Identifying Expressway Accident Black Spots Based on the Secondary Division of Road Units

For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi'an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures.

Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data

Currently, several traffic conflict indicators are used as surrogate safety measures. Each indicator has its own advantages, limitations, and suitability. There are only a few studies focusing on fixed object conflicts of highway safety estimation using traffic conflict technique. This study investigated which conflict indicator was more suitable for traffic safety estimation based on conflict-accident Pearson correlation analysis. First, a high-altitude unmanned aerial vehicle was used to collect multiple continuous high-precision videos of the Jinan-Qingdao highway. The vehicle trajectory data outputted from recognition of the videos were used to acquire conflict data following the procedure for each conflict indicator. Then, an improved indicator Ti was proposed based on the advantages and limitations of the conventional indicators. This indicator contained definitions and calculation for three types of traffic conflicts (rear-end, lane change and with fixed object). Then the conflict-accident correlation analysis of TTC (Time to Collision)/PET (Post Encroachment Time)/DRAC (Deceleration Rate to Avoid Crash)/Ti indicators were carried out. The results show that the average value of the correlation coefficient for each indicator with different thresholds are 0.670 for TTC, 0.669 for PET, and 0.710 for DRAC, and 0.771 for Ti, which Ti indicator is obviously higher than the other three conventional indicators. The findings of this study suggest TTC often fails to identify lane change conflicts, PET indicator easily misjudges some rear-end conflict when the speed of the following vehicle is slower than the leading vehicle, and PET is less informative than other indicators. At the same time, these conventional indicators do not consider the vehicle-fixed objects conflicts. The improved Ti can overcome these shortcomings; thus, Ti has the highest correlation. More data are needed to verify and support the study.

Methodology of overhead power transmission line pylons technical state assessment with typical exploitation faults accounted

Structure safety estimation via the results of modal testing is widely used in building field. However, overhead power line pylons are so specialised that it is not possible to expand existing standards so that those could be employed to assess pylon conditions. These standards do not contain any information about the pylon eigenvalues, methodology of full-scaled experiment execution or criteria to differentiate pylons with respect to the extent of the structure defects occurred. This means that it is necessary to develop a dedicated approach to estimating the safety of this type of structures. The method proposed boasts an additional advantage, that is, it takes into account the operating defects that are typical for the type of structures under consideration. The point of this method is comparing the computed and experimentally determined natural frequencies of overhead power line pylons. This comparison enables us not only to detect the defect type present in the structure, but also to find whether it is located closer to the base of the structure or in the latticework on one of the sides. The paper presents the results of using our method for estimating the safety of intermediate towers for a 110 kV overhead power line as represented by the SV-5 segment and states the advantages of using our method when planning real-time inspection of structures, as well as for monitoring select towers constantly.

A Decision Architecture for Safety Computations

Accurately estimating safety is critical to pursuing non-defensive survival behaviors, including reproduction and feeding. Relatively little attention, however, has been paid to how the human brain computes safety. We conceptualize a model that consists of two components: threat-oriented evaluations that focus on threat value, imminence, and predictability, while self-oriented evaluations focus on the agent’s experience, strategies, and ability to control the situation. Our model points to the dynamic interaction between these two components as a mechanism of safety estimation. Based on a growing body of human literature, we hypothesize distinct regions of the ventromedial prefrontal cortex respond to threat and safety. We suggest safety is not the inverse of danger, but reflects independent computations that mediate defensive circuits and behaviors.

Study on Turbulence Intensity Behavior under a Large Range of Temperature Variation

The turbulence intensity (TI) is defined as the ratio of fluctuation from the standard deviation of wind velocity to the mean value. Many studies have been performedon TI for flow dynamics and adapted various field such as aerodynamics, jets, wind turbines, wind tunnel apparatuses, heat transfer, safety estimation of construction, etc.The TI represents an important parameter for determining the intensity of velocity variation and flow quality in industrial fluid mechanics. In this paper, computational fluid dynamic (CFD) simulation of TI alteration with increasing temperature has been performed using the finite volume method. A high-temperature—maximum 300 degrees Celsius (°C)—wind tunnel test rig has been used as theapparatus, and velocity was measured by an I-type hot-wire anemometer. The velocity and TI of the core test section were operated at several degrees of inlet temperatures at anair velocity of 20 m/s. The magnitude of TI has a relationship with boundary layer development. The TI increased as temperature increased due to turbulence created by the non-uniformities.