Abatement cost functions for incentive-based policies in the automobile market

This paper compares the outcomes of policies that target vehicle holdings with those that target vehicle usage using data from the US Consumer Expenditure Survey. Results show that a higher price of gasoline shifts vehicle holdings towards more fuel efficient vehicles and reduces the annual demand for miles, whereas imposing a fee on vehicles or a feebate program only shifts vehicle holdings towards more fuel efficient vehicles and has little to no impact on the demand for miles. While it is relatively expensive to reduce CO₂ emission through incentive-based policies, achieving any abatement level is more expensive through imposing fees on vehicles than gasoline taxes. In addition, the maximum amount of abatement attainable by a feebate program is relatively small and the same amount could be achieved by imposing a $0.73 gasoline tax per gallon.     

贵州省纳雍县滑坡易发性评价

以贵州省纳雍县为研究区,基于地理信息系统（GIS）平台,采用Logistic回归模型评价区域滑坡易发性。选取高程、坡度、坡向、地表曲率、岩性、到公路距离、到水系距离和到断层距离8项影响因子,应用Logistic回归模型拟合描述滑坡发生与各项因子关系的回归方程。在此基础上,预测研究区内滑坡易发性的概率值,并将研究区划分为5个易发级别。结合历史滑坡分布,对滑坡易发性分区的合理性进行验证,结果表明滑坡易发性分区图和实际滑坡分布情况吻合较好。此外,应用受试者工作特征曲线对模型结果进行评价,结果显示,曲线下面积AUC值为0.774,Logistic回归模型的预测精度较好。     

二阶波浪漂移力的回归分析

二阶波浪载荷的预报对动力定位能力评估具有重要意义。对二阶波浪载荷的预报,通常可采用模型试验和数值模拟的方法。模型试验费用昂贵,数值模拟时面元划分的合理性对计算结果的影响很大,且模型试验和数值模拟周期都相对较长。采用压力直接积分法进行系列船型的二阶波浪漂移力计算,在此基础上,采用模长界限控制的正交化方法的多元多项式回归分析,给出二阶波浪漂移力的回归公式,并进行了验证分析。验证分析表明回归公式置信区间为0.95。     

珠三角腹地软基十字板与静探试验成果的相关性研究

在原位十字板与静探数据的相关性分析中,考虑研究范围内土体强度可分别由两种测试数据独立线性表达,找出两种试验指标的等式,将试验参数综合考虑,建立多元线性回归方程,通过大量试验数据并借助数学软件对回归方程进行求解。通过实例分析,验证两种试验关系的准确性,为今后的勘察与研究提供参考和新的方法。     

贵州省纳雍县滑坡易发性评价

以贵州省纳雍县为研究区,基于地理信息系统(GIS)平台,采用Logistic回归模型评价区域滑坡易发性。选取高程、坡度、坡向、地表曲率、岩性、到公路距离、到水系距离和到断层距离8项影响因子,应用Logistic回归模型拟合描述滑坡发生与各项因子关系的回归方程。在此基础上,预测研究区内滑坡易发性的概率值,并将研究区划分为5个易发级别。结合历史滑坡分布,对滑坡易发性分区的合理性进行验证,结果表明滑坡易发性分区图和实际滑坡分布情况吻合较好。此外,应用受试者工作特征曲线对模型结果进行评价,结果显示,曲线下面积AUC值为0.774,Logistic回归模型的预测精度较好。     

Modeling road traffic fatalities in India: Smeed's law,time invariance and regional specificity

Mathematical formulations linking road traffic fatalities to vehicle ownership, regional population, and economic growth continue to be developed against the backdrop of Smeed and Andreassen models. Though a few attempts were made, Smeed's law has not been fully tested in India. Using the 1991–2009 panel data from all states, this work (a) developed the generalized Smeed and Andreassen models; (b) evaluated if traffic fatalities were impacted by structural changes; and (c) examined if – in relation to the generalized model – the individual (time and regional) models are more relevant for application. Seven models (Smeed: original, generalized, time-variant, state-variant; and Andreassen: generalized, time-variant, state-variant) were developed and tested for fit with the actual data. Results showed that the per vehicle fatality rate closely resembled Smeed's formulation. Chow-test yielded a significant F-stat, suggesting that the models for four pre-defined time-blocks are structurally different from the 19-year generalized model. The counterclockwise rotation of the log-linear form also suggested lower fatality rates. While the new government policies, reduced vehicle operating speeds, better healthcare, and improved vehicle technology could be the factors, further research is required to understand the reasons for fatality rate reductions. The intercept and gradients of the time-series models showed high stability and varied only slightly in comparison to the 19-year generalized models, thus suggesting that the latter are pragmatic for application. Regional formulations, however, indicate that they may be more relevant for studying trends and tendencies. This research illustrates the robustness of Smeed's law, and provides evidence for time-invariance but state-specificity.     

道路路阻函数模型及适用性研究

交通诱导系统中两节点间最优路径的选择是目前的一个难点问题,其中路阻函数的确定是路径优化的核心内容.针对交通流由畅通状态到拥挤状态再到堵塞状态的过程,应用经典交通流理论和实际调查数据,构建交通流诱导系统分段路阻函数模型,以q=10veh/h为一个单位,对函数进行分段拟合,构建高速公路和城市快速路下的分段路阻函数,并对其适应性进行拟合分析.应用结果表明:在不同的流量范围内,高速公路和城市快速路分段路阻函数在自由流状态、高密度状态和低密度条件下适合不同的分段函数.     

Door-to-door travel times in RP departure time choice models: An approximation method using GPS data

A common way to determine values of travel time and schedule delay is to estimate departure time choice models, using stated preference (SP) or revealed preference (RP) data. The latter are used less frequently, mainly because of the difficulties to collect the data required for the model estimation. One main requirement is knowledge of the (expected) travel times for both chosen and unchosen departure time alternatives. As the availability of such data is limited, most RP-based scheduling models only take into account travel times on trip segments rather than door-to-door travel times, or use very rough measures of door-to-door travel times. We show that ignoring the temporal and spatial variation of travel times, and, in particular, the correlation of travel times across links may lead to biased estimates of the value of time (VOT). To approximate door-to-door travel times for which no complete measurement is possible, we develop a method that relates travel times on links with continuous speed measurements to travel times on links where relatively infrequent GPS-based speed measurements are available. We use geographically weighted regression to estimate the location-specific relation between the speeds on these two types of links, which is then used for travel time prediction at different locations, days, and times of the day. This method is not only useful for the approximation of door-to-door travel times in departure time choice models, but is generally relevant for predicting travel times in situations where continuous speed measurements can be enriched with GPS data.     

Bus running time prediction using a statistical pattern recognition technique

Abstract

Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.     

基于SVR模型的灌注桩价格估算研究

采用基于结构风险最小化思想的支持向量回归(SVR)模型预测了灌注桩的中标价格.在分析灌注桩的成本动因的基础上,通过历史项目清单预算确定了17个回归自变量,根据历史项目中标价格(因变量)和成本动因(自变量)来估算当前项目价格.利用该模型对福建省某高速公路灌注桩进了行价格估算,并与基于定额的清单预算价格以及多元线性回归估算价格进行了对比.结果表明:估算结果相对于其他两种方法明显接近实际中标价格,采用SVR模型可以大大提高估算的准确性,有效控制造价,提升公路工程造价管理水平.