基于需求弹性的城市公交票价优化方法及实证分析

城市公交票价是公交系统健康发展的重要因素，票价制定需兼顾公交企业的市场性和公益性双重属性，在保证服务质量的同时，考虑运营成本和最大限度吸引公交需求，实现经济效益和社会效益的双赢.在本文中，根据用户均衡理论，构建了城市多方式交通出行的需求分析模型，采用灵敏度分析方法给出了城市公交价格-需求弹性的计算方法.在此基础上，充分考虑了各种方式的交通特征、公交需求弹性、公交运营成本及政府限价等因素，提出了城市公交票价优化的数学规划模型，并给出了求解算法.最后，以国内某城市居民出行调查及公交运营数据为基础，分析了不同条件下公交客运需求的变化规律及城市公交票价的优化策略.     

兰州地铁地温分布特性及其演化规律

以兰州地铁所在地区为研究对象,实测地铁隧道开挖前的地温(简称为初始地温),根据实测数据,提出地铁初始地温预测模型公式。采用非稳态传热的数值模型,分析运营条件下地铁隧道围岩温度的演化规律。结果表明:兰州地铁初始地温随环境气温和埋深的变化而变化;年变温层位于自地表至埋深12m处;年恒温层位于埋深12m及其以下,温度为15℃左右;年变温层中,1年内初始地温变化规律与环境气温变化规律相似,近似呈正弦曲线状分布,但存在相位滞后的现象;1年中初始地温的振幅随埋深的增大呈指数下降趋势。在隧道内空气与围岩之间热交换中,兰州地铁隧道围岩的温度及其梯度、热透厚度(未达到极限时)均与隧道内环境温度、热交换时间成正相关关系,但与距隧道内壁的距离成负相关关系。     

基于客流需求的城市轨道交通动态时刻表优化模型

为使城市轨道交通列车运行时刻表更贴合客流需求,依据不断变化的客流需求确定每列车的发车时刻和停站时间,采用多目标优化方法构建以乘客出行时间费用和列车运行时间费用最小为目标、列车发车时刻和停站时间为决策变量的城市轨道交通动态时刻表优化模型,并采用粒子群算法求解。以广州地铁13号线为例进行验证,结果表明优化后的时刻表更满足客流需求,能有效地提高乘客出行效率,具有更好的动态适应性。     

Capturing correlation with a mixed recursive logit model for activity-travel scheduling

Representing activity-travel scheduling decisions as path choices in a time–space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Västberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.     

Modeling the impacts of mandatory and discretionary lane-changing maneuvers

In this paper, a novel mesoscopic multilane model is proposed to enable simultaneous simulation of mandatory and discretionary lane-changing behaviors to realistically capture multilane traffic dynamics. The model considers lane specific fundamental diagrams to simulate dynamic heterogeneous lane flow distributions on expressways. Moreover, different priority levels are identified according to different lane-changing motivations and the corresponding levels of urgency. Then, an algorithm is proposed to estimate the dynamic mandatory and discretionary lane-changing demands. Finally, the lane flow propagation is defined by the reaction law of the demand–supply functions, which can be regarded as an extension of the Incremental-Transfer and/or Priority Incremental-Transfer principles. The proposed mesoscopic multilane cell transmission model is calibrated and validated on a complex weaving section of the State Route 241 freeway in Orange County, California, showing both the positive and negative impact of lane changing maneuvers, e.g., balancing effect and capacity drop, respectively. Moreover, the empirical study verifies that the model requires no additional data other than the cell transmission model does. Thus, the proposed model can be deployed as a simple simulation tool for accessing dynamic mesoscopic multilane traffic state from data available to most management centers, and also the potential application in predicting the impact of traffic incident or lane control strategy.     

Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong

This paper estimates the price and income elasticities of air cargo demand and examines how they may change after the 2008 financial crisis. Using a set of time series data, we simultaneously estimate the aggregated demand and supply functions of air cargo at Hong Kong International Airport (HKIA). We find that during the entire sampling period of 2001–2013, the price elasticity for air cargo transport demand at HKIA ranges from −0.74 to −0.29, suggesting that air cargo demand in Hong Kong reacts negatively to price (as expected) but does not appear to be very sensitive to price. The income elasticity ranges from 0.29 to 1.47 and appears sensitive to seasonality adjustment approaches. However, in terms of the speed of changes, air cargo demand changes much faster than overall economy, indicating the presence of a pro-cyclical pattern of air cargo traffic with respect to the overall economy. Our analysis shows that air cargo demand becomes more sensitive to changes in both price and income after 2008.     

Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology,application and impact evaluation

This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework’s ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.     

The generators of paratransit trips by persons with disabilities

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.     

VVL耦合喷油策略对GDI汽油机混合气形成的影响

利用三维仿真软件Ansys Fluent建立了GDI汽油机的仿真计算模型,就变气门升程耦合不同喷油策略对缸内气流运动和混合气形成的影响进行了模拟计算。结果表明,与大气门升程工况相比,小气门升程工况的缸内湍流运动强度、燃油蒸发和湿壁情况以及点火时刻混合气质量都明显改善;在小气门升程工况,采用两段喷油会缩短油气混合时间,过度推迟二次喷油时刻会恶化混合气质量和燃油湿壁情况;在大气门升程工况,两段喷油会改善混合气均匀性,随着二次喷油时刻推迟,燃油蒸发量增加,湿壁情况加剧,混合气质量得到改善;小气门升程工况下采用二次喷油时刻为470°曲轴转角,前后两次喷油量比例为7∶3的两段喷油方案在燃油蒸发和湿壁以及点火时刻缸内混合气质量这几个方面的效果都很好,是最合理的方案。     

对农村金融的差异需求与分层供给行为选择的模型分析——基于机制设计理论的视角

文章基于机制设计理论的思想和框架,建立了农村金融市场上差异需求与分层供给行为选择的相关约束机制模型,分析了相关约束机制变量对农村金融供求行为选择的影响,从而提出了通过进一步改进和完善农村金融市场相关机制变量,促进我国农村金融供求者的匹配性行为选择,改善农村金融市场效率,加强金融对“三农”支持力度的政策建议。