New Consistency Model Based on Inertial Operating Speed Profiles for Road Safety Evaluation

Abstract

Road crashes are mainly caused by three concurrent factors: infrastructure, vehicles, and human factors. The interaction between infrastructure and human factors leads to the concept of geometric design consistency, which can be defined as how drivers' expectations and road behavior fit. This paper presents a new global consistency model based on the difference between the inertial operating speed profile (V i ) and the operating speed profile (V 85 ). The first is calculated as the weighted average speed of the previous road section and represents drivers' expectations, whereas the second represents road behavior. A set of 71 homogeneous two-lane rural road segments located in Italy were used in the calibration of the model. As a result, a safety performance function based on this new consistency model was proposed to estimate the number of crashes on an entire road segment. Finally, the new model was compared with previous global consistency models, concluding that the new consistency parameter better explains the phenomenon than the previous ones. Therefore, the new consistency model is a useful tool for engineers that allows estimation of the number of crashes and incorporates road safety into the geometric design of both new two-lane rural roads and improvements to existing highways.

Time-Based Calibration of the Inertial Operating Speed to Enhance the Assessment of the Geometric Design Consistency

“…Different consistency parameters were proposed considering several variables based on the difference between V i and V 85 (see 21 ). Figure 3 shows the speed differences between the speed profiles depicted in Figure 1.…”

“…Table 1 summarizes the proposed consistency parameters ( 21 ). All parameters are expressed in terms of speed.…”

“…This assumption makes sense, since the human mind tends to retain information as a function of time, not of distance covered. In fact, the authors calculated V i in terms of distance in a previous research (21), but timebased models shows a better goodness of fit (AIC of 547.01 Vs. 548. 15).…”

“…Therefore, the initial and final zones of the preceding section should not be considered in the same way when determining the inertial operating speed. In this regard, Llopis-Castelló et al ( 21 ) defined V i as the weighted average operating speed based on distance to develop a new global consistency model based on the difference between the inertial operating speed profile and the operating speed profile. As expected, this way of calculating V i showed better results than estimating this speed as the simple average of the operating speed.…”

Speed Distribution Prediction of Freight Vehicles on Mountainous Freeway Using Deep Learning Methods

“…However, the majority of existing studies on speed prediction modeling treat the input as static variables, instead of considering speed changing process in time series. Although a few studies took the geometric features of previous and oncoming elements into consideration [31][32][33], the models were not able to match the actual driving process when negotiating with the complexity of the road environment. Some researchers also conducted valuable comparative studies based on the classification of road geometric features and road scenarios [12,13], commonly with a great fitting performance, but not able to mimic actual driving process.…”