中国公路货运枢纽规模分布的分形特征

为了定量描述中国公路货运枢纽体系结构现状, 将公路货运量作为货运枢纽的规模参数, 推导了分维数的计算公式, 选取1997~2007年的货运量统计数据, 计算了200个公路货运枢纽规模分布的分维数。数据拟合发现: 1997~1999年公路货运枢纽的规模分布具有双分形特征, 2000~2007年的规模分布呈单分形结构, 且分维数介于1.464 6~1.570 1间, 公路货运枢纽体系的规模分布与城镇体系基本一致。分析结果表明: 中国公路货运枢纽体系规模分布从双分形到单分形的演化显示其发育较好, 需加强大型公路货运枢纽建设, 以进一步优化公路货运枢纽体系结构。     

航空货代装箱优化模型及算法

为了提高航空货代的盈利水平和装箱能力, 通过分析航空货物运价体系的特点, 将航空货代装箱问题划分为装箱货物优选和优选货物配装2个阶段, 建立一种基于航空货代利润最大化的装箱货物优选模型。在考虑同票货物邻近装载的约束条件下, 采用空间分割、合并和整体充填策略, 设计了一种基于评级规则的优选货物装载优化算法。计算结果表明: 货物优选模型能够合理选择装箱的货物, 货物装载优化算法能使集装箱容积平均利用率高达83%, 能够有效地满足航空货代增加利润和装箱的实际要求。     

基于飞行流量耦合的区域容量改进模型

研究了包括多个扇区的区域容量评估问题, 通过分析飞行流量在空域单元之间产生耦合约束因素, 提出了空域单元的耦合容量, 研究了区域耦合容量的影响因素。结合管制员工作负荷等限制建立了区域耦合容量的多目标整数规划模型, 并使用该模型计算了兰州区域各空域单元耦合容量。计算结果表明: 扇区1、2、3耦合容量分别为22、19、33架次.h^-1, 小于其最大容量; 区域耦合容量小于区域仿真容量评估结果, 因此, 该模型更有利于合理分配空域资源。     

收费公路资产证券化定价及发行方法研究

从数据驱动视角出发,本文探讨收费公路资产支持证券的结构化定价方法。首先,构建反 映交通量风险特征的收费公路通行收入自回归积分滑动平均模型;其次,基于瀑布式偿付结构和 到期收益率Nelson-Siegel模型计算不同等级证券发债规模与息票利率;最后结合成渝高速和渝 蓉高速现实数据进行仿真分析。研究发现,高速公路成熟期的通行收入具有尖峰厚尾特征,成长 期的通行收入更兼具显著的波动聚集效应。数据驱动的定价模型能够刻画通行收入的风险特 征,合理估计优先级的证券融资比例,比只考虑利率风险的现金流折现法更具有优势;从发行方 式来看,合并发行的融资结构显著优于单独发行。管理启示是改变以单个高速公路项目为基础 的特许经营权融资,通过绩优绩差项目的合并发行优化融资结构。     

A volatile relationship: The effect of changing gasoline prices on public support for mass transit

The determinants of public opinion toward public transit is a little-researched topic, though a better understanding of what makes consumers willing to support transit may reveal which attributes of transit consumers value most. One determinant of people’s willingness to support investments in mass transit may be the price of fuel for transit’s principal competition, the private automobile. In this paper, I examine the relationship between the cost of gasoline and stated willingness to invest public money in mass transit improvements. I hypothesize that fuel price volatility—in addition to price itself—is a determinant of support for more mass transit funding, controlling for other factors. As the price of gasoline becomes more uncertain, the public should, all else equal, support investment in mass transportation, a form of transportation that may provide some measure of protection from the price of fuel. Results suggest a strong effect of price volatility on consumers’ willingness to support transit expenditures.     

Driving to save time or saving time to drive? The enduring appeal of the private car

Use of the private car is often viewed as highly problematic. It is regularly associated with global physical, social and ecological harms such as climate change and the high incidence of lifestyle diseases, including heart disease. Attempts to address these problems generally include provision for day-to-day physical mobility based on alternatives to the private car. Labelled alternative transport, these modes include public transport, walking and cycling. Yet the private car continues as the preferred way to travel in many cities. A deeper understanding of this preference can reveal under explored sites of resistance to alternative transport modes.This paper contributes to these understandings by examining the role the car as a time saving device plays in sustaining automobility. Its central proposition is that individual decisions to drive are not necessarily motivated by the desire to save time. The paper draws on empirical evidence on the journey to work in Australia’s largest city, Sydney. Using a systematic process of trip substitution analysis, a group of people were identified who could use alternative transport to get to work in the same amount of time it currently takes them to drive. These people then participated in a series of in-depth interviews where deeper attachments and motivations for private car use were explored.This approach has enabled development of the multi-layered understanding that informs the central proposition that individual decisions to drive are not necessarily motivated by the desire to save time. Instead, automobility is sustained by appeals to flexibility and autonomy, as well as the interminable pull of the sensory experience provided by the cocoon of the car. This way of thinking about resistance to alternative transport exposes a series of inconsistencies between the expectations of those planning for, and those anticipated to one day use, alternative transport.     

Competition and public service obligations in European aviation markets

This paper analyzes the effect of universal service policies on the airline markets of five European Union countries (France, Germany, Italy, Spain and the United Kingdom) in the period 2002–2010. Results show that airfare discount schemes for island residents raise demand and positively affect competition and the number of flights at the route level. These effects are evident in France and Italy, but are particularly marked in Spain. By contrast, public service obligations (PSOs) reduce competition on the protected routes, while their effect on the number of flights differs depending on national regulations. In Spain, routes protected with PSOs have greater flight frequencies than those on unprotected routes of similar characteristics, but in France, Italy and the UK the opposite result is found. The empirical model also finds that on routes with low-cost airlines market concentration is smaller and there is a larger number of flights. This result is relevant for the design of universal service policy, since in recent years low-cost airlines have entered a number of thin routes and have increased access to air transportation.     

Evaluating the effects of bus design on passenger flow: Is agent-based simulation a feasible approach?

In this paper, we propose an agent-based simulation approach that is capable of simulating the flow of passengers on board buses and at bus stops. The intention is that it will be applied during vehicle development to analyze how vehicle design affects passenger flow, and thus also how it affects system performance such as dwell time. In turn, this could aid the developers in making design decisions early in the development process. Besides introducing the simulation tool itself, the paper explores the realism of the data generated by the tool. A number of passenger flow experiments featuring a full-scale bus mockup and 50 participants were carried out. The setup of these experiments mirrored a number of ‘bus journeys’ (regarding vehicle design, number of passengers boarding/alighting at each stop and so on) that had previously been simulated using the simulation tool. When the data from the simulations were compared with the data from the passenger flow experiments, it could be concluded that the tool is indeed able to generate realistic passenger flows, although with some errors when a large number of passengers board/alight. The simulated dwell times were rationally affected by the tested bus layout aspects. It was concluded that the tool makes it possible to evaluate how variations in bus layouts affect passenger flow, providing data of sufficiently high quality to be useful in early phases of vehicle design.     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).