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To improve the efficiency of accident treatment on mountain highways and reduce the degree of disruption from traffic accidents, the grading method of the ellipse-like radiation range of traffic accident impact is proposed. First, according to the propagation law of traffic accidents, the general function of mountain highways affected by traffic accidents was constructed based on the Gaussian plume model. Then, based on the gravity field theory, the influence of the accident source point on the accident road was analyzed in the aftermath of a supposed accident. Additionally, considering the cascading failure of the road network, the influence of the accident-intersecting roads was demarcated by the cascading failure load propagation function. Based on this analysis, the ellipse-like radiation range models of traffic accidents on the accident road and the intersecting roads were proposed, respectively. Next, the adjustment parameter was further introduced to incorporate the different levels of influence of traffic accidents on the surrounding road network into the model, and the grading impacts of the accident on the potentially utilized opposite lane were discussed. Finally, according to the queuing theory model, simulation design, and portability analysis, the accuracy of the ellipse-like radiation range grading model was verified. The research results show that, compared with queuing theory and simulation results, the error of the grading model of the ellipse-like radiation range affected by traffic accidents was within a reasonable range; that is, the model can reasonably quantify the difference of traffic accident propagation on the accident road and the intersecting roads. Moreover, the heterogeneity of traffic accident propagation was verified by taking the non-occupied opposite lanes as an example. The grading method of influence radiation range utilized for traffic accidents on mountain highways can quickly provide corresponding auxiliary decision support for accident rescue within varying influence ranges.

Travelers always exhibit bounded rationality due to limited perception. Based on the theory of bounded rationality, switching thresholds under different patterns of information are analyzed in this paper. An experiment platform including four scenarios, such as historical descriptive information, real-time descriptive information, historical travel time information and real-time travel time information is designed to obtain the participants’ travel preference and route choice behavior. The relationship among route switching behavior, perceived travel time difference and travelers’ preference is analyzed based on experiment’s results. The Probit regression method is utilized for calibrating the switching threshold under different patterns of information. The results prove the dissimilarity of switching thresholds in diverse patterns of information. The switching threshold under real-time information is lower than that under historical information. The estimated results of risk parameters prove that the traveler has a slight tendency to pursue risk. The method proposed in this paper can effectively quantify the degree of bounded rationality.

It's clinically relevant to reduce the radiation dose to children while ensuring their positron emission tomography/computed tomography (PET/CT) image quality. The optimal protocol for whole-body PET/CT imaging in children (non-model) has been less studied. In this study, we investigated the optimal protocol for PET/CT imaging of pediatric oncology by analyzing the radiation dose and image quality in18F-fluoro-2-deoxy-D-glucose (One hundred children with tumors who underwentNinety-seven images in CT and 57 images in PET were included. The best quality of CT images was in group K (120 kV/40-59 mA/8); there are 9 groups had good image quality and lower dose length product (DLP) than group K (SD ±10), while the difference in DLP between groups was large. The Kruskal-Wallis (K-W) test showed that the difference in image quality between the 9 groups was not statistically significant. The best PET image quality was in group i [0.15 (mCi/kg)/180 s]; there are four groups had good image quality and lower EDThe optimal protocols for CT scanning and PET imaging in this experiment were group H (80 kV/40-59 mA/14) and group g [0.08 (mCi/kg)/180 s], respectively.

At present, there is less attention paid to the relationship between the frequency of travel and built environment, especially in households. In this paper, some of the determining factors in the frequency of daily cycling per household were explored based on the data from 2018 Daily Trip Survey in Xianyang, China. Then a two-level linear model was construct to identify the determining factors in the frequency of per capita daily cycling of household. According to the research results, 22.8% of the differences in the per capita cycling frequency of household are due to the differences between communities. In terms of community factors, the densities of road networks and educational facilities delivered a significantly positive impact on the per capita daily cycling frequency of family; on the contrary, the densities of medical facilities, intersections and POI delivered a significantly negative impact. Per capita cycling frequency varies considerably between households. For instance, the number of bicycles owned and the number of school-age children have a significantly positive impact on the per capita daily cycling frequency of family. However, car ownership, household income and occupation composition impose a significantly negative impact. The findings of this study would benefit the transportation engineers and planners who are keen to boost the use of active means of transportation for residents.

Drivers' route switching behavior shows obvious difference when they face various traffic conditions. The article studies the drivers' route switching behavior based on group classification. Questionnaire combining SP survey and RP survey is carried out to collect the drivers' route choice behavior under the influence of individual attributes, daily travel characteristic and traffic conditions. Latent Class Model (LCM) is used to analyze the behavior characteristic. According to the goodness of models, drivers are divided into three categories. Drivers of sensitive pattern will switch route easily which is represented by young people with shorter driver-age. In contrast, drivers of unresponsive pattern will not switch routes easily and the pattern is represented by elder people with longer driver-age. Based on the drivers' classification results, ordinal logistic model is established. According to the odds ratio of each variable, we find that, age, driver-age, nature of drivers, and travel frequency all affect drivers' route switching behavior.

Bike-sharing is widely recognized as an eco-friendly mode of transportation and seen as one of the solutions to the problem of air pollution and congestion. With the emphasis on sustainability in transportation, bike-sharing systems is an emerging topic of urban transport and sustainable mobility related research. Existing studies mainly explored the factors affecting individuals’ initial intentions to start using a shared bicycle, but few looked at the likelihood that a user would continue using one This study proposed a structural equation model with bike-sharing purchase decision involvement as independent variable, bike-sharing willingness to use as dependent variable, traveler participation and traveler perceived value as intermediary variables by introducing the concepts of purchase decision involvement, customer participation and perceived value in consumer psychology and behavior. A survey on bike-sharing users in Xi’an was conducted online and offline, and 622 effective responses were collected. The research model was tested by Amos 24.0 and the empirical results showed that All influencing factors including bike-sharing’s purchase decision-making involvement, traveler participation and traveler’s perceived value are found to be significantly and positively associated with usage intention; traveler perceived value play a chain-mediating role between bike-sharing purchase decision involvement and usage intention; bike-sharing purchase decision involvement have indirect effects on traveler perceived value through traveler participation. The results of this study enrich the current research’s in the field of sharing economy, and it is certain guiding significant for how to obtain and maintain stable customers in bicycle-sharing industry.

The relationship between traffic flow, road characteristics, and light accidents was researched, and a Generalized Linear Model of minor accidents was established. It is found that motor vehicles’ traffic flow, segment length, and number of lanes are positive for accidents on road segments. The sections without isolation between non-motor vehicle and motor vehicle lanes have more accidents. Compared with other types of land use, the sections for business use have more accidents. However, the marked center-line and speed limits have no significant influence on minor accidents. Based on these conclusions, some suggestions for improving city safety are proposed.

The analysis on the park and ride demand is the basis for the planning and construction of park and ride facilities. This paper analyzes the characteristics of park and ride demand distribution by the park and ride demand survey data in Beijing. Then the demand density (or intensity) distribution chart was obtained by the Kernel density estimation method. Lastly, the paper discusses the relation between the park and ride intensity and effected factors based on the Structural equation modeling theory. The conclusions are that the poorer the traffic condition for the destination, the higher the public traffic service level, the closer the distance from the departing area to the park and ride facility for the travelers, the smaller the travel angle, the bigger is the park and ride demand intensity. The study results give some references for the demand forecasting of the park and ride in metropolis.

This paper demonstrates the two main factors that are involved in the location of chain supermarket in mega polis including the attraction of residents around the market and the management cost. The article establishes multiple-objective programming model in the location of chain supermarket which is based on the maximum attraction and minimum variable management cost. Then, the paper proposes a model in which the residents scale, purchasing power, distance between market and a bus station are regarded as the attraction indexes. In addition, the transportation cost and risk cost are regarded as the distribution cost indexes. Finally, an example has been employed which is resolved by lingo software to obtain the best location place.