Knowledge graph technology play a more and more important role in various fields of industry and academia.This paper firstly introduces the general framework of the knowledge graph construction,which includes three st...Knowledge graph technology play a more and more important role in various fields of industry and academia.This paper firstly introduces the general framework of the knowledge graph construction,which includes three stages:information extraction,knowledge fusion and knowledge processing.In order to improve the efficiency of quality and safety supervision of transportation engineering construction,this paper constructs a knowledge graph by acquiring multi-sources heterogeneous data from supervision of transportation engineering quality and safety.It employs a bottom-up construction strategy and some natural language processing methods to solve the problems of the knowledge extraction for transportation engineering construction.We use the entity relation extraction method to extract the entity triples from the multi-sources heterogeneous data,and then employ knowledge inference to complete the edges in the constructed knowledge graph,finally perform quality evaluation to add the valid triples to the knowledge graph for updating.Subgraph matching technology is also exploited to retrieve the constructed knowledge graph for efficiently acquiring the useful knowledge about the quality and safety of transportation engineering projects.The results show that the constructed knowledge graph provides a practical and valuable tool for the quality and safety supervision of transportation engineering construction.展开更多
In recent years,with the development of road and railway transportation industries,a variety of complicated decisionmaking problems have emerged in real-world applications.It is urgent to analyze these problems from t...In recent years,with the development of road and railway transportation industries,a variety of complicated decisionmaking problems have emerged in real-world applications.It is urgent to analyze these problems from the perspective of theoretical and methodological innovations,and provide methods in management,decision-making and application so as to achieve efficient operations of traffic and transportation systems.These problems have展开更多
本文从办刊体制、编辑人员专业水平、期刊评价体制、学术界唯SCI论四个方面对高校英文科技期刊的发展弊端进行了调研,总结出Journal of Traffic and Transportation Engineering (English Edition)(JTTE,交通运输工程学报(英文版))创刊...本文从办刊体制、编辑人员专业水平、期刊评价体制、学术界唯SCI论四个方面对高校英文科技期刊的发展弊端进行了调研,总结出Journal of Traffic and Transportation Engineering (English Edition)(JTTE,交通运输工程学报(英文版))创刊以来所采取的提升期刊国际影响力的措施和方法:在“中国科技期刊卓越行动计划”的支持下,JTTE充分发挥自身优势,依靠长安大学在道路工程、交通运输领域强大的学术影响力,团结作者、学者、编委三方力量,将期刊介绍给全世界,从而提高了期刊的国际显示度;在新媒体背景下,期刊利用跨平台推荐、社交媒体推广等方式宣传期刊内容,加快了期刊内容传播。展开更多
Emergency response activity relies on transportation networks. Emergency facility location interacts with transportation networks clearly. This review is aimed to provide a combined framework for emergency facility lo...Emergency response activity relies on transportation networks. Emergency facility location interacts with transportation networks clearly. This review is aimed to provide a combined framework for emergency facility location in transportation networks. The article reveals emergency response activities research clusters, issues, and objectives according to keywords co-occurrence analysis. Four classes of spatial separation models in transportation networks, including distance, routing, accessibility, and travel time are introduced. The stochastic and time-dependent characteristics of travel time are described. Travel time estimation and prediction method, travel time under emergency vehicle preemption,transportation network equilibrium method, and travel time in degradable networks are demonstrated. The emergency facilities location models interact with transportation networks, involving location-routing model, location models embedded with accessibility,location models embedded with travel time, and location models employing mathematical program with equilibrium constraints are reviewed. We then point out the-state-of-art challenges: ilities-oriented, evolution landscape and sequential decision modelling, datadriven optimization approach, and machine learning-based algorithms.展开更多
The most salient problems of transit vehicle service in Latin American intermediate cities include:the high number of passengers involved in traffic accidents;traffic congestion caused by transit vehicles,and pollutio...The most salient problems of transit vehicle service in Latin American intermediate cities include:the high number of passengers involved in traffic accidents;traffic congestion caused by transit vehicles,and pollution generated by these vehicles,which increases in high congestion scenarios.To improve upon this situation,a research was conducted on the transit vehicle tracking service,which is a basic service for implementing mobility solutions for the aforementioned problems,the most relevant characteristics of this service for the context of Latin American intermediate cities were identified,and an implementation was proposed.This paper presents the four stages of the study:(a)a review of the state-of-the-art of services or systems related to vehicle tracking,including wireless communications technologies,implemented sustainability approaches,usage of special algorithms for efficiency improvement,and the intelligent transportation system(ITS)architecture used as a basis;(b)the process of identifying relevant characteristics of the service for a given context;(c)proposal of an ITS architecture for this service in an intermediate city,its requirements and the suggested technologies;and(d)development of experiments for validating usage of the key suggested technologies.The review allowed to identify the main service characteristics,with regard to vehicle positioning technologies,the recommended wireless communication technology(long range,LoRa),energy consumption considerations,and use of artificial intelligence(AI)to calculate waiting time of users at bus stops.Finally,an ITS architecture for the city of Popayan(Colombian city)considering the aforementioned characteristics is proposed,and the experiments related to the use of these technologies are described in detail.展开更多
Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response an...Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events.To summarize the latest research progress,we collected 511VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software.Subsequently,we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords,research gaps,and future works.The results show that domestic scholars and research organizations held an unqualified advantage regarding the number of published papers.However,these organizations with the most publications performed poorly regarding the number of literature citations.China and the US have contributed the vast majority of the literature,and there are close collaborations between researchers from both countries.The optimization model of VREMD can be divided into single-,multi-,and joint-objective models.The shortest travel time is the most common optimization objective in the single-objective optimization model.Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously.In recent literature,scholars have focused on the impact of uncertainty and special events(e.g.,COVID-19)on VREMD.Moreover,some scholars focus on joint optimization models to optimize vehicle routes and central locations(or material allocation)simultaneously.Solution algorithms can be divided into two primary categories,i.e.,mathematical planning methods and intelligent evolutionary algorithms.The branch and bound algorithm is the most dominant mathematical planning algorithm,while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms.It is shown that the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ)can effectively solve the multiobjective model of VREMD.To further improve the algorithm’s performance,researchers have proposed improved hybrid intelligent algorithms that combine the advantages of NSGA-Ⅱand certain other algorithms.Scholars have also proposed a series of optimization algorithms for specific scenarios.With the development of new technologies and computation methods,it will be exciting to construct optimization models that consider uncertainty,heterogeneity,and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.展开更多
Fresh agri-product emergency supply is crucial to secure the basic livelihood of residents at large-scale epidemic disease context. Considering the massive demand and limited transportation resources, this study integ...Fresh agri-product emergency supply is crucial to secure the basic livelihood of residents at large-scale epidemic disease context. Considering the massive demand and limited transportation resources, this study integrates multi-item packaging and vehicle routing with split delivery to improve the emergency supply capacity. Firstly, three specific objectives of fresh agri-product emergency supply at large-scale epidemic disease context are formulated, i.e., average response time, infectious risk possibility and transportation resource utilization. Then, a multi-item packaging strategy is proposed to consolidate different categories of fresh agri-products according to the food cold chain temperatures.An optimization model integrating multi-item packaging and vehicle routing with split delivery is developed to jointly decide the optimal packaging scheduling, vehicle assignment and delivery routing. Next, an improved genetic algorithm based on solution features (IGA-SF) is designed to solve the integrated model with multiple decision variables. Finally,a case on fresh agri-product emergency supply of Huangpi District, Wuhan in the context of the Corona Virus Disease 2019(COVID-19) is carried out to illustrate the efficiency and feasibility of the proposed model. The numerical results of medium-to-largescale cases demonstrate that the proposed IGA-SF could save 23.91% CPU time and 37.80% iteration number on average than genetic algorithm. This study could satisfy different emergency scenario requirements flexibly, and provide scientific decision support for provincial and national governments on fresh agri-product emergency supply.展开更多
Road safety modeling is a valuable strategy for promoting safe mobility,enabling the development of crash prediction models(CPM)and the investigation of factors contributing to crash occurrence.This modeling has tradi...Road safety modeling is a valuable strategy for promoting safe mobility,enabling the development of crash prediction models(CPM)and the investigation of factors contributing to crash occurrence.This modeling has traditionally used statistical techniques despite acknowledging the limitations of this kind of approach(specific assumptions and prior definition of the link functions),which provides an opportunity to explore alternatives such as the use of machine learning(ML)techniques.This study reviews papers that used ML techniques for the development of CPM.A systematic literature review protocol was conducted,that resulted in the analysis of papers and their systematization.Three types of models were identified:crash frequency,crash classification by severity,and crash frequency and severity.The first is a regression problem,the second,a classificatory one and the third can be approached either as a combination of the preceding two or as a regression model for the expected number of crashes by severity levels.The main groups of techniques used for these purposes are nearest neighbor classification,decision trees,evolutionary algorithms,support-vector machine,and artificial neural networks.The last one is used in many kinds of approaches given the ability to deal with both regression and classification problems,and also multivariate response models.This paper also presents the main performance metrics used to evaluate the models and compares the results,showing the clear superiority of the ML-based models over the statistical ones.In addition,it identifies the main explanatory variables used in the models,which shows the predominance of road-environmental aspects as the most important factors contributing to crash occurrence.The review fulfilled its objective,identifying the various approaches and the main research characteristics,limitations,and opportunities,and also highlighting the potential of the usage of ML in crash analyses.展开更多
Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding...Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections.Although dilemma zone definitions hold true in case of homogeneous traffic mix,a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition.Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies.For carrying out the research,study locations are chosen in such a way to reflect diversity in road geometry,traffic composition and signal characteristics.The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal.The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal.In the process of identifying the statistical significance of dilemma zone definitions,it has been found that under heterogeneous traffic condition,drivers behave differently as compared to homogenous traffic when it comes to dilemma zone.It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6%according to dilemma zone definition I whereas the definition II has yielded about 10.8%violation covering different vehicle types.The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%-6%.展开更多
Rapid transit(RT)systems are becoming increasingly attractive in the developing world as they improve transportation and mobility conditions in urban areas,reduce motorization impacts and offer high quality,yet cost e...Rapid transit(RT)systems are becoming increasingly attractive in the developing world as they improve transportation and mobility conditions in urban areas,reduce motorization impacts and offer high quality,yet cost effective services to travelers.Light rail transit(LRT)and bus rapid transit(BRT)are RT systems that combine high capacity with relatively low investment costs,and as such,they are preferred in developing countries over regular metro systems.This paper investigates traveler preferences over alternative,planned rapid transit options for the city of Multan,Pakistan.The analysis is based on a household information survey with over 2300 questionnaires completed via personal interviews.Intention to pay for improved PT services and choice between LRT and BRT systems are investigated,using appropriate econometric models.Findings of this study can assist in better understanding the factors and their effect on choice between BRT and LRT in developing countries.Results show that potential travelers,who prefer LRT are willing to pay more for better public transport services.On the other hand,commuters and elders express a taste towards BRT implementation.Based on model outputs policy makers can develop targeted marketing policies in order to promote BRT/LRT implementation andattract candidate travelers from different groups,improving the possibility that users would support a BRT or LRT project.展开更多
A synchronous optimization model for rehabilitation of existing two-way two-lane(TWTL)highways is proposed in this paper considering geometric modification and existing pavement rehabilitation. The rehabilitation proc...A synchronous optimization model for rehabilitation of existing two-way two-lane(TWTL)highways is proposed in this paper considering geometric modification and existing pavement rehabilitation. The rehabilitation process of existing roadways is categorized into geometric design modifications and pavement repairs. These two types of modification apply separately in roadway life-cycle because of the difference in nature of these repairs, which impose an extra cost and time of closure to road users and owners. This paper aims to address the modification of existing highways by a new approach linking the existing pavement condition and geometric configuration changes of the developed roadway to provide the optimum vertical alignment. The proposed procedure depends on various parameters of existing pavement condition, cross-section configuration, traffic volume and composition, and current alignment composure. In the first step, all these dependencies are explained and quantified with separate cost models. For each solution,the overall cost is calculated with a life-cycle cost analysis approach. Finally, a particle swarm optimization(PSO) based model is developed to find the optimum solution. The developed model was applied in two case studies with good and adverse geometric conditions. The results show that there is a critical condition in the roadway segments which have all these conditions:(1) the grade is more than three percent,(2) the grade is following with reverse grade, and(3) decommissioning of the asphalt concrete(or extended to lower layers) exist. The optimum solution in these critical conditions suggests the modification of the geometric configuration before the pavement rehabilitation in order to reduce the overall cost. In the absence of these conditions, the optimum alignment is more analogous with the existing alignment of the highway.展开更多
The District of Columbia currently uses the standard pedestrian warning signs and diagonal arrow plaques at a substantial number of uncontrolled crosswalks within the City.However, the widespread use of these measures...The District of Columbia currently uses the standard pedestrian warning signs and diagonal arrow plaques at a substantial number of uncontrolled crosswalks within the City.However, the widespread use of these measures appears to be ineffective in curbing the incidence of pedestrian involved crashes or pedestrian-vehicle conflicts. To compensate for the perceived lack of effectiveness of the standard pedestrian warning sign the District Department of Transportation developed a new side-of-street crossing sign to improve driver compliance based on pedestrian right-of-way laws.This study was aimed at determining the effectiveness(defined as the proportion of drivers approaching a crosswalk who stop or yield the right of way to a pedestrian in the crosswalk) of the experimental side-of-street pedestrian crossing sign compared to the standard sign, with and without rectangular rapid flashing beacons. Effectiveness of the side-of-street pedestrian sign and standard sign were observed at a total of 32 locations in the District over a one-year period using the “control” and “experimental” comparison approach. Video data for each location was obtained from March 2018 through February 2019 during typical weekdays for the morning and afternoon peak periods. The results of the study showed that the experimental signs with RRFBs provided higher driver compliance rates(yielding to pedestrians) compared to the standard signs for both the morning and afternoon peak periods. However, the differences in compliance rates for the experimental and standard signs were not statistically significant at a 95% confidence interval.Further evaluation of the signs is recommended using the “before” and “after” approach in addition to an assessment of crash statistics at the selected locations.展开更多
China’s traffic safety attracts increasing research interest.Official data show that crashes in the western region of China are more severe than those in the eastern region.However,research on crash severity in weste...China’s traffic safety attracts increasing research interest.Official data show that crashes in the western region of China are more severe than those in the eastern region.However,research on crash severity in western China is scarce.This study applied a hierarchical Bayesian logistic model to examine the significant factors related to crash and vehicle/driver levels and their heterogeneous impacts on the severity of drivers’ injury.Crash data were collected from Lintao,a rural mountainous county in western China.A variable was proposed to measure the relative difference between the crashworthiness of one vehicle and the aggressivity of the other vehicle in the mixed traffic flow.Results indicated that the majority of the total variance was induced by between-crash variance,showing the suitability of the utilized hierarchical modeling approach.One crash-level variable and six vehicle/driver-level variables,namely,road type,compatibility difference,age,vehicle type,drunk driving,driving unregistered vehicle,and driving years,significantly affected modeling drivers’ injury severities.Among these variables,road type(national and provincial),age(young and senior drivers),driving unregistered vehicle,and drunk driving tended to increase the odds of crash-related mortality.Driving years(new drivers with less than six years of driving experience) and vehicle type(heavy vehicle) were likely to decrease the probability of fatal outcomes.Compatibility difference was relatively significant,and the possibilities of mortality in single vehicle crashes were higher than those inmultivehicle and pedestrian-involved crashes.The developed methodology and estimation results provided insights into the internal mechanism of rural crashes and effective countermeasures to prevent rural crashes.展开更多
The global positioning system(GPS)has motivated rapid advances in mobility data collection.A massive amount of spatio-temporal information has made it possible to know where a person was and when,but not how and why(s...The global positioning system(GPS)has motivated rapid advances in mobility data collection.A massive amount of spatio-temporal information has made it possible to know where a person was and when,but not how and why(s)he travelled,creating the need for inference models.Compared with mode detection,purpose imputation has been insufficiently studied.However,the relative lack of attention to purpose identification does not mean that this field has not emerged.For this paper,which is the first review dedicated to inferringtrip purposes from GPS data,1162 non-duplicate papers from four databases(Scopus,Web of Science,ScienceDirect and TRID)were screened,and a corpus of 25 publications was selected for examination.Based on these papers,the purpose imputation problem is defined in the contexts of the evolution of GPS-based travel surveys and two research domains,transportation science(TS)and human geography(HG).Subsequently,three steps of the purpose detection process,namely trip end detection,input feature selection and main algorithms and validation,are surveyed.During these procedures,the differences between studies in TS and those in HG are highlighted.Finally,unresolved issues related to data and feature selection,algorithms and assessment are discussed substantially to provide potential research directions.This review may be an inform ative reference for those newly accessing the GPS-based purpose imputation field and/or intending to develop solutions to this problem.展开更多
One of the critical areas of road safety is motorcycle safety. Motorcyclists are more vulnerable to injuries than occupants of other motor vehicles when involved in crashes.Researchers have studied the relationships b...One of the critical areas of road safety is motorcycle safety. Motorcyclists are more vulnerable to injuries than occupants of other motor vehicles when involved in crashes.Researchers have studied the relationships between motorcycle crash severity and crash contributing factors. They are crash characteristics, roadway geometric design features,traffic characteristics, socio-demographics and environmental conditions. However, few researchers considered unobserved heterogeneity effects when modeling motorcycle crash injury severities, let alone interaction effects. In this research, motorcycle crashes in Wyoming that occurred from 2008 to 2017 were analyzed. Specifically, the injury severities of single motorcycle crashes and multiple vehicle crashes involving motorcycles were modeled. The response was whether the motorcycle crash incurred an incapacitating injury or fatality or not. The binary logistic regression and mixed binary logistic regression modeling structures were implemented. The mixed models revealed effects that otherwise would have been undisclosed in the binary logistic regression models’ results. According to the results of single motorcycle crashes, the majority of motorcycle-animal crashes and of motorcycle-barrier crashes were likely to be severe relative to other single motorcycle crashes. It was also found that horizontal curves increased the risk of severe injuries.Young riders were found to be less at risk of being gravely injured in single motorcycle crashes than older riders as well. Furthermore, riding under the influence and high posted speed limits increased the odds of severe crashes regardless of whether the crashes were single motorcycle crashes or multiple vehicle crashes involving motorcycles. Additionally,the mixed models uncovered interaction effects and unobserved effects pertaining to speed limits.展开更多
Introduction:The emergent wetland species Typha domingensis(cattail)is a native Florida Everglades monocotyledonous macrophyte.It has become invasive due to anthropogenic disturbances and is out-competing other vegeta...Introduction:The emergent wetland species Typha domingensis(cattail)is a native Florida Everglades monocotyledonous macrophyte.It has become invasive due to anthropogenic disturbances and is out-competing other vegetation in the region,especially in areas historically dominated by Cladium jamaicense(sawgrass).There is a need for a quantitative,deterministic model in order to accurately simulate the regional-scale cattail dynamics in the Everglades.Methods:The Regional Simulation Model(RSM),combined with the Transport and Reaction Simulation Engine(TARSE),was adapted to simulate ecology.This provides a framework for user-defineable equations and relationships and enables multiple theories with different levels of complexity to be tested simultaneously.Five models,or levels,of increasing complexity were used to simulate cattail dynamics across Water Conservation Area 2A(WCA2A),which is located just south of Lake Okeechobee,in Florida,USA.These levels of complexity were formulated to correspond with five hypotheses regarding the growth and spread of cattail.The first level of complexity assumed a logistic growth pattern to test whether cattail growth is density dependent.The second level of complexity built on the first and included a Habitat Suitability Index(HSI)factor influenced by water depth to test whether this might be an important factor for cattail expansion.The third level of complexity built on the second and included an HSI factor influenced by soil phosphorus concentration to test whether this is a contributing factor for cattail expansion.The fourth level of complexity built on the third and included an HSI factor influenced by(a level 1–simulated)sawgrass density to determine whether sawgrass density impacted the rate of cattail expansion.The fifth level of complexity built on the fourth and included a feedback mechanism whereby the cattail densities influenced the sawgrass densities to determine the impact of inter-species interactions on the cattail dynamics.Results:All the simulation results from the different levels of complexity were compared to observed data for the years 1995 and 2003.Their performance was analyzed using a number of different statistics that each represent a different perspective on the ecological dynamics of the system.These statistics include box-plots,abundance-area curves,Moran’s I,and classified difference.The statistics were summarized using the Nash-Sutcliffe coefficient.The results from all of these comparisons indicate that the more complex level 4 and level 5 models were able to simulate the observed data with a reasonable degree of accuracy.Conclusions:A user-defineable,quantitative,deterministic modeling framework was introduced and tested against various hypotheses.It was determined that the more complex models(levels 4 and 5)were able to adequately simulate the observed patterns of cattail densities within the WCA2A region.These models require testing for uncertainty and sensitivity of their various parameters in order to better understand them but could eventually be used to provide insight for management decisions concerning the WCA2A region and the Everglades in general.展开更多
基金This work was supported by Scientific Research Project of Department of Transportation of Hunan Province under Grant No.201814.
文摘Knowledge graph technology play a more and more important role in various fields of industry and academia.This paper firstly introduces the general framework of the knowledge graph construction,which includes three stages:information extraction,knowledge fusion and knowledge processing.In order to improve the efficiency of quality and safety supervision of transportation engineering construction,this paper constructs a knowledge graph by acquiring multi-sources heterogeneous data from supervision of transportation engineering quality and safety.It employs a bottom-up construction strategy and some natural language processing methods to solve the problems of the knowledge extraction for transportation engineering construction.We use the entity relation extraction method to extract the entity triples from the multi-sources heterogeneous data,and then employ knowledge inference to complete the edges in the constructed knowledge graph,finally perform quality evaluation to add the valid triples to the knowledge graph for updating.Subgraph matching technology is also exploited to retrieve the constructed knowledge graph for efficiently acquiring the useful knowledge about the quality and safety of transportation engineering projects.The results show that the constructed knowledge graph provides a practical and valuable tool for the quality and safety supervision of transportation engineering construction.
文摘In recent years,with the development of road and railway transportation industries,a variety of complicated decisionmaking problems have emerged in real-world applications.It is urgent to analyze these problems from the perspective of theoretical and methodological innovations,and provide methods in management,decision-making and application so as to achieve efficient operations of traffic and transportation systems.These problems have
文摘本文从办刊体制、编辑人员专业水平、期刊评价体制、学术界唯SCI论四个方面对高校英文科技期刊的发展弊端进行了调研,总结出Journal of Traffic and Transportation Engineering (English Edition)(JTTE,交通运输工程学报(英文版))创刊以来所采取的提升期刊国际影响力的措施和方法:在“中国科技期刊卓越行动计划”的支持下,JTTE充分发挥自身优势,依靠长安大学在道路工程、交通运输领域强大的学术影响力,团结作者、学者、编委三方力量,将期刊介绍给全世界,从而提高了期刊的国际显示度;在新媒体背景下,期刊利用跨平台推荐、社交媒体推广等方式宣传期刊内容,加快了期刊内容传播。
基金partly supported by the National Science Foundation of China under Grants 51008160China Postdoctoral Science Foundation (20080430686)+1 种基金Fundamental Research Funds for the Central Universities of China (NJAU: SKZK2015005)Talent Startup Fund of College of Engineering in NJAU of China (RCQD16-01)。
文摘Emergency response activity relies on transportation networks. Emergency facility location interacts with transportation networks clearly. This review is aimed to provide a combined framework for emergency facility location in transportation networks. The article reveals emergency response activities research clusters, issues, and objectives according to keywords co-occurrence analysis. Four classes of spatial separation models in transportation networks, including distance, routing, accessibility, and travel time are introduced. The stochastic and time-dependent characteristics of travel time are described. Travel time estimation and prediction method, travel time under emergency vehicle preemption,transportation network equilibrium method, and travel time in degradable networks are demonstrated. The emergency facilities location models interact with transportation networks, involving location-routing model, location models embedded with accessibility,location models embedded with travel time, and location models employing mathematical program with equilibrium constraints are reviewed. We then point out the-state-of-art challenges: ilities-oriented, evolution landscape and sequential decision modelling, datadriven optimization approach, and machine learning-based algorithms.
基金Authors wish to thank Universidad del Cauca(Telematics Department)and Universidad Icesi(ICT Department)for supporting this research.
文摘The most salient problems of transit vehicle service in Latin American intermediate cities include:the high number of passengers involved in traffic accidents;traffic congestion caused by transit vehicles,and pollution generated by these vehicles,which increases in high congestion scenarios.To improve upon this situation,a research was conducted on the transit vehicle tracking service,which is a basic service for implementing mobility solutions for the aforementioned problems,the most relevant characteristics of this service for the context of Latin American intermediate cities were identified,and an implementation was proposed.This paper presents the four stages of the study:(a)a review of the state-of-the-art of services or systems related to vehicle tracking,including wireless communications technologies,implemented sustainability approaches,usage of special algorithms for efficiency improvement,and the intelligent transportation system(ITS)architecture used as a basis;(b)the process of identifying relevant characteristics of the service for a given context;(c)proposal of an ITS architecture for this service in an intermediate city,its requirements and the suggested technologies;and(d)development of experiments for validating usage of the key suggested technologies.The review allowed to identify the main service characteristics,with regard to vehicle positioning technologies,the recommended wireless communication technology(long range,LoRa),energy consumption considerations,and use of artificial intelligence(AI)to calculate waiting time of users at bus stops.Finally,an ITS architecture for the city of Popayan(Colombian city)considering the aforementioned characteristics is proposed,and the experiments related to the use of these technologies are described in detail.
基金the National Natural Science Foundation of China(51808187,52062027)the Fundamental Research Funds for the Central Universities(B210202035)+2 种基金the"Double-First Class"Major Research Programs,Educational Department of Gansu Province(GSSYLXM-04)the Soft Science Special Project of Gansu Basic Research PIan(22JR4ZA035)the Gansu Provincial Science and Technology Major Special Project-Enterprise Innovation Consortium Project(22ZD6GA010)。
文摘Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events.To summarize the latest research progress,we collected 511VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software.Subsequently,we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords,research gaps,and future works.The results show that domestic scholars and research organizations held an unqualified advantage regarding the number of published papers.However,these organizations with the most publications performed poorly regarding the number of literature citations.China and the US have contributed the vast majority of the literature,and there are close collaborations between researchers from both countries.The optimization model of VREMD can be divided into single-,multi-,and joint-objective models.The shortest travel time is the most common optimization objective in the single-objective optimization model.Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously.In recent literature,scholars have focused on the impact of uncertainty and special events(e.g.,COVID-19)on VREMD.Moreover,some scholars focus on joint optimization models to optimize vehicle routes and central locations(or material allocation)simultaneously.Solution algorithms can be divided into two primary categories,i.e.,mathematical planning methods and intelligent evolutionary algorithms.The branch and bound algorithm is the most dominant mathematical planning algorithm,while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms.It is shown that the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ)can effectively solve the multiobjective model of VREMD.To further improve the algorithm’s performance,researchers have proposed improved hybrid intelligent algorithms that combine the advantages of NSGA-Ⅱand certain other algorithms.Scholars have also proposed a series of optimization algorithms for specific scenarios.With the development of new technologies and computation methods,it will be exciting to construct optimization models that consider uncertainty,heterogeneity,and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.
基金supported by National Natural Science Foundation of China (71803084)Humanity and Social Science Youth Foundation of Ministry of Education of China (17YJC630048)Fundamental Research Funds for the Central Universities (NJAU: SKCX2020009)。
文摘Fresh agri-product emergency supply is crucial to secure the basic livelihood of residents at large-scale epidemic disease context. Considering the massive demand and limited transportation resources, this study integrates multi-item packaging and vehicle routing with split delivery to improve the emergency supply capacity. Firstly, three specific objectives of fresh agri-product emergency supply at large-scale epidemic disease context are formulated, i.e., average response time, infectious risk possibility and transportation resource utilization. Then, a multi-item packaging strategy is proposed to consolidate different categories of fresh agri-products according to the food cold chain temperatures.An optimization model integrating multi-item packaging and vehicle routing with split delivery is developed to jointly decide the optimal packaging scheduling, vehicle assignment and delivery routing. Next, an improved genetic algorithm based on solution features (IGA-SF) is designed to solve the integrated model with multiple decision variables. Finally,a case on fresh agri-product emergency supply of Huangpi District, Wuhan in the context of the Corona Virus Disease 2019(COVID-19) is carried out to illustrate the efficiency and feasibility of the proposed model. The numerical results of medium-to-largescale cases demonstrate that the proposed IGA-SF could save 23.91% CPU time and 37.80% iteration number on average than genetic algorithm. This study could satisfy different emergency scenario requirements flexibly, and provide scientific decision support for provincial and national governments on fresh agri-product emergency supply.
基金the Instituto Federal Goiano(IFGoiano)(Goiano Federal Institute)for the financial support it providedsupport from the Coordenagao de Aperfeigoamento de Pessoal de Nivel Superior-Brazil(CAPES)-Financing Code 001(Coordination of Improvement of Higher Education Personnel)the Fundagao para a Ciencia and Tecnologia-Portugal-(FCT)(Science and Technology Foundation)under the project"Mobilidade Urbana SustentaveleSegura"(Safe and Sustainable Urban Mobility)of which this research is a part。
文摘Road safety modeling is a valuable strategy for promoting safe mobility,enabling the development of crash prediction models(CPM)and the investigation of factors contributing to crash occurrence.This modeling has traditionally used statistical techniques despite acknowledging the limitations of this kind of approach(specific assumptions and prior definition of the link functions),which provides an opportunity to explore alternatives such as the use of machine learning(ML)techniques.This study reviews papers that used ML techniques for the development of CPM.A systematic literature review protocol was conducted,that resulted in the analysis of papers and their systematization.Three types of models were identified:crash frequency,crash classification by severity,and crash frequency and severity.The first is a regression problem,the second,a classificatory one and the third can be approached either as a combination of the preceding two or as a regression model for the expected number of crashes by severity levels.The main groups of techniques used for these purposes are nearest neighbor classification,decision trees,evolutionary algorithms,support-vector machine,and artificial neural networks.The last one is used in many kinds of approaches given the ability to deal with both regression and classification problems,and also multivariate response models.This paper also presents the main performance metrics used to evaluate the models and compares the results,showing the clear superiority of the ML-based models over the statistical ones.In addition,it identifies the main explanatory variables used in the models,which shows the predominance of road-environmental aspects as the most important factors contributing to crash occurrence.The review fulfilled its objective,identifying the various approaches and the main research characteristics,limitations,and opportunities,and also highlighting the potential of the usage of ML in crash analyses.
基金The authors would like to thank senior colleagues and technical staff for their continuous support for carrying out this project as well as director,Central Road Research Institute,New Delhi,for allowing us to take up this work as an in-house R&D project(OLP-0597).
文摘Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections.Although dilemma zone definitions hold true in case of homogeneous traffic mix,a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition.Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies.For carrying out the research,study locations are chosen in such a way to reflect diversity in road geometry,traffic composition and signal characteristics.The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal.The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal.In the process of identifying the statistical significance of dilemma zone definitions,it has been found that under heterogeneous traffic condition,drivers behave differently as compared to homogenous traffic when it comes to dilemma zone.It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6%according to dilemma zone definition I whereas the definition II has yielded about 10.8%violation covering different vehicle types.The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%-6%.
基金part of a consultancy project funded by the Government of Punjab and the Punjab Metrobus Authority(www.pma.punjab.gov.pk)。
文摘Rapid transit(RT)systems are becoming increasingly attractive in the developing world as they improve transportation and mobility conditions in urban areas,reduce motorization impacts and offer high quality,yet cost effective services to travelers.Light rail transit(LRT)and bus rapid transit(BRT)are RT systems that combine high capacity with relatively low investment costs,and as such,they are preferred in developing countries over regular metro systems.This paper investigates traveler preferences over alternative,planned rapid transit options for the city of Multan,Pakistan.The analysis is based on a household information survey with over 2300 questionnaires completed via personal interviews.Intention to pay for improved PT services and choice between LRT and BRT systems are investigated,using appropriate econometric models.Findings of this study can assist in better understanding the factors and their effect on choice between BRT and LRT in developing countries.Results show that potential travelers,who prefer LRT are willing to pay more for better public transport services.On the other hand,commuters and elders express a taste towards BRT implementation.Based on model outputs policy makers can develop targeted marketing policies in order to promote BRT/LRT implementation andattract candidate travelers from different groups,improving the possibility that users would support a BRT or LRT project.
文摘A synchronous optimization model for rehabilitation of existing two-way two-lane(TWTL)highways is proposed in this paper considering geometric modification and existing pavement rehabilitation. The rehabilitation process of existing roadways is categorized into geometric design modifications and pavement repairs. These two types of modification apply separately in roadway life-cycle because of the difference in nature of these repairs, which impose an extra cost and time of closure to road users and owners. This paper aims to address the modification of existing highways by a new approach linking the existing pavement condition and geometric configuration changes of the developed roadway to provide the optimum vertical alignment. The proposed procedure depends on various parameters of existing pavement condition, cross-section configuration, traffic volume and composition, and current alignment composure. In the first step, all these dependencies are explained and quantified with separate cost models. For each solution,the overall cost is calculated with a life-cycle cost analysis approach. Finally, a particle swarm optimization(PSO) based model is developed to find the optimum solution. The developed model was applied in two case studies with good and adverse geometric conditions. The results show that there is a critical condition in the roadway segments which have all these conditions:(1) the grade is more than three percent,(2) the grade is following with reverse grade, and(3) decommissioning of the asphalt concrete(or extended to lower layers) exist. The optimum solution in these critical conditions suggests the modification of the geometric configuration before the pavement rehabilitation in order to reduce the overall cost. In the absence of these conditions, the optimum alignment is more analogous with the existing alignment of the highway.
基金District Department of Transportation for funding and contributing to this study(Grant ID#:HU-0009253)。
文摘The District of Columbia currently uses the standard pedestrian warning signs and diagonal arrow plaques at a substantial number of uncontrolled crosswalks within the City.However, the widespread use of these measures appears to be ineffective in curbing the incidence of pedestrian involved crashes or pedestrian-vehicle conflicts. To compensate for the perceived lack of effectiveness of the standard pedestrian warning sign the District Department of Transportation developed a new side-of-street crossing sign to improve driver compliance based on pedestrian right-of-way laws.This study was aimed at determining the effectiveness(defined as the proportion of drivers approaching a crosswalk who stop or yield the right of way to a pedestrian in the crosswalk) of the experimental side-of-street pedestrian crossing sign compared to the standard sign, with and without rectangular rapid flashing beacons. Effectiveness of the side-of-street pedestrian sign and standard sign were observed at a total of 32 locations in the District over a one-year period using the “control” and “experimental” comparison approach. Video data for each location was obtained from March 2018 through February 2019 during typical weekdays for the morning and afternoon peak periods. The results of the study showed that the experimental signs with RRFBs provided higher driver compliance rates(yielding to pedestrians) compared to the standard signs for both the morning and afternoon peak periods. However, the differences in compliance rates for the experimental and standard signs were not statistically significant at a 95% confidence interval.Further evaluation of the signs is recommended using the “before” and “after” approach in addition to an assessment of crash statistics at the selected locations.
基金The research reported in this paper is part of the project supported by the National Natural Science Foundation of China (71871123)。
文摘China’s traffic safety attracts increasing research interest.Official data show that crashes in the western region of China are more severe than those in the eastern region.However,research on crash severity in western China is scarce.This study applied a hierarchical Bayesian logistic model to examine the significant factors related to crash and vehicle/driver levels and their heterogeneous impacts on the severity of drivers’ injury.Crash data were collected from Lintao,a rural mountainous county in western China.A variable was proposed to measure the relative difference between the crashworthiness of one vehicle and the aggressivity of the other vehicle in the mixed traffic flow.Results indicated that the majority of the total variance was induced by between-crash variance,showing the suitability of the utilized hierarchical modeling approach.One crash-level variable and six vehicle/driver-level variables,namely,road type,compatibility difference,age,vehicle type,drunk driving,driving unregistered vehicle,and driving years,significantly affected modeling drivers’ injury severities.Among these variables,road type(national and provincial),age(young and senior drivers),driving unregistered vehicle,and drunk driving tended to increase the odds of crash-related mortality.Driving years(new drivers with less than six years of driving experience) and vehicle type(heavy vehicle) were likely to decrease the probability of fatal outcomes.Compatibility difference was relatively significant,and the possibilities of mortality in single vehicle crashes were higher than those inmultivehicle and pedestrian-involved crashes.The developed methodology and estimation results provided insights into the internal mechanism of rural crashes and effective countermeasures to prevent rural crashes.
基金the Ministry of Education and Training of Vietnam(The educational program 911)。
文摘The global positioning system(GPS)has motivated rapid advances in mobility data collection.A massive amount of spatio-temporal information has made it possible to know where a person was and when,but not how and why(s)he travelled,creating the need for inference models.Compared with mode detection,purpose imputation has been insufficiently studied.However,the relative lack of attention to purpose identification does not mean that this field has not emerged.For this paper,which is the first review dedicated to inferringtrip purposes from GPS data,1162 non-duplicate papers from four databases(Scopus,Web of Science,ScienceDirect and TRID)were screened,and a corpus of 25 publications was selected for examination.Based on these papers,the purpose imputation problem is defined in the contexts of the evolution of GPS-based travel surveys and two research domains,transportation science(TS)and human geography(HG).Subsequently,three steps of the purpose detection process,namely trip end detection,input feature selection and main algorithms and validation,are surveyed.During these procedures,the differences between studies in TS and those in HG are highlighted.Finally,unresolved issues related to data and feature selection,algorithms and assessment are discussed substantially to provide potential research directions.This review may be an inform ative reference for those newly accessing the GPS-based purpose imputation field and/or intending to develop solutions to this problem.
文摘One of the critical areas of road safety is motorcycle safety. Motorcyclists are more vulnerable to injuries than occupants of other motor vehicles when involved in crashes.Researchers have studied the relationships between motorcycle crash severity and crash contributing factors. They are crash characteristics, roadway geometric design features,traffic characteristics, socio-demographics and environmental conditions. However, few researchers considered unobserved heterogeneity effects when modeling motorcycle crash injury severities, let alone interaction effects. In this research, motorcycle crashes in Wyoming that occurred from 2008 to 2017 were analyzed. Specifically, the injury severities of single motorcycle crashes and multiple vehicle crashes involving motorcycles were modeled. The response was whether the motorcycle crash incurred an incapacitating injury or fatality or not. The binary logistic regression and mixed binary logistic regression modeling structures were implemented. The mixed models revealed effects that otherwise would have been undisclosed in the binary logistic regression models’ results. According to the results of single motorcycle crashes, the majority of motorcycle-animal crashes and of motorcycle-barrier crashes were likely to be severe relative to other single motorcycle crashes. It was also found that horizontal curves increased the risk of severe injuries.Young riders were found to be less at risk of being gravely injured in single motorcycle crashes than older riders as well. Furthermore, riding under the influence and high posted speed limits increased the odds of severe crashes regardless of whether the crashes were single motorcycle crashes or multiple vehicle crashes involving motorcycles. Additionally,the mixed models uncovered interaction effects and unobserved effects pertaining to speed limits.
文摘Introduction:The emergent wetland species Typha domingensis(cattail)is a native Florida Everglades monocotyledonous macrophyte.It has become invasive due to anthropogenic disturbances and is out-competing other vegetation in the region,especially in areas historically dominated by Cladium jamaicense(sawgrass).There is a need for a quantitative,deterministic model in order to accurately simulate the regional-scale cattail dynamics in the Everglades.Methods:The Regional Simulation Model(RSM),combined with the Transport and Reaction Simulation Engine(TARSE),was adapted to simulate ecology.This provides a framework for user-defineable equations and relationships and enables multiple theories with different levels of complexity to be tested simultaneously.Five models,or levels,of increasing complexity were used to simulate cattail dynamics across Water Conservation Area 2A(WCA2A),which is located just south of Lake Okeechobee,in Florida,USA.These levels of complexity were formulated to correspond with five hypotheses regarding the growth and spread of cattail.The first level of complexity assumed a logistic growth pattern to test whether cattail growth is density dependent.The second level of complexity built on the first and included a Habitat Suitability Index(HSI)factor influenced by water depth to test whether this might be an important factor for cattail expansion.The third level of complexity built on the second and included an HSI factor influenced by soil phosphorus concentration to test whether this is a contributing factor for cattail expansion.The fourth level of complexity built on the third and included an HSI factor influenced by(a level 1–simulated)sawgrass density to determine whether sawgrass density impacted the rate of cattail expansion.The fifth level of complexity built on the fourth and included a feedback mechanism whereby the cattail densities influenced the sawgrass densities to determine the impact of inter-species interactions on the cattail dynamics.Results:All the simulation results from the different levels of complexity were compared to observed data for the years 1995 and 2003.Their performance was analyzed using a number of different statistics that each represent a different perspective on the ecological dynamics of the system.These statistics include box-plots,abundance-area curves,Moran’s I,and classified difference.The statistics were summarized using the Nash-Sutcliffe coefficient.The results from all of these comparisons indicate that the more complex level 4 and level 5 models were able to simulate the observed data with a reasonable degree of accuracy.Conclusions:A user-defineable,quantitative,deterministic modeling framework was introduced and tested against various hypotheses.It was determined that the more complex models(levels 4 and 5)were able to adequately simulate the observed patterns of cattail densities within the WCA2A region.These models require testing for uncertainty and sensitivity of their various parameters in order to better understand them but could eventually be used to provide insight for management decisions concerning the WCA2A region and the Everglades in general.
