基于改进TOPSIS的城市客运综合交通枢纽评价

城市客运综合交通枢纽规划方案的优劣对城市综合交通系统的建设发展具有重大影响。为了提高城市客运综合交通枢纽规划方案评价的客观性和准确性,结合城市客运综合交通枢纽客流衔接换乘的系统分析,从多维角度出发构建了城市客运综合交通枢纽规划方案评价的多层次指标体系,在遵循方案评价基本原理及城市客运综合交通枢纽特点的基础上,提出了基于改进逼近理想点排序法的评价方法,用于城市客运综合交通枢纽方案的评价,建立城市客运综合交通枢纽综合评价模型。     

Assessing the effects of a mixed-mode design in a longitudinal household travel survey

The German Mobility Panel (MOP) is a national household travel survey, which has been collecting data on travel behavior in Germany since 1994. One of the MOP’s central assets is its ability to provide time-series data on travel behavior. Thus, the comparability of survey results from different years is a major objective of the survey method used. Declining survey participation rates in the last decade in various socio-demographic groups resulted in the implementation of a mixed-mode design for the MOP in 2013, both for the sampling stage (landline and mobile phone recruitment) and the data collection stage (paper and web). In this study, we analyze whether the adaptations in the survey mode do indeed improve the results and, if so, why and to what degree. Ideally, the survey mode adaptions have increased the representativeness of the MOP. However, measurement biases due to the mixed-mode design are also conceivable. To decompose survey mode effects, we applied the propensity score weighting method. This method imputes the hypothetical responses participants would have given in different survey modes; disparities between actual responses and hypothetical responses under another mode are then traced back to the mixed-mode design. Our analysis indicates that trip-rate biases on shopping, leisure, and short trips are partly caused by the mixed-mode design; in contrast, quantities of time spent in the transportation system, trips made by car and public transportation, and commuting trips are hardly biased.

     

From traces to trajectories: How well can we guess activity locations from mobile phone traces?

Passively generated mobile phone dataset is emerging as a new data source for research in human mobility patterns. Information on individuals’ trajectories is not directly available from such data; they must be inferred. Many questions remain in terms how well we can capture human mobility patterns from these datasets. Only one study has compared the results from a mobile phone dataset to those from the National Household Travel Survey (NHTS), though the comparison is on two different populations and samples. This study is a very first attempt that develops a procedure to generate a simulated mobile phone dataset containing the ground truth information. This procedure can be used by other researchers and practitioners who are interested in using mobile phone data and want to formally evaluate the effectiveness of an algorithm.To identify activity locations from mobile phone traces, we develop an ensemble of methods: a model-based clustering method to identify clusters, a logistic regression model to distinguish between activity and travel clusters, and a set of behavior-based algorithms to detect types of locations visited. We show that the distribution of the activity locations identified from the simulated mobile phone dataset resembles the ground truth better than the existing studies. For home locations, 70% and 97% of identified homes are within 100 and 1000 m from the truth, respectively. For work places, 65% and 86% of the identified work places are within 100 and 1000 m from the true ones, respectively. These results point to the possibility of using these passively generated mobile phone datasets to supplement or even replace household travel surveys in transportation planning in the future.     

Modeling real-time human mobility based on mobile phone and transportation data fusion

Even though a variety of human mobility models have been recently developed, models that can capture real-time human mobility of urban populations in a sustainable and economical manner are still lacking. Here, we propose a novel human mobility model that combines the advantages of mobile phone signaling data (i.e., comprehensive penetration in a population) and urban transportation data (i.e., continuous collection and high accuracy). Using the proposed human mobility model, travel demands during each 1-h time window were estimated for the city of Shenzhen, China. Significantly, the estimated travel demands not only preserved the distribution of travel demands, but also captured real-time bursts of mobility fluxes during large crowding events. Finally, based on the proposed human mobility model, a predictive model is deployed to predict crowd gatherings that usually cause severe traffic jams.     

Passengers’ activities during short trips on the London Underground

The present study considers underground passengers and investigates the ways in which they spend their time during a trip of average length or shorter. Using a structured procedure that had been refined after a preliminary study, more than 1,700 passengers were observed in London. The results showed that even when the length of travel is very short (2–6 stops), underground passengers engage in several occupations, especially those involving the use of mobile Information and Communication Technologies. These occupations depend on the specific spatial and temporal conditions of the travel, as well as on gender and age. These results should be useful in designing travel services that enhance passengers’ experiences; they also suggest a criterion for comparing trips using different transportation modes (i.e., looking at the time point during the trip at which the ratio of active versus passive occupations changes).     

国家级综合运输枢纽型城市发展策略研究

以南京市为例,从枢纽型城市整体构建、综合运输通道系统、综合运输枢纽集疏运体系、保障策略四个方面综合提出构建国家级综合运输型城市的发展策略。     

Understanding travellers’ preferences for different types of trip destination based on mobile internet usage data

New mobility data sources like mobile phone traces have been shown to reveal individuals’ movements in space and time. However, socioeconomic attributes of travellers are missing in those data. Consequently, it is not possible to partition the population and have an in-depth understanding of the socio-demographic factors influencing travel behaviour. Aiming at filling this gap, we use mobile internet usage behaviour, including one’s preferred type of website and application (app) visited through mobile internet as well as the level of usage frequency, as a distinguishing element between different population segments. We compare the travel behaviour of each segment in terms of the preference for types of trip destinations. The point of interest (POI) data are used to cluster grid cells of a city according to the main function of a grid cell, serving as a reference to determine the type of trip destination. The method is tested for the city of Shanghai, China, by using a special mobile phone dataset that includes not only the spatial-temporal traces but also the mobile internet usage behaviour of the same users. We identify statistically significant relationships between a traveller’s favourite category of mobile internet content and more frequent types of trip destinations that he/she visits. For example, compared to others, people whose favourite type of app/website is in the “tourism” category significantly preferred to visit touristy areas. Moreover, users with different levels of internet usage intensity show different preferences for types of destinations as well. We found that people who used mobile internet more intensively were more likely to visit more commercial areas, and people who used it less preferred to have activities in predominantly residential areas.     

Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data

Accessibility is a key concept in transportation research and an important indicator of people’s quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents’ real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone’s real-travel covered area. We then apply this DMAG methodology to Shanghai’s central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.     

Policy Simulation for New BRT and Area Pricing Alternatives Using an Opinion Survey in Jakarta

Abstract

An area pricing scheme for Jakarta, Indonesia, is currently under review as a transportation control measure along with the operation of new bus rapid transit (BRT) system. While this scheme may be effective for congestion reduction in the central business district (CBD), provision of alternative means of transportation for auto users that are ‘pushed-out’ is of great importance to obtain public acceptance. Hence, it is necessary to simulate simultaneously the area pricing scheme and the BRT development which may serve as an alternative for assumed ‘pushed-out’ auto users. Utilizing data from an opinion survey, this paper studies how BRT and auto ridership are likely to vary as a function of traveler and system attributes. Additionally, the study attempts to evaluate the way this new travel mode is distinguished from other existing conventional transportation alternatives in Jakarta. The survey data contains socioeconomic information of over 1000 respondents as well as details of to-work/school trips to the CBD including mode, travel cost, time, etc. Respondents were asked about their willingness to shift from their current mode to BRT to make the same travel for different BRT fare levels. Modeling efforts suggest that a mixed logit model performs better in explaining choice behavior. Therefore, this model was used for policy simulation. The simulation results brought about many implications as to the tested policies. While the developed models may be applied only to future BRT corridors in which the survey was conducted, they capture the key variables that are significant in explaining mode choice behavior and present great potential for practical use in policy simulation and analysis in a large metropolitan area of the developing world.     

Exploratory analysis of Zipf’s universal power law in activity schedules

People’s behavior is governed by extremely complex, multidimensional processes. This fact is well-established in the transportation research community, which has been working on travel behavior (travel demand) models for many years. The number of degrees of freedom in a person’s activity schedule is enormous. However, the frequency of occurrence of day-long activity schedules obeys a remarkably simple, scale-free distribution. This particular distribution has been observed in many natural and social processes and is commonly referred to as Zipf’s law, a power law distribution. This research provides evidence that activity schedules from various study areas exhibit a universal power law distribution. To this end, an elaborate analysis using 13 household travel surveys from diverse study areas discusses the effect of proportional outlier removal on the power law’s exponent value. Statistical evidence is provided for the hypothesis that activity schedules in all these datasets exhibit a power law distribution with a common exponent value. The study proposes that a Zipf power law could be used as an additional dimension within a travel demand model’s validation process. Contrary to other validation methods, no new data is required. The observation of a Zipf power law distribution in the generated schedules appears to be a necessary condition. Additionally, the universal activity schedule distribution might enable the full integration of activity schedules in models based on universal mobility patterns.

     

Mobile phone data in transportation research: methods for benchmarking against other data sources

The ubiquity of personal cellular phones in society has led to a surging interest in using Big Data generated by mobile phones in transport research. Studies have suggested that the vast amount of data could be used to estimate origin–destination (OD) matrices, thereby potentially replacing traditional data sources such as travel surveys. However, constructing OD matrices from mobile phone data (MPD) entails multiple challenges, and the lack of ground truth hampers the evaluation and validation of the estimated matrices. Furthermore, national laws may prohibit the distribution of MPD for research purposes, compelling researchers to work with pre-compiled OD matrices with no insight into the methods used. In this paper, we analyse a set of such pre-compiled OD matrices from the greater Oslo area and perform validation procedures against several sources to assess the quality and robustness of the OD matrices as well as their usefulness in transportation planning applications. We find that while the OD matrices correlate well with other sources at a low resolution, the reliability decreases when a finer level of detail is chosen, particularly when comparing shorter trips between neighbouring areas. Our results suggest that coarseness of data and privacy concerns restrict the usefulness of MPD in transport research in the case where OD matrices are pre-compiled by the operator.

     

Assessing the quality of intercity road transportation of passengers: An exploratory study in Brazil

In Brazil, buses represent the main mode of public transportation. However, in recent years intercity and interstate bus companies have been facing a growing competition with other forms of transportation such as bus companies competitors, illegal transportation companies, chartered buses, and, more recently, air companies. In this scenario characterized by growing competition, it is essential to evaluate the quality of road transportation of passengers. In order to contribute to the analysis of this issue, this paper presents a methodological approach to assess the quality of intercity road transportation of passengers, according to the customers’ perspective. By conducting a case study in a city of almost 500,000 inhabitants from the interior of Rio de Janeiro, an Importance–Satisfaction Analysis (ISA) and an assignment procedure were used in order to obtain: (i) the main factors (criteria) that influence the quality of service intercity road transportation of passengers, (ii) the importance degree of criteria related to road transportation of passengers, (iii) the satisfaction of the users of road transportation under the considered criteria, (iv) the critical criteria/items, and (v) the categories which best represent the quality of service intercity road transportation according to the passengers’ perspective. Finally, several possible corrective actions to improve the quality of services considering each critical item/criterion were highlighted and special recommendations were done for the critical process (ticket sales).     

Effects of incorporating latent and attitudinal information in mode choice models

Abstract

Hybrid choice modelling approaches allow latent variables in mode choice utility functions to be addressed. However, defining attitude and behavior as latent variables is influenced by the researcher's assumptions. Therefore, it is better to capture the effects of latent behavioral and attitudinal factors as latent variables than defining behaviors and attitudes per se. This article uses a hybrid choice model for capturing such latent effects, which will herein be referred to as modal captivity effects in commuting mode choice. Latent modal captivity refers to the unobserved and apparently unexplained attraction towards a specific mode of transportation that is resulting from latent attitude and behavior of passengers in addition to the urban transportation system. In empirical models, the latent modal captivity variables are explained as functions of different observed variables. Empirical models show significant improvement in fitting observed data as well as improved understanding of travel behavior.     

The San Francisco Travel Quality Study: tracking trials and tribulations of a transit taker

In helping understand the dynamics of travel choice behavior and traveler satisfaction over time, multi-day panel data is invaluable (McFadden in Am Econ Rev 91(3): 351–378, 2001). The collection of such data has become increasingly feasible thanks to smartphones, which researchers can use to present surveys to travelers and to collect additional information through the phones’ location services and other sensors. This paper describes the design and implementation of the San Francisco Travel Quality Study, a multi-day research study conducted in autumn 2013 with 838 participants. The objective of the study was to investigate the link between transit service quality, the satisfaction and subjective well-being of transit riders, and travel choice behavior, with a particular interest in the influence of travelers’ choice history and personal experiences on future transit use. For that purpose, a rich panel data set was collected from multiple sources, including a number of mobile travel experience surveys capturing traveler satisfaction and emotions, two online surveys capturing demographics, attitudes and mode choice intentions, as well as high-resolution phone location data and transit vehicle location data. By fusing the phone location data with transit vehicle location data, individual-level transit travel diaries could be automatically created, and by fusing the location data with the survey responses, additional information about the context of the responses could be derived. While the behavioral and satisfaction-related findings of the study are detailed in other publications, this paper is intended to serve two purposes. First, it describes the study design, data collection effort and challenges faced in order to provide a learning opportunity for other researchers considering similar studies. Second, it discusses the key sociodemographic data and characteristics of the study population in order to provide a foundation and reference for further publications that make use of the data set described here. The authors would like to invite other researchers to collaborate with them on the evaluation of the data.     

Using spike model to reduce traffic congestion and improve public transportation in Malaysia

In this study, passengers’ willingness to pay (WTP) for and willingness to accept (WTA) improved public transportation and shift to public transportation in Malaysia were examined. Specifically, this study aimed to determine the factors or transport attributes that affect passenger WTA and WTP to shift to public transportation. The adopted methodology was based on a contingent valuation (CV) survey, which was conducted on a representative sample of a cross section in residents of Kajang, in Malaysia. This CV primary survey elicited the demand of passengers for improved public transportation. The spike model was adopted to avoid estimation errors caused by a large percentage of respondents who were unwilling to pay and accept at all. The estimation results showed that the best reduction rate for both travel time and cost was 45% among other amounts that range from 15% to 75%. The best parking cost increment was US$0.30 and the average WTP is US$0.68.     

Mobile phone use by young drivers: effects on traffic speed and headways

Abstract

This paper investigates the effects of mobile phone use while driving on traffic speed and headways, with particular focus on young drivers. For this purpose, a field survey was carried out in real road traffic conditions, in which drivers' speeds and headways were measured while using or not using a mobile phone. The survey took place within a University Campus area, allowing to distinguish between settings approximating to either free flow or interrupted flow conditions. Linear and loglinear regression methods were used to investigate the effects of mobile phone use and several other young driver characteristics, such as gender, driving experience and annual distance travelled, on vehicle speeds and headways. Separate models were developed for average free flow, interrupted flow, as well as for total average speed. Results show that mobile phone use leads to a statistically significant reduction in traffic speeds of young drivers in all types of traffic conditions. Furthermore, male and female drivers reduce their speed similarly when using a mobile phone while driving. However, male drivers using their mobile phone drive at lower speeds than female drivers not using their mobile phones. Sensitivity analysis revealed that, among all explanatory variables, the effect of mobile phone use on speed was most important. Accordingly, vehicle headways appear to increase for drivers using their mobile phone. However, this effect could not be statistically validated, due to the strong correlation between speed and headway.     

Medical-purposed travel behaviors in rural areas in developing countries: a case study in rural Cambodia

This study aimed at identifying influencing factors in an individual’s choice of health service facility and transportation mode to the facility, using two datasets: one collected through face-to-face interviews held between February and March 2016, containing responses from 258 local residents, and the other collected from 45 residents in the follow-up survey in December 2016. The study area was located in rural Cambodia, where road conditions were recently improved and a health sector policy was implemented to assist poor people in accessing to health services. An empirical analysis was carried out using nested logit models, consisting of two choices of three travel modes (private, shared, or walking) and two types of public health service facilities (health center or referral hospital). The results revealed the following: (1) individuals in households with motorcycles tend to visit health service facilities using private travel modes, whereas individuals in households without their own transportation tend to visit health service facilities using shared travel modes or on foot, and (2) travel distance between individuals’ houses and the selected facilities likely discourages people from visiting referral hospitals, where a variety of health services are available, but does not affect the choice of health centers, offering limited health services while being located closer to residential areas. These findings suggested the need to equip health centers with more functions as health service providers and to operationalize public transportation services for those who cannot afford to visit referral hospitals, which would enable people to receive necessary health services more conveniently.

     

站城融合理念下高铁客运枢纽区域步行交通布置研究

本文对高铁客运枢纽区域内步行交通的影响范围和功能定位进行分析,提出在站城融合理念下,步行交通是高铁客运枢纽最重要的交通方式。利用开源数据,对比我国京沪高铁沿线与日本东海道新干线,以及北京南站、上海虹桥站、东京站、名古屋站,分析枢纽步行交通的影响因素,并提出站城融合背景下枢纽步行交通系统的规划建设重点和指标体系,为高铁客运枢纽实现站城融合、建立完善的步行交通系统提供参考。     

Passengers’ Perceived Service Quality of City Buses in Taipei: Scale Development and Measurement

Abstract

To understand fully passengers’ perceptions and expectations of the bus service quality in Taipei, business managers and governmental agencies must seek a proper scale that can reflect passengers’ opinions accurately. This study develops and tests a service quality scale designed for a city bus transit system in Taipei. Churchill’s paradigm and a focus group interview were combined into a multistage scale development procedure. Based on the procedure, Taipei city buses were selected as the example, for which a service quality scale was developed. The final scale contains four dimensions and 20 items. These four dimensions are ‘interaction with passengers’, ‘tangible service equipment’, ‘convenience of service’ and ‘operating management support’. Finally, the results of scale development and the managerial applications of the service quality scale for the city transit system are discussed.     

Transportation carbon dioxide emissions by built environment and family lifecycle: Case study of the Osaka metropolitan area

How a city grows and changes, along with where people choose to live likely affects travel behavior, and thus the amount of transportation CO₂ emissions that they produce. People generally go through different stages in their life, and different travel needs are associated with each. The impact of the built environment may vary depending on the lifecycle stage, and the years spent at each stage will differ. A family with children may last for twenty to thirty years, while the time spent without dependents might be short in comparison. Over a family’s lifecycle, how big of a difference might the built environment, through household location choice, have on the amount of transportation CO₂ emissions produced? From a climate change perspective, how significant is residential location on the CO₂ produced by transportation use? This paper uses data from the Osaka metropolitan area to compare the direct transportation CO₂ emissions produced over a family’s lifecycle across five different built environments to determine whether any are sustainable and which lifecycle stage has the greatest overall emissions. This understanding would enable the design of a targeted policy based on household lifecycle to reduce overall transportation CO₂ of individuals throughout one’s lifecycle. The yearly average per-capita family lifetime transportation CO₂ emissions were 0.25, 0.35, 0.58, 0.78, and 0.79 metric tonnes for the commercial, mixed-commercial, mixed-residential, autonomous, and rural areas respectively. The results show that only the commercial and mixed-commercial areas were considered to be sustainable from a climate change and transportation perspective.