城市新区道路横断面规划设计研究

道路系统的建设是引导城市新区开发、改善投资环境的重要措施。城市道路横断面作为道路交通功能实现的重要载体,其合理规划设计有利于保障道路安全畅通,提高资源利用效率,实现城市社会经济的良性发展。     

基于SPSS主成分分析法在公路客运量预测中的应用

分析选取影响公路客运量的主要因素,基于SPSS统计软件对各因素进行主成分分析,将众多相关因素简化为少数不相关因素,消除由于变量过多导致的多重共线性影响,构建了河南省公路客运量预测模型。实例证明,该模型具有较高的精度,能够满足河南省公路客运量预测的需要。     

冬季巴士海峡偏北大风的分析与预报

本文通过冬季巴士海峡偏北大风个例的计算分析，认为大气的不稳定、狭管效应对该海区偏北大风的形成起重要作用。并在此基础上，提出了适用于船舶的预报此类大风的方法。     

Forecasting travel behavior using Markov Chains-based approaches

Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real-world populations and underlying travel demands. In this regard, we propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling-based methods to capture the behavioral complexity and the great heterogeneity of agents of the true population through representative micro-samples. The population synthesis method is capable of building the joint distribution of a given population with its corresponding marginal distributions using either full or partial conditional probabilities or both of them simultaneously. In particular, the estimation of socio-demographic or transport-related variables and the characterization of daily activity-travel patterns are included within the framework. The fully probabilistic structure based on Markov Chains characterizing this framework makes it innovative compared to standard activity-based models. Moreover, data stemming from the 2010 Belgian Household Daily Travel Survey (BELDAM) are used to calibrate the modeling framework. We illustrate that this framework effectively captures the behavioral heterogeneity of travelers. Furthermore, we demonstrate that the proposed framework is adequately adapted to meeting the demand for large-scale micro-simulation scenarios of transportation and urban systems.     

Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.     

新冠肺炎疫情下城市公共交通非常规防疫策略——以宁波市为例

在国家重大突发疫情面前，城市公共交通具有保障出行与阻断疫情的双重责任。面对新型冠状病毒感染的肺炎（简称新冠肺炎，COVID-19）疫情，城市公共交通既要保证有效运输，又要降低疫情扩散的风险。地铁和常规公交是城市公共交通系统不可缺少的一部分，在城市公共交通中占据重要地位。针对宁波市城市公共交通系统中存在的防疫问题，提出了基于问题驱动的城市公共交通非常规防疫策略。研究结果表明：新冠肺炎疫情形势下，城市公共交通系统防疫需要启动应急响应机制，遵循分区分类防控的基本原则，在保障人们刚性出行需求的同时，必须阻断疫情传播，减少通过公共交通运输造成的交叉感染，实现疫情可防可控。除体温检测、佩戴口罩与洗手消毒等防疫措施之外，还应结合地方实际和风险评估等级采取非常规的组合防疫策略，即：①面向城市常规公交，建议采取网格化运营策略、需求响应式运营策略以及应急公交接驳策略；②面向城市轨道交通，建议采取3级组合防疫策略，即暂停运营策略、车厢隔离防疫策略以及需求响应式防疫策略。以上常规公交与轨道交通的多种组合防疫策略需根据疫情的发展情况动态调整，及时启动相应级别的公共交通应急预案，被动防御与主动防控相结合，积极发挥城市公共交通在疫情时期的交通骨干作用和应急保障作用。     

Estimating flight-level price elasticities using online airline data: A first step toward integrating pricing,demand, and revenue optimization

We estimate flight-level price elasticities using a database of online prices and seat map displays. In contrast to market-level and route-level elasticities reported in the literature, flight-level elasticities can forecast responses in demand due to day-to-day price fluctuations. Knowing how elasticities vary by flight and booking characteristics and in response to competitors’ pricing actions allows airlines to design better promotions. It also allows policy makers the ability to evaluate the impacts of proposed tax increases or time-of-day congestion pricing policies. Our elasticity results show how airlines can design optimal promotions by considering not only which departure dates should be targeted, but also which days of the week customers should be allowed to purchase. Additionally, we show how elasticities can be used by carriers to strategically match a subset of their competitors’ sale fares. Methodologically, we use an approach that corrects for price endogeneity; failure to do so results in biased estimates and incorrect pricing recommendations. Using an instrumental variable approach to address this problem we find a set of valid instruments that can be used in future studies of air travel demand. We conclude by describing how our approach contributes to the literature, by offering an approach to estimate flight-level demand elasticities that the research community needs as an input to more advanced optimization models that integrate demand forecasting, price optimization, and revenue optimization models.     

洞新高速公路岩溶路基处理工程实例

在分析总结国内外相关研究成果的基础上,基于洞新高速公路现场施工处治经验,开展现场变形预测分析,总结提出适用的溶洞路基施工处治技术,并采用有限元计算与理论分析相结合的方法,对加固效果进行分析。     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

Flexible feeder transit route design to enhance service accessibility in urban area

To improve the accessibility of transit system in urban areas, this paper presents a flexible feeder transit routing model that can serve irregular‐shaped networks. By integrating the cost efficiency of fixed‐route transit system and the flexibility of demand responsive transit system, the proposed model is capable of letting operating feeder busses temporarily deviate from their current route so as to serve the reported demand locations. With an objective of minimizing total bus travel time, a new operational mode is then proposed to allow busses to serve passengers on both street sides. In addition, when multiple feeder busses are operating in the target service area, the proposed model can provide an optimal plan to locate the nearest one to response to the demands. A three‐stage solution algorithm is also developed to yield meta‐optimal solutions to the problem in a reasonable amount of time by transforming the problem into a traveling salesman problem. Numerical studies have demonstrated the effectiveness of the proposed model as well as the heuristic solution approach. Copyright © 2015 John Wiley & Sons, Ltd.