Influence of adverse weather on drivers’ perceived risk during car following based on driving simulations

Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers'perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment.An expressway road scenario was built in a driving simulator.Eleven types of weather conditions,including clear sky,four levels of fog,four levels of rain and two levels of snow,were designed.Furthermore,to simulate the carfollowing behavior,three car-following situations were designed according to the motion of the lead car.Seven car-following indicators were extracted based on risk homeostasis theory.Then,the entropy weight method was used to integrate the selected indicators into an index to represent the drivers'perceived risk.Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk,and the coefficients were considered as indicators.The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior.Drivers'perceived risk tends to increase with the worsening weather conditions.Under conditions of extremely poor visibility,such as heavy dense fog,the measured drivers'perceived risk is low due to the difficulties in vehicle operation and limited visibility.

Study of The Technical Index of Online Learning Behavior Analysis of Nursing Majors on The Superstar Platform Based on The Kirkpatrick Evaluation Model

Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.

Room-temperature chlorine gas sensor based on CdSnO_(3) synthesized by hydrothermal process

The perovskite-structure CdSnO_(3) was obtained by calcinating CdSnO_(3)·3H_(2)O precursor at 550℃,which was synthesized by hydrothermal process at 170℃for 16 h.The phase and microstructure of the obtained CdSnO_(3) powders were characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM)and transmission electron microscopy(TEM).The CdSnO_(3) powders exhibit uniformly cubic structure with side length of about 100 nm.The effects of working temperature and concentration of detected gas on the gas response were studied.The selectivity of chlorine gas against other gases and response-recovery time of the sensor were also investigated.The results reveal that the CdSnO_(3) gas sensor has enhanced sensing properties to 1-10 ppm chlorine gas at room temperature;the value of gas response can reach 1338.9 to 5 ppm chlorine gas.Moreover,the sensor shows good selectivity and quick response behavior(23 s)to chlorine gas,indicating its application in detecting chlorine gas at room temperature in the future.

A new meshless approach for bending analysis of thin plates with arbitrary shapes and boundary conditions

An efficient and meshfree approach is proposed for the bending analysis of thin plates.The approach is based on the choice of a set of interior points,for each of which a basis function can be defined.Plate deflection is then approximated as the linear combination of those basis functions.Unlike traditional meshless methods,present basis functions are defined in the whole domain and satisfy the governing differential equation for plate.Therefore,no domain integration is needed,while the unknown coefficients of deflection expression could be determined through boundary conditions by using a collocation point method.Both efficiency and accuracy of the approach are shown through numerical results of plates with arbitrary shapes and boundary conditions under various loads.

Evaluation of fog warning system on driving under heavy fog condition based on driving simulator

Purpose–Heavy fog results in low visibility,which increases the probability and severity of traffic crashes,and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers.This paper aims at exploring the effects of dynamic message sign(DMS)of fog warning system on driver performance.Design/methodology/approach–First,a testing platform was established based on driving simulator and driver performance data under DMS were collected.The experiment route was consisted of three different zones(i.e.warning zone,transition zone and heavy fog zone),and mean speed,mean acceleration,mean jerk in the whole zone,ending speed in the warning zone and transition zone,maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected.Next,the one-way analysis of variance was applied to test the significant difference between the metrics.Besides,drivers’subjective perception was also considered.Findings–The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone.Besides,when drivers enter a heavy fog zone,DMS can reduce the tension of drivers and make drivers operate more smoothly.Originality/value–This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform.The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

Technology acceptance comparison between on-road dynamic message sign and on-board human machine interface for connected vehicle-based variable speed limit in fog area

Purpose–Connected vehicle-based variable speed limit(CV-VSL)systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur.The purpose of the speed limit is to make the driver’s driving behavior more consistent,so as to improve traffic safety and relieve traffic congestion.The on-road dynamic message sign(DMS)and on-board human–machine interface(HMI)are two types of warning technologies for CV-VSL systems.This study aims to analyze drivers’acceptance of the two types of warning technologies in fog area and its influencing factors.Design/methodology/approach–This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator.The DMS and on-board HMI provided the driver with weather and speed limit information.In all,38 participants participated in the experiment and completed questionnaires on drivers’basic information,perceived usefulness and ease of use of the CV-VSL systems.Technology acceptance model(TAM)was developed to evaluate the drivers’acceptance of CV-VSL systems.A variance analysis method was used to study the influencing factors of drivers’acceptance including drivers’characteristics,technology types and fog density.Findings–The results showed that drivers’acceptance of on-road DMS was significantly higher than that of on-board HMI.The fog density had no significant effect on drivers’acceptance of on-road DMS or on-board HMI.Drivers’gender,age,driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently.This study is beneficial to the functional improvement of on-road DMS,on-board HMI and their market prospects.Originality/value–Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems.However,there were rare studies focused on the drivers’attitude toward using which was also called as acceptance of the CV-VSL systems.Therefore,this research calculated the drivers’acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM.Furthermore,variance analysis was conducted to explore whether the factors such as drivers’characteristics(gender,age,driving year and driving personality),technology types and fog density affected the drivers’acceptance of the CV-VSL systems.