In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individua...In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.展开更多
This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport...This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.展开更多
This paper analyses the effectiveness of applying the Quick Response Freight Manual (QRFM) to model freight transportation. Typically, freight transportation is indirectly modeled or as an after-thought. Increasing fr...This paper analyses the effectiveness of applying the Quick Response Freight Manual (QRFM) to model freight transportation. Typically, freight transportation is indirectly modeled or as an after-thought. Increasing freight volumes, coupled with cost saving strategies such as just-in-time delivery systems, require that transportation policymakers analyze infrastructure needs and make investment decisions that explicitly include freight volumes as a component. This paper contains a case study using a medium sized urban area travel model and the QRFM trip generation and a distribution methodology to provide a framework for freight planning that can be used to improve resource allocation decisions.展开更多
The identification and selection of performance measures play an important role in any decision making process. Additionally, millions of dollars are spent on appropriate planning and identification of prospective pro...The identification and selection of performance measures play an important role in any decision making process. Additionally, millions of dollars are spent on appropriate planning and identification of prospective projects for improvements. As a result, current practitioners spend a lot of time and money in prioritizing their limited resources. This research proposes two tasks: 1) estimation of performance measures using a simulation based on dynamic traffic assignment model, and 2) development of a methodology to evaluate multiple projects based on benefit-cost analysis. The model, DynusT, is used for the Las Vegas roadway network during the morning peak time period. A comparative analysis of the results from proposed methodology with existing California Benefit-Cost (Cal-B/C) models is presented. The results indicate that the new methodology provides an accurate benefit-cost ratio of the projects. In addition, it signifies that the existing Cal-B/C models underestimate the benefits associated with the prospective project improvements. The major contribution of this research is the simultaneous estimation of the performance measures and development of a methodology to evaluate multiple projects. This is helpful to decision makers to rank and prioritize future projects in a cost-effective manner. Planning and operational policies for the transportation systems can be developed based on the gained insights from this study.展开更多
充电负荷是计算研究电动汽车(electric vehicle,EV)对电网冲击和充电设施规划的基础。为此提出一种考虑电池健康状态(state of health,SOH)的充电需求计算方法。首先,利用EV出行链中与充电负荷相关的特征量的概率分布,实现单个EV用户出...充电负荷是计算研究电动汽车(electric vehicle,EV)对电网冲击和充电设施规划的基础。为此提出一种考虑电池健康状态(state of health,SOH)的充电需求计算方法。首先,利用EV出行链中与充电负荷相关的特征量的概率分布,实现单个EV用户出行行为的完整模拟。接着,基于电池健康状态修正EV实际容量和充电特征,并提出由用户里程焦虑系数修正用户下次出行后所允许的最小剩余SOC(state of charge,SOC)值,改进充电负荷计算模型。最后,基于美国家庭出行调查(national household travel survey,NHTS)数据的仿真表明,SOH影响EV用户出行的多个特征,EV规模越大,充电负荷计算越应考虑SOH。展开更多
Demand forecasting is often difficult due to the unobservability of the applicable historical demand series. In this study, the authors propose a demand forecasting method based on stochastic frontier analysis(SFA) mo...Demand forecasting is often difficult due to the unobservability of the applicable historical demand series. In this study, the authors propose a demand forecasting method based on stochastic frontier analysis(SFA) models and a model average technique. First, considering model uncertainty,a set of alternative SFA models with various combinations of explanatory variables and distribution assumptions are constructed to estimate demands. Second, an average estimate from the estimated demand values is obtained using a model average technique. Finally, future demand forecasts are achieved, with the average estimates used as historical observations. An empirical application of air travel demand forecasting is implemented. The results of a forecasting performance comparison show that in addition to its ability to estimate demand, the proposed method outperforms other common methods in terms of forecasting passenger traffic.展开更多
In the last decades, there has been substantial development in modeling techniques of travel demand estimation. For low population areas the external trip estimation is important but usually neglected in travel demand...In the last decades, there has been substantial development in modeling techniques of travel demand estimation. For low population areas the external trip estimation is important but usually neglected in travel demand modeling process. In Egypt, the researches in this field are scarce due to lack of data. Accordingly, this paper aims to identify and estimate the main variables that affect the travel demand in low population areas, and to develop models to predict them. The study focused on the Port Said Govemorate in North East Egypt. A special questionnaire had been prepared in 2010 depending on interviews of passengers at basic taxi terminals in Port Said. And 2211 filled questionnaires were offering for research. To analyze the data, two modeling procedures were used. One is the multiple linear regression and the other is the generalized linear modeling （GLM） applying normal distributions. It is found that GLM procedure offers more suitable and accurate approach than the linear regression for developing number of trips. The final demand models have statistics within the acceptable regions and, also, they are conceptually reasonable. These results are so important for Egyptian highway authorities to improve the efficiency of highway transportation system in Egypt.展开更多
文摘In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.
文摘This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.
文摘This paper analyses the effectiveness of applying the Quick Response Freight Manual (QRFM) to model freight transportation. Typically, freight transportation is indirectly modeled or as an after-thought. Increasing freight volumes, coupled with cost saving strategies such as just-in-time delivery systems, require that transportation policymakers analyze infrastructure needs and make investment decisions that explicitly include freight volumes as a component. This paper contains a case study using a medium sized urban area travel model and the QRFM trip generation and a distribution methodology to provide a framework for freight planning that can be used to improve resource allocation decisions.
文摘The identification and selection of performance measures play an important role in any decision making process. Additionally, millions of dollars are spent on appropriate planning and identification of prospective projects for improvements. As a result, current practitioners spend a lot of time and money in prioritizing their limited resources. This research proposes two tasks: 1) estimation of performance measures using a simulation based on dynamic traffic assignment model, and 2) development of a methodology to evaluate multiple projects based on benefit-cost analysis. The model, DynusT, is used for the Las Vegas roadway network during the morning peak time period. A comparative analysis of the results from proposed methodology with existing California Benefit-Cost (Cal-B/C) models is presented. The results indicate that the new methodology provides an accurate benefit-cost ratio of the projects. In addition, it signifies that the existing Cal-B/C models underestimate the benefits associated with the prospective project improvements. The major contribution of this research is the simultaneous estimation of the performance measures and development of a methodology to evaluate multiple projects. This is helpful to decision makers to rank and prioritize future projects in a cost-effective manner. Planning and operational policies for the transportation systems can be developed based on the gained insights from this study.
文摘充电负荷是计算研究电动汽车(electric vehicle,EV)对电网冲击和充电设施规划的基础。为此提出一种考虑电池健康状态(state of health,SOH)的充电需求计算方法。首先,利用EV出行链中与充电负荷相关的特征量的概率分布,实现单个EV用户出行行为的完整模拟。接着,基于电池健康状态修正EV实际容量和充电特征,并提出由用户里程焦虑系数修正用户下次出行后所允许的最小剩余SOC(state of charge,SOC)值,改进充电负荷计算模型。最后,基于美国家庭出行调查(national household travel survey,NHTS)数据的仿真表明,SOH影响EV用户出行的多个特征,EV规模越大,充电负荷计算越应考虑SOH。
基金supported by the National Natural Science Foundation of China under Grant Nos.71522004,11471324 and 71631008a Grant from the Ministry of Education of China under Grant No.17YJC910011
文摘Demand forecasting is often difficult due to the unobservability of the applicable historical demand series. In this study, the authors propose a demand forecasting method based on stochastic frontier analysis(SFA) models and a model average technique. First, considering model uncertainty,a set of alternative SFA models with various combinations of explanatory variables and distribution assumptions are constructed to estimate demands. Second, an average estimate from the estimated demand values is obtained using a model average technique. Finally, future demand forecasts are achieved, with the average estimates used as historical observations. An empirical application of air travel demand forecasting is implemented. The results of a forecasting performance comparison show that in addition to its ability to estimate demand, the proposed method outperforms other common methods in terms of forecasting passenger traffic.
文摘In the last decades, there has been substantial development in modeling techniques of travel demand estimation. For low population areas the external trip estimation is important but usually neglected in travel demand modeling process. In Egypt, the researches in this field are scarce due to lack of data. Accordingly, this paper aims to identify and estimate the main variables that affect the travel demand in low population areas, and to develop models to predict them. The study focused on the Port Said Govemorate in North East Egypt. A special questionnaire had been prepared in 2010 depending on interviews of passengers at basic taxi terminals in Port Said. And 2211 filled questionnaires were offering for research. To analyze the data, two modeling procedures were used. One is the multiple linear regression and the other is the generalized linear modeling （GLM） applying normal distributions. It is found that GLM procedure offers more suitable and accurate approach than the linear regression for developing number of trips. The final demand models have statistics within the acceptable regions and, also, they are conceptually reasonable. These results are so important for Egyptian highway authorities to improve the efficiency of highway transportation system in Egypt.
