# Speed-Flow-Geometric Relationship for Urban Roads Network
###### Abstract  
Speed on the urban roads is significantly affected by the surrounding geometric and traffic parameters. Based on this fact, we ascertained the impact of the geometric and traffic parameters on the average travel speed of the urban roads network. Herein, 197 urban road segments in Johor (Malaysia) with diverse features were randomly selected. The average travel speed and volume of the traffic on these road segments were measured using the moving observer method (MOM). Meanwhile, these roads' features were recorded via the direct visual inspection. Various geometric (density of the traffic calming speed, right-turn driveway, access, and right-turn) and cross-sectional (median, number of lanes, and side friction) parameters were considered. First, 14 multilinear models constructed via multilinear regression analysis were developed for traffic volume scenarios (in veh/h and pcu/h). Then, 10 models were adopted to evaluate the geometric parameters' influence on the average travel speed for the selected roads. The results revealed a considerable impact of some geometric and traffic parameters on the average travel speed for the studied urban roads. Furthermore, the density of traffic calming speed, driveway, and intersection per 1 km of urban road segment one for each parameter was found to reduce the speed of the vehicles from 1.3 to 0.22 km/h. The combination of the road cross-section features such as median, number of lanes, and side friction strongly affected the observed speed variation. It is asserted that the developed model may facilitate the Malaysian urban roads network management to provide better traffic performance with higher mobility and safer roads design and planning, thereby offering a gateway toward sustainability. a +
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Several studies showed that due to the enhancement of the geometric and traffic features of the urban road facility, a gradual improvement of the speed-flow model occurred [10; 11; 12]. In addition, some of the reports on speed-flow relationship issues related to the urban roads focused on the congestion and capacity [12; 13]. The applications for these models were predetermined based on a few geometric parameters such as signal intersection [11], signal timing [14], road width [15; 16; 17; 18; 19], and spacing length between intersections [10]. Other speed-flow relationship models evaluated the impact of the geometric and traffic parameters considered as numerical coefficients [20; 21; 22; 23]. Nevertheless, all these studies confirmed that the geometric and traffic parameters improvement can positively influence the speed-flow relationship for the urban roads network. For instance, [PERSON] et al. [20] developed a speed-flow relationship model based on certain geometric parameters such as lane width, lateral clearance, and access point density. In addition, various other parameters such as pavement conditions, time of days, and heavy vehicles percentage on the average speed under adverse road weather conditions were considered to build a speed-flow model [22]. The inclusion of the pavement condition and heavy vehicles' percentages in the speed-flow model was shown to impact the travel speed at maximum. [PERSON] and [PERSON] [21] proposed a linear model among the average speed and vehicle classes of the motorcycles, light vehicles, and heavy vehicles. The speed-flow relationship was shown to be greatly affected by the motorcycle's percentage in the traffic stream. In addition, some other geometric and traffic parameters like number of lanes [24; 25], side friction [26; 27] and median [28; 29] were shown to appreciably influence the travel speed on the urban roads. Despite the strong influence of these parameters on the speed for the urban roads network they are seldom considered in the speed-flow relationship model development. On top, the parameters like traffic calming speed and right-turn driveways were never addressed in the speed-flow relationship models.