Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage...Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage- ment of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, den- sity, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simula- tion model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continu- ous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient.展开更多
As the transport sector is a major source of greenhouse gas emissions, the effect of urbanization on transport CO2 emissions in developing cities has become a key issue under global climate change. Examining the case ...As the transport sector is a major source of greenhouse gas emissions, the effect of urbanization on transport CO2 emissions in developing cities has become a key issue under global climate change. Examining the case of Xi＇an, this paper aims to explore the spatial distribution of commuting CO2 emissions and influencing factors in the new, urban industry zones and city centers considering Xi＇an＇s transition from a monocentric to a polycentric city in the process of urbanization. Based on household survey data from 1501 respondents, there are obvious differences in commuting CO2 emissions between new industry zones and city centers： City centers feature lower household emissions of 2.86 kg CO2 per week, whereas new industry zones generally have higher household emissions of 3.20 kg CO2 per week. Contrary to previous research results, not all new industry zones have high levels of CO2 emissions; with the rapid development of various types of industries, even a minimum level of household emissions of 2.53 kg CO2 per week is possible. The uneven distribution of commuting CO2 emissions is not uniformly affected by spatial parameters such as job-housing balance, residential density, employment density, and land use diversity. Optimum combination of the spatial parameters and travel pattern along with corresponding transport infrastructure construction may be an appropriate path to reduction and control of emissions from commuting.展开更多
To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditi...To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditional data preprocessing method is improved.The new method uses hierarchical clustering to determine the traffic flow state and fills in missing and abnormal data according to different traffic flow states.Secondly,one-dimensional data are mapped into a multidimensional data matrix through PSR,and the time series complex network is used to verify the data reconstruction effect.Finally,the multidimensional data matrix is inputted into the XGBoost model to predict future traffic flow parameters.The experimental results show that the mean square error,average absolute error,and average absolute percentage error of the prediction results of the PSR-XGBoost model are 5.399%,1.632%,and 6.278%,respectively,and the required running time is 17.35 s.Compared with mathematical-statistical models and other machine learning models,the PSR-XGBoost model has clear advantages in multiple predictive indicators,proving its feasibility and superiority in short-term traffic flow prediction.展开更多
Boron nitride nanotubes （BN-NTs） with pure hexagonal BN phase have been synthesized by heating ball-milled boron powders in flowing ammonia gas at a temperature of 1200℃. The as-synthesized products were characteri...Boron nitride nanotubes （BN-NTs） with pure hexagonal BN phase have been synthesized by heating ball-milled boron powders in flowing ammonia gas at a temperature of 1200℃. The as-synthesized products were characterized by X-ray powder diffraction, transmission electron microscopy, high-resolution transmission electron microscopy, and electron energy loss spectroscopy （EELS）. The diameters of nanotubes are in the rage of 40-120nm and the lengths are more than 10μm. EELS result identifies that the ratio of boron and nitrogen is almost 1：1 The growth temperature is a crucial growth parameter in controlling the structure and crystalline of BN-NTs. The nanotubes grown at 1100℃ possesses of a bamboo-like structure, while as the temperature increased to 1200℃, most of the nanotubes exhibited a cylindrical structure. In addition, changing the heating time can control the size of the nanotubes. The gas atmosphere has influence on the yield of BN-NTs during heating process. When heating atmosphere was replaced by nitrogen, the yield of nanotubes was remarkably decreased.展开更多
This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Fir...This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Firstly,this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system,and uses the analytic hierarchy process(AHP)to evaluate the indicators,analyzes various factors that affect the safe operation of FAO,and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.Secondly,taking the Yanfang Line as an example,this paper uses OpenTrack software to analyze the efficiency of FAO operation,and conducts simulation calculations for key links such as the mainline tracking interval,train entry and exit,and return limit interval.The fault impact surface of the FAO trains is simulated and discussed to verify whether FAO can meet the long-term operation requirements of Yanfang Line.Finally,this paper compares the simulation data of FAO on the Yanfang Line with manual operation(MO)to verify the advantages of FAO and guide the engineering construction of subsequent fully automated driving lines.展开更多
In this paper, after analyzing the predicaments that Chinese traditional logistics enterprises face while launching modem logistics services, the theory of reforming Chinese traditional logistics enterprises with Busi...In this paper, after analyzing the predicaments that Chinese traditional logistics enterprises face while launching modem logistics services, the theory of reforming Chinese traditional logistics enterprises with Business Process Reengineering （BPR） is put forward. Then the basic implementation principles are discussed, and the steps of BPR are also analyzed for Chinese logistics enterprises. Moreover, five relevant measures of ensuring the success of BPR for them are concept reengineering, system reengineering, organization reengineering, culture reengineering and technology reengineering.展开更多
The dispersion of vehicular paths is a common phenomenon in the inner area of signalized intersections due to heterogeneous driver behavior and interactions.This study aims to develop an explainable neural network-bas...The dispersion of vehicular paths is a common phenomenon in the inner area of signalized intersections due to heterogeneous driver behavior and interactions.This study aims to develop an explainable neural network-based model to describe the vehicle path dispersion by exploring the relationship between the path dispersion and external factors.A backpropagation neural network model was established to analyze the effects of external factors on the dispersion of through and left-turn paths based on real trajectory data collected from 20 intersections in Shanghai,China.Twelve influencing factors in varying geometric,traffic,signalization,and traffic management conditions were considered.The predictive power and transferability of the model were verified by applying the trained model on the four new intersections.The contributions of the influencing factors on the path dispersion were explored based on the neural interpretation diagram,relative importance of influencing factors,and sensitivity analysis to offer explanatory insights for the proposed model.The results show that the mean absolute percentage errors of the path dispersion models for the through and left-turn movements are only 14.67%and 17.65%,respectively.The through path dispersion is primarily influenced by the number of exit lanes,the offset degree between the approach and exit lanes,and the traffic saturation degree on the through lane.In contrast,the path dispersion of the left turn is mainly affected by the number of exit lanes,the left-turn angle,and the setting of guide lines.展开更多
Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used veh...Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used vehicle emission estimation model.We first design a protocol of converting percentage values of rotating speed and torque of engine to second-by-second vehicle speed to accommodate the differences between driving cycles adopted in local emission standards and those used in MOVES.In order to identify the best model year for estimating emissions under different local emission standards,we propose an approach of comparing emission outcomes rather than emission factors,considering the differences in unit used between MOVES and emission standards.To calculate road seg mentlevel emission factors,we weight original factors by integrating vehicle fleet informa tion which contains the shares of vehicles under different emission standards and at different ages.We apply the approach to a major freight corridor area in Shanghai and cal culate emission factors by air pollutant,average speed of road sections,and road type.Dynamic emissions of each road section per hour are calculated to reflect the spatial dis tribution of truck emissions.The research outcomes may help local departments,especially in developing countries,better estimate freight vehicle emissions and make policies corre spondingly to control their impacts on public health.展开更多
Rapid advancements in automated vehicles(AVs)technology have transformed the measurability,controllability and unpredictability of transportation systems.Evaluating driving risk and effectively managing driving behavi...Rapid advancements in automated vehicles(AVs)technology have transformed the measurability,controllability and unpredictability of transportation systems.Evaluating driving risk and effectively managing driving behaviours is critical.AVs should be enabled to identify,analyse,evaluate and devise effective countermeasures for driving risk by autonomously learning from human driving experiences.This learning will enhance the interactive decision-making capabilities and achieve driving behaviours that reflect human-like logic.The primary challenge lies in integrating human-like logic and driving risk constraints based on behavioural decision-making outcomes.This integration is crucial to align the AVs’cognitive levels-movement,comprehension,memory and inference-more closely with human driving necessities,habits and styles.Such alignment holds the potential to improve the prediction and planning of future actions and facilitate the development of motion planning schemes geared towards minimizing driving risk.We performed a comprehensive review of AVs’behavioural decision-making and intelligent motion-planning research from 2000 to 2023 from four key perspectives-driving risk,human-like logic,behavioural decision making and motion planning.Based on the Web of Science and China National Knowledge Internet database,the results of our review indicate that significant progress has been made in AV behavioural decision making and intelligent motion planning over time.When AVs and human-driven vehicles coexist,greater incorporation of human-like logic is required.Guided by these findings,we delineate future development directions and propose a research paradigm for human-like logic and a research framework for human-like logic-driven behavioural decision making and intelligent motion planning of AVs.展开更多
The purpose of this paper is to provide a summary of a quick overview of the latest developments and unprecedented opportunities for scholars who want to set foot in the field of traditional taxi and online car-hailin...The purpose of this paper is to provide a summary of a quick overview of the latest developments and unprecedented opportunities for scholars who want to set foot in the field of traditional taxi and online car-hailing(TTOC).From the perspectives of peoples(e.g.,passenger,driver,and policymaker),vehicle,road,and environment,this paper describes the current research status of TTOC's big data in six hot topics,including the ridership factor,spatio-temporal distribution and travel behavior,cruising strategy and passenger service market partition,route planning,transportation emission and new-energy,and TTOC's data extensional application.These topics were included in five mainstreams as follows:(1)abundant studies often focus only on determinant analysis on given transportation(taxi,transit,online car-hailing);the exploration of ridership patterns for a multimodal transportation mode is rare;furthermore,multiple aspects of factors were not considered synchronously in a wide time span;(2)travel behavior research mainly concentrates on the commuting trips and distribution patterns of various travel indices(e.g.,distance,displacement,time);(3)the taxi driver-searching strategy can be divided into autopsychic cruising and system dispatching;(4)the spatio-temporal distribution character of TTOC's fuel consumption(FC)and greenhouse gas(GHG)emissions has become a hotspot recently,and there has been a recommendation for electric taxi(ET)in urban cities to decrease transportation congestion is proposed;and(5)based on TTOC and point of interest(POI)multi-source data,many machine learning algorithms were used to predict travel condition indices,land use,and travel behavior.Then,the main bottlenecks and research directions that can be explored in the future are discussed.We hope this result can provide an overview of current fundamental aspects of TTOC's utilization in the urban area.展开更多
Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and t...Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.Findings–The proposed model has a promising control effect under different geometric controlled conditions.Moreover,the proposed model performs robustly under various safety time headways,lengths of the CLL and green times of the main signal.Originality/value–This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections.The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness。展开更多
Purpose–This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency.By introducing the theory of moving block section for high-...Purpose–This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency.By introducing the theory of moving block section for high-speed train control,a speed guidance model based on the quasi-moving block speed guidance(QMBSG)is proposed to direct platoon including human-driven vehicles and connected vehicles(CV)through the intersection coordinately.Design/methodology/approach–In this model,the green time of the intersection is divided into multiple block intervals according to the minimal safety headway.Connected vehicles can pass through the intersection by following the block interval using the QMBSG model.The block interval is assigned dynamically according to the traveling relation of HV and CV,when entering the communication range of the intersection.To validate the comprehensive guidance effect of the proposed model,a general evaluation function(GEF)is established.Compared to CVs without speed guidance,the simulation results show that the GEF of QMBSG model has an obvious improvement.Findings–Compared to CVs without speed guidance,the simulation results show that the GEF of QMBSG model has an obvious improvement.Also,compared to the single intersection speed guidance model,the GEF value of the QMBSG model improves over 17.1%.To further explore the guidance effect,the impact of sensitivity factors of the CVs’environment,such as intersection environment,communication range and penetration rate(PR)is analyzed.When the PR reaches 75.0%,the GEF value will change suddenly and the model guidance effect will be significantly improved.This paper also analyzes the impact of the length of block interval under different PR and traffic demands.It is found that the proposed model has a better guidance effect when the length of the block section is 2 s,which facilitates traffic congestion alleviation of the intersection in practice.Originality/value–Based on the aforementioned discussion,the contributions of this paper are three-fold.Based on the traveling information of HV/CV and the signal phase and timing plans,the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately,by following the block interval assigned dynamically.Considering comprehensively the indexes of mobility,safety and environment,a GEF is provided to evaluate the guidance effect of vehicles through the intersection.Sensitivity analysis is carried out on the QMBSG model.The key communication and traffic parameters of the CV environment are analyzed,such as path attenuation,PR,etc.Finally,the effect of the length of block interval is explored.展开更多
Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature ...Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.展开更多
The fragmented design of intelligent transportation systems creates isolated intelligent systems.Resource competition and information gaps are fierce and widespread,worsening traffic issues and degrading overall servi...The fragmented design of intelligent transportation systems creates isolated intelligent systems.Resource competition and information gaps are fierce and widespread,worsening traffic issues and degrading overall service levels.Therefore,empowered by advanced technologies,an evolution toward an autonomous transportation system(ATS)is observed.This evolution aims to develop a collaborative and sustainable ecosystem,prompting interoperability within the cloud-edge-device continuum.展开更多
Many studies suggest that more crashes occur due to mixed traffic flow at unsignalized intersections. However, very little is known about the injury severity of these crashes. The objective of this study is therefore ...Many studies suggest that more crashes occur due to mixed traffic flow at unsignalized intersections. However, very little is known about the injury severity of these crashes. The objective of this study is therefore to investigate how contributory factors affect crash injury severity at unsignalized intersections. The dataset used for this analysis derived from police crash reports from Dec. 2006 to Apr. 2009 in Heilongjiang Province, China. An ordered probit model was developed to predict the probability that the injury severity of a crash will be one of four levels ： no injury, slight injury, severe injury, and fatal injury. The injury severity of a crash was evaluated in terms of the most severe injury sustained by any person involved in the crash. Results from the present study showed that different factors had varying effects on crash injury severity. Factors found to result in the increased probability of serious injuries include adverse weather, sideswiping with pedestrians on poor surface, the interaction of rear-ends and the third-class highway, winter night without illumination, and the interaction between traffic signs or markings and the third-class highway. Although there are some limitations in the current study, this study provides more insights into crash injury severity at unsignalized intersections.展开更多
文摘Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage- ment of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, den- sity, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simula- tion model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continu- ous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient.
基金funded by National Natural Science Foundation of China(51178055)Asia Pacific Network for Global Change Research(1094801)
文摘As the transport sector is a major source of greenhouse gas emissions, the effect of urbanization on transport CO2 emissions in developing cities has become a key issue under global climate change. Examining the case of Xi＇an, this paper aims to explore the spatial distribution of commuting CO2 emissions and influencing factors in the new, urban industry zones and city centers considering Xi＇an＇s transition from a monocentric to a polycentric city in the process of urbanization. Based on household survey data from 1501 respondents, there are obvious differences in commuting CO2 emissions between new industry zones and city centers： City centers feature lower household emissions of 2.86 kg CO2 per week, whereas new industry zones generally have higher household emissions of 3.20 kg CO2 per week. Contrary to previous research results, not all new industry zones have high levels of CO2 emissions; with the rapid development of various types of industries, even a minimum level of household emissions of 2.53 kg CO2 per week is possible. The uneven distribution of commuting CO2 emissions is not uniformly affected by spatial parameters such as job-housing balance, residential density, employment density, and land use diversity. Optimum combination of the spatial parameters and travel pattern along with corresponding transport infrastructure construction may be an appropriate path to reduction and control of emissions from commuting.
基金The National Natural Science Foundation of China (No.71771019, 71871130, 71971125)the Science and Technology Special Project of Shandong Provincial Public Security Department (No. 37000000015900920210010001,37000000015900920210012001)。
文摘To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditional data preprocessing method is improved.The new method uses hierarchical clustering to determine the traffic flow state and fills in missing and abnormal data according to different traffic flow states.Secondly,one-dimensional data are mapped into a multidimensional data matrix through PSR,and the time series complex network is used to verify the data reconstruction effect.Finally,the multidimensional data matrix is inputted into the XGBoost model to predict future traffic flow parameters.The experimental results show that the mean square error,average absolute error,and average absolute percentage error of the prediction results of the PSR-XGBoost model are 5.399%,1.632%,and 6.278%,respectively,and the required running time is 17.35 s.Compared with mathematical-statistical models and other machine learning models,the PSR-XGBoost model has clear advantages in multiple predictive indicators,proving its feasibility and superiority in short-term traffic flow prediction.
基金Supported by the National Natural Science Foundation of China （No.20171007）.
文摘Boron nitride nanotubes （BN-NTs） with pure hexagonal BN phase have been synthesized by heating ball-milled boron powders in flowing ammonia gas at a temperature of 1200℃. The as-synthesized products were characterized by X-ray powder diffraction, transmission electron microscopy, high-resolution transmission electron microscopy, and electron energy loss spectroscopy （EELS）. The diameters of nanotubes are in the rage of 40-120nm and the lengths are more than 10μm. EELS result identifies that the ratio of boron and nitrogen is almost 1：1 The growth temperature is a crucial growth parameter in controlling the structure and crystalline of BN-NTs. The nanotubes grown at 1100℃ possesses of a bamboo-like structure, while as the temperature increased to 1200℃, most of the nanotubes exhibited a cylindrical structure. In addition, changing the heating time can control the size of the nanotubes. The gas atmosphere has influence on the yield of BN-NTs during heating process. When heating atmosphere was replaced by nitrogen, the yield of nanotubes was remarkably decreased.
文摘This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Firstly,this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system,and uses the analytic hierarchy process(AHP)to evaluate the indicators,analyzes various factors that affect the safe operation of FAO,and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.Secondly,taking the Yanfang Line as an example,this paper uses OpenTrack software to analyze the efficiency of FAO operation,and conducts simulation calculations for key links such as the mainline tracking interval,train entry and exit,and return limit interval.The fault impact surface of the FAO trains is simulated and discussed to verify whether FAO can meet the long-term operation requirements of Yanfang Line.Finally,this paper compares the simulation data of FAO on the Yanfang Line with manual operation(MO)to verify the advantages of FAO and guide the engineering construction of subsequent fully automated driving lines.
文摘In this paper, after analyzing the predicaments that Chinese traditional logistics enterprises face while launching modem logistics services, the theory of reforming Chinese traditional logistics enterprises with Business Process Reengineering （BPR） is put forward. Then the basic implementation principles are discussed, and the steps of BPR are also analyzed for Chinese logistics enterprises. Moreover, five relevant measures of ensuring the success of BPR for them are concept reengineering, system reengineering, organization reengineering, culture reengineering and technology reengineering.
基金supported by grants from the National Natural Science Foundation of China(71971140 and 52122215)the Shanghai Pujiang Program(21PJC085)the Shanghai Shuguang Program(22SG45).
文摘The dispersion of vehicular paths is a common phenomenon in the inner area of signalized intersections due to heterogeneous driver behavior and interactions.This study aims to develop an explainable neural network-based model to describe the vehicle path dispersion by exploring the relationship between the path dispersion and external factors.A backpropagation neural network model was established to analyze the effects of external factors on the dispersion of through and left-turn paths based on real trajectory data collected from 20 intersections in Shanghai,China.Twelve influencing factors in varying geometric,traffic,signalization,and traffic management conditions were considered.The predictive power and transferability of the model were verified by applying the trained model on the four new intersections.The contributions of the influencing factors on the path dispersion were explored based on the neural interpretation diagram,relative importance of influencing factors,and sensitivity analysis to offer explanatory insights for the proposed model.The results show that the mean absolute percentage errors of the path dispersion models for the through and left-turn movements are only 14.67%and 17.65%,respectively.The through path dispersion is primarily influenced by the number of exit lanes,the offset degree between the approach and exit lanes,and the traffic saturation degree on the through lane.In contrast,the path dispersion of the left turn is mainly affected by the number of exit lanes,the left-turn angle,and the setting of guide lines.
基金The research is also supported by the Shanghai sailing project(Grant ID 20YF1451700)Shanghai Municipal Bureau of Ecology and Environment(Grant ID Huhuanke 2022-25).
文摘Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used vehicle emission estimation model.We first design a protocol of converting percentage values of rotating speed and torque of engine to second-by-second vehicle speed to accommodate the differences between driving cycles adopted in local emission standards and those used in MOVES.In order to identify the best model year for estimating emissions under different local emission standards,we propose an approach of comparing emission outcomes rather than emission factors,considering the differences in unit used between MOVES and emission standards.To calculate road seg mentlevel emission factors,we weight original factors by integrating vehicle fleet informa tion which contains the shares of vehicles under different emission standards and at different ages.We apply the approach to a major freight corridor area in Shanghai and cal culate emission factors by air pollutant,average speed of road sections,and road type.Dynamic emissions of each road section per hour are calculated to reflect the spatial dis tribution of truck emissions.The research outcomes may help local departments,especially in developing countries,better estimate freight vehicle emissions and make policies corre spondingly to control their impacts on public health.
基金support of the National Natural Science Foundation of China(Grant No.72261021)the Science and Technology R&D Project of Yunnan Communications Investment&Construction Group CO,LTD.(Grant No.YCIC-YF-2021-05)the Research Project on Key Technologies for Road Safety and Disaster Mitigation and Prevention,Department of Transport of Yunnan Province,China(Grant No.SZKM202231022).
文摘Rapid advancements in automated vehicles(AVs)technology have transformed the measurability,controllability and unpredictability of transportation systems.Evaluating driving risk and effectively managing driving behaviours is critical.AVs should be enabled to identify,analyse,evaluate and devise effective countermeasures for driving risk by autonomously learning from human driving experiences.This learning will enhance the interactive decision-making capabilities and achieve driving behaviours that reflect human-like logic.The primary challenge lies in integrating human-like logic and driving risk constraints based on behavioural decision-making outcomes.This integration is crucial to align the AVs’cognitive levels-movement,comprehension,memory and inference-more closely with human driving necessities,habits and styles.Such alignment holds the potential to improve the prediction and planning of future actions and facilitate the development of motion planning schemes geared towards minimizing driving risk.We performed a comprehensive review of AVs’behavioural decision-making and intelligent motion-planning research from 2000 to 2023 from four key perspectives-driving risk,human-like logic,behavioural decision making and motion planning.Based on the Web of Science and China National Knowledge Internet database,the results of our review indicate that significant progress has been made in AV behavioural decision making and intelligent motion planning over time.When AVs and human-driven vehicles coexist,greater incorporation of human-like logic is required.Guided by these findings,we delineate future development directions and propose a research paradigm for human-like logic and a research framework for human-like logic-driven behavioural decision making and intelligent motion planning of AVs.
基金supported by the National Natural Science Foundation of China,grant number 51878062the National Key Research and Development Program of China,grant number 2019YFB1600300the National Science Foundation of Shaanxi Province,grant number 2020JQ-387。
文摘The purpose of this paper is to provide a summary of a quick overview of the latest developments and unprecedented opportunities for scholars who want to set foot in the field of traditional taxi and online car-hailing(TTOC).From the perspectives of peoples(e.g.,passenger,driver,and policymaker),vehicle,road,and environment,this paper describes the current research status of TTOC's big data in six hot topics,including the ridership factor,spatio-temporal distribution and travel behavior,cruising strategy and passenger service market partition,route planning,transportation emission and new-energy,and TTOC's data extensional application.These topics were included in five mainstreams as follows:(1)abundant studies often focus only on determinant analysis on given transportation(taxi,transit,online car-hailing);the exploration of ridership patterns for a multimodal transportation mode is rare;furthermore,multiple aspects of factors were not considered synchronously in a wide time span;(2)travel behavior research mainly concentrates on the commuting trips and distribution patterns of various travel indices(e.g.,distance,displacement,time);(3)the taxi driver-searching strategy can be divided into autopsychic cruising and system dispatching;(4)the spatio-temporal distribution character of TTOC's fuel consumption(FC)and greenhouse gas(GHG)emissions has become a hotspot recently,and there has been a recommendation for electric taxi(ET)in urban cities to decrease transportation congestion is proposed;and(5)based on TTOC and point of interest(POI)multi-source data,many machine learning algorithms were used to predict travel condition indices,land use,and travel behavior.Then,the main bottlenecks and research directions that can be explored in the future are discussed.We hope this result can provide an overview of current fundamental aspects of TTOC's utilization in the urban area.
基金the National Natural Science Foundation of China under Grant No.71971140the Soft Science Research Project of Shanghai No.22692194500the Pujiang Program under Grant No.21PJC085.
文摘Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.Findings–The proposed model has a promising control effect under different geometric controlled conditions.Moreover,the proposed model performs robustly under various safety time headways,lengths of the CLL and green times of the main signal.Originality/value–This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections.The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness。
基金supported by the Joint Laboratory for Internet of Vehicles,Ministry of Education–China Mobile Communications Corporation under Project No.ICV-KF2019-01the National Key Research and Development Program of China under Grant 2018YFB1600703.
文摘Purpose–This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency.By introducing the theory of moving block section for high-speed train control,a speed guidance model based on the quasi-moving block speed guidance(QMBSG)is proposed to direct platoon including human-driven vehicles and connected vehicles(CV)through the intersection coordinately.Design/methodology/approach–In this model,the green time of the intersection is divided into multiple block intervals according to the minimal safety headway.Connected vehicles can pass through the intersection by following the block interval using the QMBSG model.The block interval is assigned dynamically according to the traveling relation of HV and CV,when entering the communication range of the intersection.To validate the comprehensive guidance effect of the proposed model,a general evaluation function(GEF)is established.Compared to CVs without speed guidance,the simulation results show that the GEF of QMBSG model has an obvious improvement.Findings–Compared to CVs without speed guidance,the simulation results show that the GEF of QMBSG model has an obvious improvement.Also,compared to the single intersection speed guidance model,the GEF value of the QMBSG model improves over 17.1%.To further explore the guidance effect,the impact of sensitivity factors of the CVs’environment,such as intersection environment,communication range and penetration rate(PR)is analyzed.When the PR reaches 75.0%,the GEF value will change suddenly and the model guidance effect will be significantly improved.This paper also analyzes the impact of the length of block interval under different PR and traffic demands.It is found that the proposed model has a better guidance effect when the length of the block section is 2 s,which facilitates traffic congestion alleviation of the intersection in practice.Originality/value–Based on the aforementioned discussion,the contributions of this paper are three-fold.Based on the traveling information of HV/CV and the signal phase and timing plans,the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately,by following the block interval assigned dynamically.Considering comprehensively the indexes of mobility,safety and environment,a GEF is provided to evaluate the guidance effect of vehicles through the intersection.Sensitivity analysis is carried out on the QMBSG model.The key communication and traffic parameters of the CV environment are analyzed,such as path attenuation,PR,etc.Finally,the effect of the length of block interval is explored.
基金Supported by Qinghai University Youth Research Fund,China(Grant No.2023-QGY-15)。
文摘Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.
基金supported by the National Key Research and Development Program of China(2023YFB4301900)the National Natural Science Foundation of China(52125208)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(2023A1515012895)the Department of Science and Technology of Guangdong Province(2021QN02S161).
文摘The fragmented design of intelligent transportation systems creates isolated intelligent systems.Resource competition and information gaps are fierce and widespread,worsening traffic issues and degrading overall service levels.Therefore,empowered by advanced technologies,an evolution toward an autonomous transportation system(ATS)is observed.This evolution aims to develop a collaborative and sustainable ecosystem,prompting interoperability within the cloud-edge-device continuum.
基金supported by the National Natural Science Foundation of China(No.51178149)
文摘Many studies suggest that more crashes occur due to mixed traffic flow at unsignalized intersections. However, very little is known about the injury severity of these crashes. The objective of this study is therefore to investigate how contributory factors affect crash injury severity at unsignalized intersections. The dataset used for this analysis derived from police crash reports from Dec. 2006 to Apr. 2009 in Heilongjiang Province, China. An ordered probit model was developed to predict the probability that the injury severity of a crash will be one of four levels ： no injury, slight injury, severe injury, and fatal injury. The injury severity of a crash was evaluated in terms of the most severe injury sustained by any person involved in the crash. Results from the present study showed that different factors had varying effects on crash injury severity. Factors found to result in the increased probability of serious injuries include adverse weather, sideswiping with pedestrians on poor surface, the interaction of rear-ends and the third-class highway, winter night without illumination, and the interaction between traffic signs or markings and the third-class highway. Although there are some limitations in the current study, this study provides more insights into crash injury severity at unsignalized intersections.
