The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

Transit network design with allocation of green vehicles: A genetic algorithm approach

The use of fossil fuels in transportation generates harmful emissions that accounts for nearly half of the total pollutants in urban areas. Dealing with this issue, local authorities are dedicating specific efforts to seize the opportunity offered by new fuels and technological innovations in achieving a cleaner urban mobility. In fact, authorities are improving environmental performances of their public transport fleet by procuring cleaner vehicles, usually called low and zero emission vehicles (LEV and ZEV, respectively). Nevertheless there seems to be a lack of methodologies for supporting stakeholders in decisions related to the introduction of green vehicles, whose allocation should be performed since the network design process in order to optimize their available green capacity.In this paper, the problem of clean vehicle allocation in an existing public fleet is faced by introducing a method for solving the transit network design problem in a multimodal, demand elastic urban context dealing with the impacts deriving from transportation emissions.The solving procedure consists of a set of heuristics which includes a routine for route generation and a genetic algorithm for finding a sub-optimal set of routes with the associated frequencies.     

Sensitivity-based uncertainty analysis of a combined travel demand model

Travel demand forecasting is subject to great uncertainties. A systematic uncertainty analysis can provide insights into the level of confidence on the model outputs, and also identify critical sources of uncertainty for enhancing the robustness of the travel demand model. In this paper, we develop a systematic framework for quantitative uncertainty analysis of a combined travel demand model (CTDM) using the analytical sensitivity-based method. The CTDM overcomes limitations of the sequential four-step procedure since it is based on a single unifying rationale. The analytical sensitivity-based method requires less computational effort than the sampling-based method. Meanwhile, the uncertainties stemming from inputs and parameters can be treated separately so that the individual and collective effects of uncertainty on the outputs can be clearly assessed and quantified. Numerical examples are finally used to demonstrate the proposed sensitivity-based uncertainty analysis method for the CTDM.     

On the degradation of performance for traffic networks with oblivious users

We consider the problem of characterizing user equilibria and optimal solutions for routing in a given network. We extend the known models by considering users oblivious to congestion in the following sense: While in the typical user equilibrium setting the users follow a strategy that minimizes their individual cost by taking into account the (dynamic) congestion due to the current routing pattern, an oblivious user ignores congestion altogether; instead, he or she decides his routing on the basis of cheapest routes on a network without any flow whatsoever. These cheapest routes can be, for example, the shortest paths in the network without any flow. This model tries to capture the fact that a certain percentage of travelers base their route simply on the distances they observe on a map, without thinking (or knowing, or caring) about the delays experienced on this route due to their fellow travelers. In this work we study the effect of such users using as the measure of network performance its price of anarchy, i.e., the ratio of the total latency experienced by the users (oblivious or not) at equilibrium over the social optimum.     

高职院校筹资及资金管理问题探略

我国高等教育承载民众希望与国民素质提升之重任,高等教育发展关系国计民生,同时也迫切需要解决自身发展中存在的资金需求问题,本文在分析总结高职院校筹资现状和存在问题的基础上,提出优化和改进高职院校筹资的对策建议。     

大型机场地面集疏运需求预测方法研究

机场地面集疏运系统是机场发展的重要支撑，交通需求预测是进行机场集疏运交通规划的前提。笔者以四阶段预测的基本原理为基础，结合机场集疏运需求特点，对预测的整体思路、方法、步骤和内容等进行详细分析，优化调整出行分布、方式划分预测模型，并以南京禄口国际机场为实例进行了预测。研究成果对国内同类大型机场的集疏运需求预测具有借鉴和参考价值。     

Evolving competition between Hong Kong and Shenzhen ports

Shenzhen Port (SZP), once a negligible local port, has risen dramatically to a world-leading container port and an “equal” player with Hong Kong Port (HKP). Will this market share reallocation continue, or will equilibrium be eventually realized for HKP to prosper continuously? We examine the relationship between these two ports to answer this question. We propose a new transformation method to describe the growth of container cargo transport demand, define the quantitative measures of the competition relationship and port competitiveness, and present a rigorous analytical framework with econometric tests and models to understand the true relationship between HKP and SZP. Direct empirical tests suggest that SZP complements HKP; however, the two ports exhibit strong competition when the effect of demand growth is excluded. Considering transshipment separately, we find that the impact of SZP on HKP is negative in transshipment but complementary in direct shipment. We may conclude that HKP does not affect SZP, whereas SZP has competitive power over HKP. These results are consistent with the findings of some previous theoretical studies.     

行人过街需要分析研究

通过调查分析研究,运用心理学需要理论和交通工程理论,分析了行人过街过程中的各种需要,包括心理需要、时间和空间需要、环境和其他需要。对过街过程中需要的具体内容进行了阐述。最后总结了各种需要之间的联系。     

基于非集计与弹性联合模型的交通需求分析

随着我国交通事业的蓬勃发展,人们对交通方式的需求正在不断发生变化。基于科学研究的交叉性和外延性,将不同研究领域已经基本成熟的模型,即微观经济学中的费用效益弹性理论模型和交通方式分布中的非集计模型(Logit模型)有机地结合并融为一体,得到一种联合模型,使其更容易将数据定量化、具体化。通过这个联合模型来分析交通需求并将与交通需求相关的因素进行对比,得出交通因素发生变化对交通需求者和供给者的影响。