大型铁路客运枢纽换乘服务研究

站在运输服务设计的角度,以增强旅客换乘出行体验为目的,提出“人、行李分离”的换乘服务理念,并基于该服务理念设计铁路客运枢纽内同站和异站换乘的方案。异站换乘方案设计时,提出铁路专用车的概念,打造一种全新的换乘模式,满足旅客换乘出行的多元化需求,吸引旅客主动换乘。最后,从心理和生理舒适性两个角度对换乘服务理念进行评价,结果表明“人、行李分离”服务创造了旅客换乘出行附加价值,提高了旅客的换乘出行体验感。     

Comfort and Safety as Perceived by Wheelchair-Seated Bus Passengers

Abstract

Wheelchair-seated passengers on European and Swedish urban transit buses can travel rearwards, resting against a bulkhead, without the use of tie-down equipment. However, users sometimes disapprove of being the only passengers who have to travel rearwards, and also unrestrained. In order to investigate comfort and safety as perceived by wheelchair-seated bus passengers riding either forwards or rearwards, an experimental field study was carried out. Participating subjects were 31 wheelchair users and a group of 44 ambulant passengers. Each subject made two consecutive, identical 15-minute trips, randomly beginning either forwards or backwards, and interviews were conducted after each trip. During the trips, three-axis bus motion was recorded. The concept of categorization was used as a theoretical background and basis for discussion of the comfort and safety constructs. The results indicated that while the majority preferred the forward-facing position regarding comfort issues, a minority felt that the level of perceived safety was better. Wheelchair-seated passengers were more positive towards the rearward position than the ambulant group.     

基于旅客特性的离站静态标识空间布局设计

铁路客运枢纽是城市内外交通衔接的纽带,铁路客运站内部的离站交通标识对旅客在铁路客运站中安全快速流动和转移起到了重要作用。如何使旅客舒适快捷地离站,不仅是离站旅客也是铁路客运枢纽管理者所密切关心的问题。文章从标识的基本概念出发,对静态交通标识进行详细分类,基于旅客特性,对静态标识的摆放位置进行研究,并建立各类静态标识高度设计模型,为大中型铁路客运枢纽中的静态标识空间布局设计提供参考。     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Exploring passenger anxiety associated with train travel

Although people are often encouraged to use public transportation, the riding experience is not always comfortable. This study uses service items to measure passenger anxieties by applying a conceptual model based on the railway passenger service chain perspective. Passenger anxieties associated with train travel are measured using a modern psychometric method, the Rasch model. This study surveys 412 train passengers. Analytical results indicate that the following service items cause passenger anxiety during trains travel: crowding, delays, accessibility to a railway station, searching for the right train on a platform, and transferring trains. Empirical results obtained using the Rasch approach can be used to derive an effective strategy to reduce train passenger anxiety. This empirical study also demonstrates that anxiety differs based on passenger sex, age, riding frequency, and trip type. This information will also prove useful for transportation planners and policy-makers when considering the special travel needs of certain groups to create a user-friendly railway travel environment that promotes public use.     

基于广西旅游业的道路客运发展探析

文章针对广西道路旅客运输的现状及广西道路客运企业发展旅游业的优越条件,以＂运游结合＂为切入点,介绍以快捷优质的客运服务带动＂慢旅游＂道路客运企业发展旅游业的新模式,对采取＂运游结合＂经营模式,提高服务质量,发展＂慢旅游＂提出了相关的建议。     

An aggregate demand model for intercity passenger travel in Sri Lanka

Inspite of the inherent weaknesses in aggregate demand models, they continue to be used in everyday applications, especially in developing countries. The largely data intensive disaggregate model preclude its application in many cases. This paper attempts the formulation and calibration of an aggregate total demand model for estimating inter-district passenger travel by public transport in Sri Lanka. In its process, an investigation is made of the common problems in the aggregate approach while examining possible remedial measures to improve the accuracy and (hence) the usability of the aggregate model. It is argued that commonly used variables and functional forms are inappropriate for making accurate estimates in developing countries. Consequently, the model calibration is shown to incorporate variables representing urbanisation, under-development, transfers, a mode-abstract cost function and intrinsic features. The necessity for functional form for each variable to be based on behavioral assumptions that are tested using the Box-Cox transformation for ensuring the best fit of the data is also observed. Although, the model form was calibrated for Sri Lanka, the model is generalised in order for its applications to other countries as well as, both, inter-district and intercity travel demand estimation.     

An investigation into passenger preference for express trains during peak hours

Seoul South Korea metro line 9 has a relatively short (27 km) length and dispatches express and local trains alternately with a 3-min headway. Despite a minimal time saving and more crowded conditions with regard to express trains, the passenger dependence on them is growing. The present study investigated the potential reasons for this seemingly irrational phenomenon during peak hours. A multinomial logit model was set up based only on route-specific variables, such as travel times and the proportion of express-train-involved travel time. Furthermore, the influence of trip-related properties, individual-specific characteristics, and latent factors on the preference for express trains was identified by adopting an interaction variable model. As a result, passenger transferrals from, or to, other lines, had a positive influence on the choice of express trains, but those who regularly used line 9 were less dependent on express trains. Passengers with pre-trip plans tended to prefer the use of express trains. Regarding the latent variables, passengers who were well aware of the line 9 system and sensitive to sanitation tended to choose express trains, while those who were sensitive to comfort tended to avoid express trains.     

Structure and dynamics of non-suburban passenger travel demand in Indian railways

In this paper we derive long run structural relationships for all the three classes, viz. upper, second and ordinary second class, of non-suburban long distance passenger transport demand for Indian railways using annual time series data for 1970–1995. We employ some of the recent developments in multivariate dynamic econometric time series modeling including estimation of long-run structural cointegrating relationships, short-run dynamics and measurement of the effects of shocks and their persistence on evolution of the dynamic passenger transport demand system. The models are estimated using a cointegrating vector autoregressive (VAR) modeling framework, which allows for endogeneity of regressors. The demand systems are found to be stable for all the classes in the long run and they converge to equilibrium in a period of around 2–4 years after a typical system-wide shock. Any disequilibrium in the short-run is corrected in the long-run with adjustments in passenger transport demand and the price variable, i.e. real rate charged per passenger kilometer. Results show that travel demand in all classes would rise with income, although the rise is less than proportionate in the case of ordinary class. High price elasticity in long-run and short-run impulse responses indicate that passenger fare hike could lead to substantial decline in travel demand leading to decline in revenue earnings of the railways. This revised version was published online in June 2006 with corrections to the Cover Date.     

Impact of heavy vehicles on surrounding traffic characteristics

This work examines the impact of heavy vehicle movements on measured traffic characteristics in detail. Although the number of heavy vehicles within the traffic stream is only a small percentage, their impact is prominent. Heavy vehicles impose physical and psychological effects on surrounding traffic flow because of their length and size (physical) and acceleration/deceleration (operational) characteristics. The objective of this work is to investigate the differences in traffic characteristics in the vicinity of heavy vehicles and passenger cars. The analysis focuses on heavy traffic conditions (level of service E) using a trajectory data of highway I‐80 in California. The results show that larger front and rear space gaps exist for heavy vehicles compared with passenger cars. This may be because of the limitations in manoeuvrability of heavy vehicles and the safety concerns of the rear vehicle drivers, respectively. In addition, heavy vehicle drivers mainly keep a constant speed and do not change their speed frequently. This work also examines the impact of heavy vehicles on their surrounding traffic in terms of average travel time and number of lane changing manoeuvres using Advanced Interactive Microscopic Simulator for Urban and Non‐Urban Networks (AIMSUN) microscopic traffic simulation package. According to the results, the average travel time increases when proportion of heavy vehicles rises in each lane. To reflect the impact of heavy vehicles on average travel time, a term related to heavy vehicle percentage is introduced into two different travel time equations, Bureau of Public Roads and Akçelik's travel time equations. The results show that using an exclusive term for heavy vehicles can better estimate the travel times for more than 10%. Finally, number of passenger car lane changing manoeuvres per lane will be more frequent when more heavy vehicles exist in that lane. The influence of heavy vehicles on the number of passenger car lane changing is intensified in higher traffic densities and higher percentage of heavy vehicles. Large numbers of lane changing manoeuvres can increase the number of traffic accidents and potentially reduce traffic safety. The results show an increase of 5% in the likelihood of accidents, when percentage of heavy vehicles increases to 30% of total traffic. Copyright © 2014 John Wiley & Sons, Ltd.     

Energy use in passenger transport in OECD countries: Changes since 1970

This paper analyzes some of the changes that took place in the structure of energy use for passenger travel in industrialized countries. Data is presented on energy use and travel activity for the four major modes of travel — automobile, bus, rail and air — for eight OECD countries: the United States, Japan, the United Kingdom, West Germany, France, Italy, Sweden, and Norway. We use the Laspeyres and Divisia indices to analyze the causes of the change in energy use between 1970 and 1987. The total change in energy use for travel is explained by changes in domestic passenger transport volumes, the mix of modes of travel, and the energy intensities of each mode. We have found two important effects that have a fundamental impact on energy use for travel since 1970. First, shifts among modes of transport towards more energy-intensive ones and large increases in volumes of travel (measured in passenger-kilometers) increased energy use for travel in many OECD countries, often more rapidly than the overall growth in GDP. Second, energy intensities, measured in mJ/passenger-kilometer, of passenger transport fell only in a few countries between 1970 and 1987. Even though individual automobiles have become more energy-efficient, greater size, power, and weight, worsening traffic conditions in Japan and Europe, and fewer people in cars restrained or even offset efficiency improvements. Particularly notable are the increases in intensities in Japan and Germany. The most important exception to this trend was the United States, but the intensities of land-based travel remain higher there than in most other countries. These findings lead to a pessimistic outlook for future energy use for travel. After all, if little or no energy was saved during the decades of high fuel prices, what can be expected in the 1990s?     

Determinants of airport retail revenue: a review of literature

ABSTRACT

As the airport retail industry continues to grow due to increasing travel demands, airport operators are increasingly developing their retail revenue potential to ensure financial viability. This study aims to provide a review of airport retail literature and identify the salient factors associated with passenger shopping behaviour. The paper presents a review of contemporary airport retail literature, covering a total of 50 studies from 1998 to 2018. The review identified 26 factors, which could broadly be grouped into five categories: airport/operator related; passengers' demographic related; passengers’ travel related; passengers’ psychological related and passengers’ resources related. In addition to providing a summary of the statistically significant factors across studies, the review identifies and discusses potential approaches for future research. These include the importance of considering both “to spend or not” decision and how much to spend and how most empirical studies focussed on the former; the gap in empirical analysis on the impact of airport terminal design layout on retail performance; and the gap in application of general consumer shopping behavioural models to airport retail problems. The paper concludes with the suggestion that we can build on the existing studies to develop a hybrid approach to solve several of the identified gaps simultaneously.     

Improving the forecasting accuracy of air passenger and air cargo demand: the application of back-propagation neural networks

This study employs back-propagation neural networks (BPN) to improve the forecasting accuracy of air passenger and air cargo demand from Japan to Taiwan. The factors which influence air passenger and air cargo demand are identified, evaluated and analysed in detail. The results reveal that some factors influence both passenger and cargo demand, and the others only one of them. The forecasting accuracy of air passenger and air cargo demand has been improved efficiently by the proposed procedure to evaluate input variables. The established model improves dramatically the forecasting accuracy of air passenger demand with an extremely low mean absolute percentage error (MAPE) of 0.34% and 7.74% for air cargo demand.     

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。     

Factors affecting the use of bus and rail services in a deregulated environment

In 1987, the NSW Government commenced deregulation of the long-distance bus industry in NSW. This immediately led to greater inter-modal competition and contestability within the context of changing passenger markets.This study utilises categorical data analysis methods to examine the emerging passenger markets of inter-modal competitors (bus and rail) and to assess the relative importance of socioeconomic and travel related variables which affect the use of bus and rail services along the high volume Sydney-Canberra and Sydney-North Coast corridors.Conclusions from the study indicate varied passenger markets within a relatively new contestable environment which are mode and corridor specific. Results are indicative of the need for competitors to develop marketing strategies conducive to the demands of the travelling public in order to enhance viability and commercial opportunities.     

Weather,transport mode choices and emotional travel experiences

With climate change high on the political agenda, weather has emerged as an important issue in travel behavioural research and urban planning. While various studies demonstrate profound effects of weather on travel behaviours, limited attention has been paid to subjective weather experiences and the psychological mechanisms that may (partially) underlie these effects. This paper integrates theoretical insights on outdoor thermal comfort, weather perceptions and emotional experiences in the context of travel behaviour. Drawing on unique panel travel diary data for 945 Greater Rotterdam respondents (The Netherlands), this paper aims to investigate how and to what extent weather conditions affect transport mode choices, outdoor thermal perceptions and emotional travel experiences. Our findings point out that observed dry, calm, sunny and warm but not too hot weather conditions stimulate cycling over other transport modes and – via mechanisms of thermal and mechanical comfort – lead to more pleasant emotions during travel. Overall, public transport users have less pleasant emotional experiences than users of other transport modes, while active mode users appear most weather sensitive. The theoretical contributions and empirical findings are discussed in the context of climate change and climate-sensitive urban planning.     

Effects of passenger characteristics and terminal layout on airport retail revenue: an agent-based simulation approach

This paper examines the effect of passenger characteristics and terminal layout on airport retail revenue using an agent-based simulation approach. Simulation results show that passenger mix (that is, the mix of shopper types according to a typology of airport shoppers) has a profound effect on airport retail revenue; the larger the number of ‘shopping lovers’ there are among passengers, the higher the airport retail revenue. Results also reveal that group travel can lead to negative effects on retail in certain terminal layouts, and that the amount of free dwell time that a passenger has can affect spending due to less retail engagement. This paper shows a combined effect of passenger characteristics and terminal layout on airport retail revenue, and discusses the implications of these results for future airport terminal design that aims to maximise retail potential.     

Evaluating bus transit performance of Chinese cities: Developing an overall bus comfort model

In order to improve the level of bus service, a field study was undertaken to develop a combined bus comfort model. This paper provides a comprehensive review of the different ways to predict the bus comfort, in addition to the variable experimental techniques used. It was found some environment parameters like noise, vibration, thermal comfort and the acceleration would affect the passengers’ experience. In this model, both the measurement of objective physical parameters and subjective questionnaire survey were conducted to gather the practical environment date, as well as to distribute questionnaires on board city buses during the same trips. By comparing the subjective views of bus passengers to objective physical parameters, a combined bus comfort model was established. This model helps to calculate the concrete value of passengers’ perceived bus comfort. An effective approach integrated the comfort model, measuring instrument and the driver monitor could greatly improve the bus service quality.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.