By analyzing the basic naturalistic features,namely the controlling power of environment and heredity,it is expected that the naturalistic tendency,at least naturalistic features of the novel can be revealed and some ...By analyzing the basic naturalistic features,namely the controlling power of environment and heredity,it is expected that the naturalistic tendency,at least naturalistic features of the novel can be revealed and some enlightenments on the world view of the contemporary can be gained.The early part of the thesis provides a frame by giving the research background and synopsis,while the later sections aim at approaching the conclusion at the efforts of unveiling the naturalistic features in the novel.展开更多
The purpose of the study is to analyze the naturalistic elements in The Egg, which is taken from the collection of short stories, The Triumph of the Egg. The study states the ideology and technique of naturalism and t...The purpose of the study is to analyze the naturalistic elements in The Egg, which is taken from the collection of short stories, The Triumph of the Egg. The study states the ideology and technique of naturalism and then exams how naturalistic elements are revealed in the fiction. Then it comes to the conclusion that the family is defeated by the egg and the life of human beings is under control of complicated forces from both inside and outside.展开更多
Background: In the past we have shown the preservation and improvement of cognitive tasks in depressed and demented patients after 24 and 36 months of combined pharmacological and non-pharmacological treatment. Here w...Background: In the past we have shown the preservation and improvement of cognitive tasks in depressed and demented patients after 24 and 36 months of combined pharmacological and non-pharmacological treatment. Here we present the results of our ongoing, naturalistic study, in the same outpatient setting, at 60 month follow up. Materials and Methods: The study group consisted of 156 medically ill, physically disabled patients with mild to moderate dementia and depression. Patients were treated with antidepressants, cholinesterase inhibitors, and NMDA antagonists, along with their regular medication regimen. Non-pharmacological intervention was centered on a home-based program of physical and cognitive exercises paired with vitamins and supplements (multivitamins, vitamin E, L-methylfolate, alphalipoic acid, acetyl-L-carnitine, omega-3, and coenzyme Q-10) and diet modification. Cognitive assessments were performed yearly. Results: After 60 months of treatment, performance of all tasks remained at or above baseline. The MMSE, Cognistat-Attention, Cognistat-Judgment, and RFFT-Total Unique Designs demonstrated significant improvement. Conclusion: Our results, for the first time, demonstrate arrest in cognitive decline in demented/depressed patients with multiple medical co-morbidities for 60 months. Future investigations addressing the application of a combined, integrative treatment model are warranted.展开更多
Rural intersections account for around 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Crashes at rural intersections are also problematic si...Rural intersections account for around 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Crashes at rural intersections are also problematic since high speeds on intersection approaches are present which can exacerbate the impact of a crash. Additionally, rural areas are often underserved with EMS services which can further contribute to negative crash outcomes. This paper describes an analysis of driver stopping behavior at rural T-intersections using the SHRP 2 Naturalistic Driving Study data. Type of stop was used as a safety surrogate measure using full/rolling stops compared to non-stops. Time series traces were obtained for 157 drivers at 87 unique intersections resulting in 1277 samples at the stop controlled approach for T-intersections. Roadway (i.e. number of lanes, presence of skew, speed limit, presence of stop bar or other traffic control devices), driver (age, gender, speeding), and environmental characteristics (time of day, presence of rain) were reduced and included as independent variables. Results of a logistic regression model indicated drivers were less likely to stop during the nighttime. However presence of intersection lighting increased the likelihood of full/rolling stops. Presence of intersection skew was shown to negatively impact stopping behavior. Additionally drivers who were traveling over the posted speed limit upstream of the intersection approach were less likely to stop at the approach stop sign.展开更多
Stephen Crane spent a very productive life in his short span of life. His challenge against convention helps him to accept new ideas that were popular in his time, like naturalism, symbolism and impressionism. In part...Stephen Crane spent a very productive life in his short span of life. His challenge against convention helps him to accept new ideas that were popular in his time, like naturalism, symbolism and impressionism. In particular, Crane gave the perfect union of naturalistic conception and symbolic techniques in his novels, which are valued by critics as American literary classic works with highly artistic value, and his scant legacy was a rich one to the America literature. This paper tells us that, no matter how literary scholarships interpret and misinterpret Stephen Crane's literary works, the significance of Crane's achievement in the development of American literature has not been and will not be ignored.展开更多
Naturalistic codeswitching is a normal and powerful communicative feature of formal or informal bilingual interactions,which present linguists with part of their most fascinating analytical challenge.People use codesw...Naturalistic codeswitching is a normal and powerful communicative feature of formal or informal bilingual interactions,which present linguists with part of their most fascinating analytical challenge.People use codeswitching in various communication environments such as in bilingual families or immigrant contexts for effective information exchange.The present article investigates the environments and reasons for occurrence of naturalistic codeswitching and analyzes the linguistic constraints and social constraints on naturalistic codeswitching with examples.A more thorough and authentic assessment of individuals'linguistic knowledge about codeswitching,as well as individuals'codeswitching habits,must include observations of codeswitching behavior in naturalistic environments.展开更多
The COVID-19 pandemic and subsequent government responses have had unprecedented effects on public transit(PT)demand.This paper presents a naturalistic observation of the Jiading bus transit system in Shanghai,China,s...The COVID-19 pandemic and subsequent government responses have had unprecedented effects on public transit(PT)demand.This paper presents a naturalistic observation of the Jiading bus transit system in Shanghai,China,spanning from April 2021 to October 2023 and covering different stages under various extreme policy response combinations.We use the Prais-Winsten regression to quantitatively assess the pandemic’s impact on bus demand and explore demand recovery patterns at both aggregated and individual levels in the post-pandemic era.Our findings reveal a strong negative correlation between bus demand and the stringency of containment policies,consistent across both levels of anal-ysis.In the post-pandemic period,ridership has only rebounded to 77%of the pre-Omicron near-normal level,with notable spatial and temporal disparities across different regions.While the temporal distribution of ridership has largely normalized,the recovery of travel demand between zones outpaces that of travel within zones.Moreover,a persistent decline in individual travel frequency has been observed,which has not reverted in the post-pandemic period.The insights from this study can help policymakers better respond to potential future crises and improve PT services in the post-pandemic era.展开更多
Understanding how drivers perceive and respond to external stimuli in driving tasks is important for the development of advanced driving technologies and human-computer interaction.In this paper,we conducted a tempora...Understanding how drivers perceive and respond to external stimuli in driving tasks is important for the development of advanced driving technologies and human-computer interaction.In this paper,we conducted a temporal response analysis between driving data and cortical activation data measured by functional near-infrared spectroscopy(fNIRS),based on a naturalistic driving experiment.Temporal response function analysis indicates that stimuli,which elicit significant responses of drivers include distance,acceleration,time headway,and the velocity of the preceding vehicle.For these stimuli,the time lags and response patterns were further discussed.The influencing factors on drivers’perception were also studied based on various driver characteristics.These conclusions can provide guidance for the construction of car-following models,the safety assessment of drivers and the improvement of advanced driving technologies.展开更多
Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vit...Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vital important to understand the ecological performance of electric vehicles and its association with driving behaviors under varying road and environmental conditions.However,current researches on ecological driving behavior mostly use structured data to reflect the characteristics of ecological driving behavior,and it is difficult to accurately reveal the recessive relationship between driving behavior and energy consumption.One promising and prevalent method for comprehensively and in-depth characterizing driving behaviors is“graph spectrums”,which allows for an effective and illustrative representation of complex driving behavior characteristics.This study presented an assessment method of ecological driving for electric vehicles based on the graph.Firstly,a multi-source refined data set was constructed through naturalistic driving experiments(NDE).Four typical traffic state(CCCF:congested close car-following;CSSF:constrained slow free-flow;CSCF:constrained slow carfollowing;UFFF:unconstrained fast free-flow)were classified through longitudinal acceleration data,and driving behavior graph was constructed to realize the visual representation of driving behavior.Then,the energy consumption graph was constructed using the energy loss of 100 km(EL)index.After the six drivers with the highest and lowest ecological assessment of driving behavior using the behavior graph and energy consumption graph,proposing the quantitative analysis of fifteen drivers'ecology driving behavior.The results show that:1)The graphical method can describe the individual features of a driver’s ecological driving behavior;2)Rapid acceleration of driving behavior leads to high energy consumption;3)In the comparison among the six ecodrivers and energy-intensive drivers,founding that the energy-intensive drivers accelerate and decelerate significantly more in CCCF traffic state;4)The driving behavior was more complex and unecological in CCCF traffic state;5)Fifteen drivers had lower ecological scores in start-up driving.This study proposes a method for visualizing ecology driving behavior that not only help understand the individual characteristics of ecological driving behaviors,but also offers substantial application value for the subsequent construction of Ecological driving behavior regulation models.展开更多
The visual system continuously adapts to the statistical properties of the environment. Existing evidence shows a close resemblance between deep convolutional neural networks(CNNs) and primate visual stream in neural ...The visual system continuously adapts to the statistical properties of the environment. Existing evidence shows a close resemblance between deep convolutional neural networks(CNNs) and primate visual stream in neural selectivity to naturalistic textures above the primary visual processing stage. This study delves into the mechanisms of perceptual learning in CNNs,focusing on how they assimilate the high-order statistics of natural textures. Our results show that a CNN model achieves a similar performance improvement as humans, as manifested in the learning pattern across different types of high-order image statistics. While L2 was the first stage exhibiting texture selectivity, we found that stages beyond L2 were critically involved in learning. The significant contribution of L4 to learning was manifested both in the modulations of texture-selective responses and in the consequences of training with frozen connection weights. Our findings highlight learning-dependent plasticity in the mid-to-high-level areas of the visual hierarchy. This research introduces an AI-inspired approach for studying learning-induced cortical plasticity, utilizing DCNNs as an experimental framework to formulate testable predictions for empirical brain studies.展开更多
Visual language pre-training(VLP)models have demonstrated significant success in various domains,but they remain vulnerable to adversarial attacks.Addressing these adversarial vulnerabilities is crucial for enhancing ...Visual language pre-training(VLP)models have demonstrated significant success in various domains,but they remain vulnerable to adversarial attacks.Addressing these adversarial vulnerabilities is crucial for enhancing security in multi-modal learning.Traditionally,adversarial methods that target VLP models involve simultaneous perturbation of images and text.However,this approach faces significant challenges.First,adversarial perturbations often fail to translate effectively into real-world scenarios.Second,direct modifications to the text are conspicuously visible.To overcome these limitations,we propose a novel strategy that uses only image patches for attacks,thus preserving the integrity of the original text.Our method leverages prior knowledge from diffusion models to enhance the authenticity and naturalness of the perturbations.Moreover,to optimize patch placement and improve the effectiveness of our attacks,we utilize the cross-attention mechanism,which encapsulates inter-modal interactions by generating attention maps to guide strategic patch placement.Extensive experiments conducted in a white-box setting for image-to-text scenarios reveal that our proposed method significantly outperforms existing techniques,achieving a 100%attack success rate.展开更多
This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB op...This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB operators in Shanghai,China,with a 22-month con secutive observation ranging from January 2019 to October 2020.As all CB services were totally suspended at the beginning of 2020 due to the COVID-19 travel restriction and then gradually recovered in March 2020,we utilize this study period as a naturalistic observa tion experiment to investigate the changes in the operation status of each CB line before and after the travel restriction.Using the operation status at each month as the binary alternatives,the mixed logit models and the tree-based models with explainable machine learning techniques are respectively adopted to explore the factors that influence the decision-making process.The findings from both types of models are in general consistent.The results show that the characteristics of each CB line including the ridership,the length of the line,the closeness to charging stations,and the overlap of CB lines significantly impact the decisions.In addition,the land-use types around the CB stops and the market competition from alternative travel modes also play a key role in making the decisions.展开更多
Purpose–Feature selection is crucial for machine learning to recognize lane-change(LC)maneuver as there exist a large number of feature candidates.Blindly using feature could take up large storage and excessive compu...Purpose–Feature selection is crucial for machine learning to recognize lane-change(LC)maneuver as there exist a large number of feature candidates.Blindly using feature could take up large storage and excessive computation time,while insufficient feature selection would cause poor performance.Selecting high contributive features to classify LC and lane-keep behavior is effective for maneuver recognition.This paper aims to propose a feature selection method from a statistical view based on an analysis from naturalistic driving data.Design/methodology/approach–In total,1,375 LC cases are analyzed.To comprehensively select features,the authors extract the feature candidates from both time and frequency domains with various LC scenarios segmented by an occupancy schedule grid.Then the effect size(Cohen’s d)and p-value of every feature are computed to assess their contribution for each scenario.Findings–It has been found that the common lateral features,e.g.yaw rate,lateral acceleration and time-to-lane crossing,are not strong features for recognition of LC maneuver as empirical knowledge.Finally,cross-validation tests are conducted to evaluate model performance using metrics of receiver operating characteristic.Experimental results show that the selected features can achieve better recognition performance than using all the features without purification.Originality/value–In this paper,the authors investigate the contributions of each feature from the perspective of statistics based on big naturalistic driving data.The aim is to comprehensively figure out different types of features in LC maneuvers and select the most contributive features over various LC scenarios.展开更多
Traffic accidents are one of the most serious problems worldwide,being one of the leading causes of death and economic loss in the world.Low-and middle-income countries,mainly their medium-sized cities,are among the m...Traffic accidents are one of the most serious problems worldwide,being one of the leading causes of death and economic loss in the world.Low-and middle-income countries,mainly their medium-sized cities,are among the most affected by this problem.93%of traffic accidents occur in low and middle-income countries,even though these countries have approximately 60%of the world’s vehicles.This occurs mainly because in these types of countries,especially in medium-sized cities(target context),there are no ideal conditions for driving,such as adequate road infrastructure,good condition of vehicles,and rigorous safety policies.Advanced data analysis techniques including machine learning(ML)have increasingly been used to solve this problem.Naturalistic driving(ND)can be applied as a data collection method that provides information on traffic accidents.ND commonly uses a vehicle’s kinematic data to detect high-risk driving behaviors that could cause an accident.The objectives of this document are to present a review of different alternatives that help in data collection and creation of intelligent solutions related to detection of possible traffic accidents,principally using ND;and to propose an intelligent collision risk detection system(ICRDS)for identification of areas with a high probability of TA in the target context.Through the review,it was possible to analyze and evaluate the devices,variables and algorithms that help characterize a risk event in driving,considering the target context.The development of a prototype of an ICRDS for a medium-sized city in a developing country is considered viable,considering the identified components,with the aim of identifying risk events in driving,and areas of high probability of accidents in the city.展开更多
In my paper, I analyse Hume＇s philosophy of love with the general philosophical idea of a continual flux in the background. My main source is his Treatise of Human Nature published in 1739 where Hume develops in full...In my paper, I analyse Hume＇s philosophy of love with the general philosophical idea of a continual flux in the background. My main source is his Treatise of Human Nature published in 1739 where Hume develops in full length his purely naturalistic moral theory. First, I recall some basic features of Hume＇s general concept of a passion. Afterwards, I characterize his concept of love in context of his ＂principle＂ of sympathy in order to connect finally Hume＇s ideas to a basic distinction within traditional philosophy of love between love of benevolence and love of desire.展开更多
Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,71...Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research.The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage.The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics(age,driving experience or their combination)and the crash risk regarding cell phone engagements,as well as the correlation among the likelihood of the cell phone engagement during the driving,multiple driver demographic characteristics(gender,age and driving experience)and environment conditions.Findings–Senior drivers face an extremely high crash risk when distracted by cell phone during driving,but they are not involved in crashes at a large scale.On the contrary,cell phone usages account for a far larger percentage of total crashes for young drivers.Similarly,experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving,and cell phone engagements are attributed to a lower percentage of total crashes for them.Furthermore,experienced,senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.Originality/value–The results provide support to guide countermeasures and vehicle design.展开更多
Due to the speed difference and the complex interaction between merging and throughlane vehicles at freeway merging sections,crashes involving both human drivers and automated vehicles(AVs)persist.To assist AVs to pre...Due to the speed difference and the complex interaction between merging and throughlane vehicles at freeway merging sections,crashes involving both human drivers and automated vehicles(AVs)persist.To assist AVs to predict the intentions of surrounding vehicles for further dynamic motion planning,researchers have focused on developing trajectory prediction algorithms.Few studies,however,have developed merging trajectory prediction models using naturalistic driving data in China,making it urgent to put it on the agenda for AVs’safety and efficiency at freeway merging sections.Based on the merging periods extracted from the Shanghai Naturalistic Driving Study(SH-NDS),this study compares merging behavior on freeways with through-lane speed limits of 80 km/h,100 km/h,and 120 km/h using analysis of variance(ANOVA).Merging trajectory prediction algorithms for these three speed limit cases are trained and tested using backpropagation neural network(BPNN)and long short-term memory neural network(LSTMNN)approaches.Results show that:1)there are significant differences among the three cases in all merging behavior variables except for longitudinal gap,and 2)the BPNN algorithm for merging trajectory prediction demonstrates superior performance compared to the LSTMNN.Two major contributions to the safe operation of AVs are provided:1)the developed algorithms can be integrated into AV systems to accurately predict real-time desired trajectories of nearby merging vehicles in uncongested traffic conditions,and assist ongoing motion planning strategies for AVs;2)the algorithms can be incorporated in simulation tests for AV safety evaluation involving freeway merging sections.展开更多
A set of major disruptive political,socio-economic,technological,and ecological trends presents serious issues for tourism policy makers,regulators,and operators alike.In this turbulent context,how best to attempt to ...A set of major disruptive political,socio-economic,technological,and ecological trends presents serious issues for tourism policy makers,regulators,and operators alike.In this turbulent context,how best to attempt to predict tourist behaviours?In tourism research the dominant rationalistic approach to decision-making does provide some useful insights across tourism choice.However,it seems increasingly less suited to the often relatively unplanned,hedonic,opportunistic,and impulsive decision-making that often characterises tourists’behaviours on-site within a destination,and more generally to the behaviours of Generation Y and Generation Z.More generally,it is arguable that rational models of motivation and decision-making systematically underestimate the importance of affective processes in tourists’behaviours.In this paper,we explore the implications of employing a much more naturalistic approach to decision-making at both the policy level and at the frontline of tourism operations.展开更多
My goal in this paper is to respond to the objection that naturalistic accounts of morality miss the thicker meaning with which we normally imbue ethics. I concur. This should lead us to doubt our thicker concepts, ho...My goal in this paper is to respond to the objection that naturalistic accounts of morality miss the thicker meaning with which we normally imbue ethics. I concur. This should lead us to doubt our thicker concepts, however, not doubt moral genealogy. Our thicker conceptions are hyperbolic, at best. The underlying algorithm of morality is the evolutionarily stable strategy： conditional cooperation. The content of such agreements can vary, however, and that is where moral hyperbole resides. Still, we like to distinguish good hyperbole from bad hyperbole, but the only standard for such appraisal is whether the hyperbole is consistent with the social glue of evolutionary dynamics.展开更多
文摘By analyzing the basic naturalistic features,namely the controlling power of environment and heredity,it is expected that the naturalistic tendency,at least naturalistic features of the novel can be revealed and some enlightenments on the world view of the contemporary can be gained.The early part of the thesis provides a frame by giving the research background and synopsis,while the later sections aim at approaching the conclusion at the efforts of unveiling the naturalistic features in the novel.
文摘The purpose of the study is to analyze the naturalistic elements in The Egg, which is taken from the collection of short stories, The Triumph of the Egg. The study states the ideology and technique of naturalism and then exams how naturalistic elements are revealed in the fiction. Then it comes to the conclusion that the family is defeated by the egg and the life of human beings is under control of complicated forces from both inside and outside.
文摘Background: In the past we have shown the preservation and improvement of cognitive tasks in depressed and demented patients after 24 and 36 months of combined pharmacological and non-pharmacological treatment. Here we present the results of our ongoing, naturalistic study, in the same outpatient setting, at 60 month follow up. Materials and Methods: The study group consisted of 156 medically ill, physically disabled patients with mild to moderate dementia and depression. Patients were treated with antidepressants, cholinesterase inhibitors, and NMDA antagonists, along with their regular medication regimen. Non-pharmacological intervention was centered on a home-based program of physical and cognitive exercises paired with vitamins and supplements (multivitamins, vitamin E, L-methylfolate, alphalipoic acid, acetyl-L-carnitine, omega-3, and coenzyme Q-10) and diet modification. Cognitive assessments were performed yearly. Results: After 60 months of treatment, performance of all tasks remained at or above baseline. The MMSE, Cognistat-Attention, Cognistat-Judgment, and RFFT-Total Unique Designs demonstrated significant improvement. Conclusion: Our results, for the first time, demonstrate arrest in cognitive decline in demented/depressed patients with multiple medical co-morbidities for 60 months. Future investigations addressing the application of a combined, integrative treatment model are warranted.
文摘Rural intersections account for around 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Crashes at rural intersections are also problematic since high speeds on intersection approaches are present which can exacerbate the impact of a crash. Additionally, rural areas are often underserved with EMS services which can further contribute to negative crash outcomes. This paper describes an analysis of driver stopping behavior at rural T-intersections using the SHRP 2 Naturalistic Driving Study data. Type of stop was used as a safety surrogate measure using full/rolling stops compared to non-stops. Time series traces were obtained for 157 drivers at 87 unique intersections resulting in 1277 samples at the stop controlled approach for T-intersections. Roadway (i.e. number of lanes, presence of skew, speed limit, presence of stop bar or other traffic control devices), driver (age, gender, speeding), and environmental characteristics (time of day, presence of rain) were reduced and included as independent variables. Results of a logistic regression model indicated drivers were less likely to stop during the nighttime. However presence of intersection lighting increased the likelihood of full/rolling stops. Presence of intersection skew was shown to negatively impact stopping behavior. Additionally drivers who were traveling over the posted speed limit upstream of the intersection approach were less likely to stop at the approach stop sign.
文摘Stephen Crane spent a very productive life in his short span of life. His challenge against convention helps him to accept new ideas that were popular in his time, like naturalism, symbolism and impressionism. In particular, Crane gave the perfect union of naturalistic conception and symbolic techniques in his novels, which are valued by critics as American literary classic works with highly artistic value, and his scant legacy was a rich one to the America literature. This paper tells us that, no matter how literary scholarships interpret and misinterpret Stephen Crane's literary works, the significance of Crane's achievement in the development of American literature has not been and will not be ignored.
文摘Naturalistic codeswitching is a normal and powerful communicative feature of formal or informal bilingual interactions,which present linguists with part of their most fascinating analytical challenge.People use codeswitching in various communication environments such as in bilingual families or immigrant contexts for effective information exchange.The present article investigates the environments and reasons for occurrence of naturalistic codeswitching and analyzes the linguistic constraints and social constraints on naturalistic codeswitching with examples.A more thorough and authentic assessment of individuals'linguistic knowledge about codeswitching,as well as individuals'codeswitching habits,must include observations of codeswitching behavior in naturalistic environments.
基金supported by the National Natural Science Foundation of China(Nos.52272321,71901164,52272335)the Fundamental Research Funds for the Central Universities.
文摘The COVID-19 pandemic and subsequent government responses have had unprecedented effects on public transit(PT)demand.This paper presents a naturalistic observation of the Jiading bus transit system in Shanghai,China,spanning from April 2021 to October 2023 and covering different stages under various extreme policy response combinations.We use the Prais-Winsten regression to quantitatively assess the pandemic’s impact on bus demand and explore demand recovery patterns at both aggregated and individual levels in the post-pandemic era.Our findings reveal a strong negative correlation between bus demand and the stringency of containment policies,consistent across both levels of anal-ysis.In the post-pandemic period,ridership has only rebounded to 77%of the pre-Omicron near-normal level,with notable spatial and temporal disparities across different regions.While the temporal distribution of ridership has largely normalized,the recovery of travel demand between zones outpaces that of travel within zones.Moreover,a persistent decline in individual travel frequency has been observed,which has not reverted in the post-pandemic period.The insights from this study can help policymakers better respond to potential future crises and improve PT services in the post-pandemic era.
基金supported by the National Key R&D Program of China(No.2021YFC3001500).
文摘Understanding how drivers perceive and respond to external stimuli in driving tasks is important for the development of advanced driving technologies and human-computer interaction.In this paper,we conducted a temporal response analysis between driving data and cortical activation data measured by functional near-infrared spectroscopy(fNIRS),based on a naturalistic driving experiment.Temporal response function analysis indicates that stimuli,which elicit significant responses of drivers include distance,acceleration,time headway,and the velocity of the preceding vehicle.For these stimuli,the time lags and response patterns were further discussed.The influencing factors on drivers’perception were also studied based on various driver characteristics.These conclusions can provide guidance for the construction of car-following models,the safety assessment of drivers and the improvement of advanced driving technologies.
基金supported by the National Key R&D Program of China(2023YFC3081700)the National Natural Science Foundation of China(52372341).
文摘Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vital important to understand the ecological performance of electric vehicles and its association with driving behaviors under varying road and environmental conditions.However,current researches on ecological driving behavior mostly use structured data to reflect the characteristics of ecological driving behavior,and it is difficult to accurately reveal the recessive relationship between driving behavior and energy consumption.One promising and prevalent method for comprehensively and in-depth characterizing driving behaviors is“graph spectrums”,which allows for an effective and illustrative representation of complex driving behavior characteristics.This study presented an assessment method of ecological driving for electric vehicles based on the graph.Firstly,a multi-source refined data set was constructed through naturalistic driving experiments(NDE).Four typical traffic state(CCCF:congested close car-following;CSSF:constrained slow free-flow;CSCF:constrained slow carfollowing;UFFF:unconstrained fast free-flow)were classified through longitudinal acceleration data,and driving behavior graph was constructed to realize the visual representation of driving behavior.Then,the energy consumption graph was constructed using the energy loss of 100 km(EL)index.After the six drivers with the highest and lowest ecological assessment of driving behavior using the behavior graph and energy consumption graph,proposing the quantitative analysis of fifteen drivers'ecology driving behavior.The results show that:1)The graphical method can describe the individual features of a driver’s ecological driving behavior;2)Rapid acceleration of driving behavior leads to high energy consumption;3)In the comparison among the six ecodrivers and energy-intensive drivers,founding that the energy-intensive drivers accelerate and decelerate significantly more in CCCF traffic state;4)The driving behavior was more complex and unecological in CCCF traffic state;5)Fifteen drivers had lower ecological scores in start-up driving.This study proposes a method for visualizing ecology driving behavior that not only help understand the individual characteristics of ecological driving behaviors,but also offers substantial application value for the subsequent construction of Ecological driving behavior regulation models.
基金supported by the National Natural Science Foundation of China (Grant Nos. 31971031, 31930053, and 32171039)the STI2030Major Projects (Grant Nos. 2021ZD0203600, 2022ZD0204802, and 2022ZD0204804)。
文摘The visual system continuously adapts to the statistical properties of the environment. Existing evidence shows a close resemblance between deep convolutional neural networks(CNNs) and primate visual stream in neural selectivity to naturalistic textures above the primary visual processing stage. This study delves into the mechanisms of perceptual learning in CNNs,focusing on how they assimilate the high-order statistics of natural textures. Our results show that a CNN model achieves a similar performance improvement as humans, as manifested in the learning pattern across different types of high-order image statistics. While L2 was the first stage exhibiting texture selectivity, we found that stages beyond L2 were critically involved in learning. The significant contribution of L4 to learning was manifested both in the modulations of texture-selective responses and in the consequences of training with frozen connection weights. Our findings highlight learning-dependent plasticity in the mid-to-high-level areas of the visual hierarchy. This research introduces an AI-inspired approach for studying learning-induced cortical plasticity, utilizing DCNNs as an experimental framework to formulate testable predictions for empirical brain studies.
基金supported by the Open Research Fund of The State Key Laboratory of Blockchain and Data Security,Zhejiang University,the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.23xkjc010)Shenzhen Science and Technology Program(Nos.RCYX20221008092849068,JCYJ20220530145209022,KOTD20221101093559018,and JCYJ20220818102012025).
文摘Visual language pre-training(VLP)models have demonstrated significant success in various domains,but they remain vulnerable to adversarial attacks.Addressing these adversarial vulnerabilities is crucial for enhancing security in multi-modal learning.Traditionally,adversarial methods that target VLP models involve simultaneous perturbation of images and text.However,this approach faces significant challenges.First,adversarial perturbations often fail to translate effectively into real-world scenarios.Second,direct modifications to the text are conspicuously visible.To overcome these limitations,we propose a novel strategy that uses only image patches for attacks,thus preserving the integrity of the original text.Our method leverages prior knowledge from diffusion models to enhance the authenticity and naturalness of the perturbations.Moreover,to optimize patch placement and improve the effectiveness of our attacks,we utilize the cross-attention mechanism,which encapsulates inter-modal interactions by generating attention maps to guide strategic patch placement.Extensive experiments conducted in a white-box setting for image-to-text scenarios reveal that our proposed method significantly outperforms existing techniques,achieving a 100%attack success rate.
基金This work is supported by the National Natural Science Foundation of China(Grant Nos.52272321,71901164,52272335)the Fundamental Research Funds for the Central Universities.
文摘This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB operators in Shanghai,China,with a 22-month con secutive observation ranging from January 2019 to October 2020.As all CB services were totally suspended at the beginning of 2020 due to the COVID-19 travel restriction and then gradually recovered in March 2020,we utilize this study period as a naturalistic observa tion experiment to investigate the changes in the operation status of each CB line before and after the travel restriction.Using the operation status at each month as the binary alternatives,the mixed logit models and the tree-based models with explainable machine learning techniques are respectively adopted to explore the factors that influence the decision-making process.The findings from both types of models are in general consistent.The results show that the characteristics of each CB line including the ridership,the length of the line,the closeness to charging stations,and the overlap of CB lines significantly impact the decisions.In addition,the land-use types around the CB stops and the market competition from alternative travel modes also play a key role in making the decisions.
文摘Purpose–Feature selection is crucial for machine learning to recognize lane-change(LC)maneuver as there exist a large number of feature candidates.Blindly using feature could take up large storage and excessive computation time,while insufficient feature selection would cause poor performance.Selecting high contributive features to classify LC and lane-keep behavior is effective for maneuver recognition.This paper aims to propose a feature selection method from a statistical view based on an analysis from naturalistic driving data.Design/methodology/approach–In total,1,375 LC cases are analyzed.To comprehensively select features,the authors extract the feature candidates from both time and frequency domains with various LC scenarios segmented by an occupancy schedule grid.Then the effect size(Cohen’s d)and p-value of every feature are computed to assess their contribution for each scenario.Findings–It has been found that the common lateral features,e.g.yaw rate,lateral acceleration and time-to-lane crossing,are not strong features for recognition of LC maneuver as empirical knowledge.Finally,cross-validation tests are conducted to evaluate model performance using metrics of receiver operating characteristic.Experimental results show that the selected features can achieve better recognition performance than using all the features without purification.Originality/value–In this paper,the authors investigate the contributions of each feature from the perspective of statistics based on big naturalistic driving data.The aim is to comprehensively figure out different types of features in LC maneuvers and select the most contributive features over various LC scenarios.
基金Universidad del Cauca(Colombia)Universidad Icesi(Colombia)for supporting this research。
文摘Traffic accidents are one of the most serious problems worldwide,being one of the leading causes of death and economic loss in the world.Low-and middle-income countries,mainly their medium-sized cities,are among the most affected by this problem.93%of traffic accidents occur in low and middle-income countries,even though these countries have approximately 60%of the world’s vehicles.This occurs mainly because in these types of countries,especially in medium-sized cities(target context),there are no ideal conditions for driving,such as adequate road infrastructure,good condition of vehicles,and rigorous safety policies.Advanced data analysis techniques including machine learning(ML)have increasingly been used to solve this problem.Naturalistic driving(ND)can be applied as a data collection method that provides information on traffic accidents.ND commonly uses a vehicle’s kinematic data to detect high-risk driving behaviors that could cause an accident.The objectives of this document are to present a review of different alternatives that help in data collection and creation of intelligent solutions related to detection of possible traffic accidents,principally using ND;and to propose an intelligent collision risk detection system(ICRDS)for identification of areas with a high probability of TA in the target context.Through the review,it was possible to analyze and evaluate the devices,variables and algorithms that help characterize a risk event in driving,considering the target context.The development of a prototype of an ICRDS for a medium-sized city in a developing country is considered viable,considering the identified components,with the aim of identifying risk events in driving,and areas of high probability of accidents in the city.
文摘In my paper, I analyse Hume＇s philosophy of love with the general philosophical idea of a continual flux in the background. My main source is his Treatise of Human Nature published in 1739 where Hume develops in full length his purely naturalistic moral theory. First, I recall some basic features of Hume＇s general concept of a passion. Afterwards, I characterize his concept of love in context of his ＂principle＂ of sympathy in order to connect finally Hume＇s ideas to a basic distinction within traditional philosophy of love between love of benevolence and love of desire.
基金supported in part by the Joint Laboratory for Internet of Vehicles,Ministry of Education-China Mobile Communications Corporation under Grant ICV-KF2018-01in part by the National Natural Science Foundation of China underGrant 51975194 and 51905161.
文摘Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research.The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage.The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics(age,driving experience or their combination)and the crash risk regarding cell phone engagements,as well as the correlation among the likelihood of the cell phone engagement during the driving,multiple driver demographic characteristics(gender,age and driving experience)and environment conditions.Findings–Senior drivers face an extremely high crash risk when distracted by cell phone during driving,but they are not involved in crashes at a large scale.On the contrary,cell phone usages account for a far larger percentage of total crashes for young drivers.Similarly,experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving,and cell phone engagements are attributed to a lower percentage of total crashes for them.Furthermore,experienced,senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.Originality/value–The results provide support to guide countermeasures and vehicle design.
基金sponsored by the National Natural Science Foundation of China(No.51878498)the Belt and Road Cooperation Program under the 2023 Shanghai Action Plan for Science,Technology and Innovation(No.23210750500).
文摘Due to the speed difference and the complex interaction between merging and throughlane vehicles at freeway merging sections,crashes involving both human drivers and automated vehicles(AVs)persist.To assist AVs to predict the intentions of surrounding vehicles for further dynamic motion planning,researchers have focused on developing trajectory prediction algorithms.Few studies,however,have developed merging trajectory prediction models using naturalistic driving data in China,making it urgent to put it on the agenda for AVs’safety and efficiency at freeway merging sections.Based on the merging periods extracted from the Shanghai Naturalistic Driving Study(SH-NDS),this study compares merging behavior on freeways with through-lane speed limits of 80 km/h,100 km/h,and 120 km/h using analysis of variance(ANOVA).Merging trajectory prediction algorithms for these three speed limit cases are trained and tested using backpropagation neural network(BPNN)and long short-term memory neural network(LSTMNN)approaches.Results show that:1)there are significant differences among the three cases in all merging behavior variables except for longitudinal gap,and 2)the BPNN algorithm for merging trajectory prediction demonstrates superior performance compared to the LSTMNN.Two major contributions to the safe operation of AVs are provided:1)the developed algorithms can be integrated into AV systems to accurately predict real-time desired trajectories of nearby merging vehicles in uncongested traffic conditions,and assist ongoing motion planning strategies for AVs;2)the algorithms can be incorporated in simulation tests for AV safety evaluation involving freeway merging sections.
文摘A set of major disruptive political,socio-economic,technological,and ecological trends presents serious issues for tourism policy makers,regulators,and operators alike.In this turbulent context,how best to attempt to predict tourist behaviours?In tourism research the dominant rationalistic approach to decision-making does provide some useful insights across tourism choice.However,it seems increasingly less suited to the often relatively unplanned,hedonic,opportunistic,and impulsive decision-making that often characterises tourists’behaviours on-site within a destination,and more generally to the behaviours of Generation Y and Generation Z.More generally,it is arguable that rational models of motivation and decision-making systematically underestimate the importance of affective processes in tourists’behaviours.In this paper,we explore the implications of employing a much more naturalistic approach to decision-making at both the policy level and at the frontline of tourism operations.
文摘My goal in this paper is to respond to the objection that naturalistic accounts of morality miss the thicker meaning with which we normally imbue ethics. I concur. This should lead us to doubt our thicker concepts, however, not doubt moral genealogy. Our thicker conceptions are hyperbolic, at best. The underlying algorithm of morality is the evolutionarily stable strategy： conditional cooperation. The content of such agreements can vary, however, and that is where moral hyperbole resides. Still, we like to distinguish good hyperbole from bad hyperbole, but the only standard for such appraisal is whether the hyperbole is consistent with the social glue of evolutionary dynamics.
