Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Desi...Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.展开更多
The COVID-19 pandemic had an enormous impact on the vegetable supply chain in China.Effective evaluation of the pandemic’s influences on vegetable production is vital for policy settings to enhance the security of ve...The COVID-19 pandemic had an enormous impact on the vegetable supply chain in China.Effective evaluation of the pandemic’s influences on vegetable production is vital for policy settings to enhance the security of vegetable supply.Based on first-hand data from 526 households,we explored regional differences in different types of loss and potential factors affecting the severity farmer households suffered during the pandemic.The results underline that sales contraction and price volatility in the context of interruption of supply chain dominate the total losses during the pandemic.Such losses differ across provinces and are more substantial in provinces with stricter confinement measures.Farmer households’participation in local market and modern marketing methods helps mitigate the negative effects of the COVID-19 shock,while labor hiring and facilities adoption in production widen the losses due to the shortage in the workforce.In the future,the vegetable industry practitioners and relevant government departments should work together to coordinate the development of short and long supply chains and strengthen the stability and security of the vegetable supply chain.展开更多
During the past two decades, several methodologies are endorsed to assess the compatibility of roadways for bicycle use under homogeneous traffic conditions. However, these methodologies cannot be adopted under hetero...During the past two decades, several methodologies are endorsed to assess the compatibility of roadways for bicycle use under homogeneous traffic conditions. However, these methodologies cannot be adopted under heterogeneous traffic where on-street bicyclists encounter a complex interaction with various types of vehicles and show divergent operational characteristics. Thus, the present study proposes an initial model suitable for urban road segments in mid-sized cities under such complex situations. For analysis purpose, various operational and physical factors along with user perception data sets （13,624 effective ratings in total） were collected from 74 road segments. Eight important road attributes affecting the bicycle service quality were identified using the most recent and most promising machine learning technique namely, random forest. The identified variables are namely, effective width of outside through lane, pavement condition index, traffic volume, traffic speed, roadside commercial activities, interruptions by unauthorized stoppages of intermittent public transits, vehicular ingress-egress to on-street parking area, and frequency of driveways carrying a high volume of traffic. Service prediction models were developed using ordered probit and ordered logit modeling structures which meet a confidence level of 95%. Prediction performances of developed models were assessed in terms of several statistical parameters and the ordered probit model outperformed the ordered logit model. Incorporating outputs of the probit model, a pre- dictive equation is presented that can identify under what level a segment is offering services for bicycle use. The service levels offered by roadways were classified into six categories varying from ＇excellent＇ to ＇worst＇ （A-F）.展开更多
On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration...On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration with the method of Ordered Probit Regression.As is shown in the results,variables under peasants' personal endowment group and resource of the development group have little impact on peasants' SWB.The variables with observable impact are concentrated in the living condition group and the public atmosphere group.展开更多
基金National Natural Science Foundation of China(No.52072214)the project of Tsinghua University-Toyota Joint Research Center for AI technology of Automated Vehicle(No.TTAD2021-10).
文摘Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.
基金This paper was supported by the National Social Science Foundation of China(19ZDA106)the National Science Foundation of China(71773109)the European Commission Project 777742(EC H2020-MSCA-RISE-2017).
文摘The COVID-19 pandemic had an enormous impact on the vegetable supply chain in China.Effective evaluation of the pandemic’s influences on vegetable production is vital for policy settings to enhance the security of vegetable supply.Based on first-hand data from 526 households,we explored regional differences in different types of loss and potential factors affecting the severity farmer households suffered during the pandemic.The results underline that sales contraction and price volatility in the context of interruption of supply chain dominate the total losses during the pandemic.Such losses differ across provinces and are more substantial in provinces with stricter confinement measures.Farmer households’participation in local market and modern marketing methods helps mitigate the negative effects of the COVID-19 shock,while labor hiring and facilities adoption in production widen the losses due to the shortage in the workforce.In the future,the vegetable industry practitioners and relevant government departments should work together to coordinate the development of short and long supply chains and strengthen the stability and security of the vegetable supply chain.
文摘During the past two decades, several methodologies are endorsed to assess the compatibility of roadways for bicycle use under homogeneous traffic conditions. However, these methodologies cannot be adopted under heterogeneous traffic where on-street bicyclists encounter a complex interaction with various types of vehicles and show divergent operational characteristics. Thus, the present study proposes an initial model suitable for urban road segments in mid-sized cities under such complex situations. For analysis purpose, various operational and physical factors along with user perception data sets （13,624 effective ratings in total） were collected from 74 road segments. Eight important road attributes affecting the bicycle service quality were identified using the most recent and most promising machine learning technique namely, random forest. The identified variables are namely, effective width of outside through lane, pavement condition index, traffic volume, traffic speed, roadside commercial activities, interruptions by unauthorized stoppages of intermittent public transits, vehicular ingress-egress to on-street parking area, and frequency of driveways carrying a high volume of traffic. Service prediction models were developed using ordered probit and ordered logit modeling structures which meet a confidence level of 95%. Prediction performances of developed models were assessed in terms of several statistical parameters and the ordered probit model outperformed the ordered logit model. Incorporating outputs of the probit model, a pre- dictive equation is presented that can identify under what level a segment is offering services for bicycle use. The service levels offered by roadways were classified into six categories varying from ＇excellent＇ to ＇worst＇ （A-F）.
基金supported by the Natural Science Foundation of China(NSFC)[Grant No.71263042],Evaluation of Farmer Development Capability in Poverty-Ridden Areas Liupanshan
文摘On the basis of data collected from Liupanshan poverty-ridden areas,the paper selects 24 variables under 4 groups to figure out the influencing factors of subjective well-being(SWB) of peasants in ecological migration with the method of Ordered Probit Regression.As is shown in the results,variables under peasants' personal endowment group and resource of the development group have little impact on peasants' SWB.The variables with observable impact are concentrated in the living condition group and the public atmosphere group.
