors influencing operating speed. Research by [PERSON] et al. (2005) [22] found that driveway density, median type, and the presence of parked vehicles and pedestrians significantly affect vehicle speeds. In particular, pedestrian presence has been shown to inversely correlate with operating speeds, as drivers tend to reduce speed when pedestrian activity is high [21]. Furthermore, road design characteristics, such as lane width, was found to have an essential role in speed variations. Wider lanes have been associated with higher operating speeds, as drivers perceive them to be safer and less restrictive [15]. However, some studies, such as [PERSON] et al. (2005) [22], have reported that lane width does not always have a statistically significant impact on operating speed, suggesting that additional contextual factors may be at play.