Probabilistic model for destination inference and travel pattern mining from smart card data

Transportation - Inferring trip destination in smart card data with only tap-in control is an important application. Most existing methods estimate trip destinations based on the continuity of trip...     

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.

     

Between-mode-differences in the value of travel time: Self-selection or strategic behaviour?

Using stated preference survey data, we measure the value of travel time for several transport modes. We find, like many before us, that the value of travel time varies across modes in the opposite direction of what would be the consequence of differences in comfort. We examine three candidate causes for the observed differences: Comfort effects, self-selection and strategic behaviour of respondents. Using experiments with both the current and an alternative mode we find that the differences in the value of travel time are consistent with self-selection and comfort effects. Moreover, respondents having bus as the current or the alternative mode seem not to value comfort differently across modes. Strategic behaviour seems to play no role.     

An analysis of the Spanish high capacity road network criticality

The analysis of complex networks has been carried out in different fields using an ample variety of method and concepts. Recently, in the general literature of regional economics, the concepts of resilience, connectivity, vulnerability and criticality have been gaining their momentum. The aim of this paper is to provide an analytical framework, using well-known accessibility indicators, in order to calculate the critical links or road sections of the Spanish high-capacity road network. Our analysis will be based on approximately four hundred sections that will be classified in five different groups according to their criticality degree in the whole network. Our analysis will be complemented with the comparison of the results obtained in five different scenarios, namely the average criticality using the effects on the whole country, Madrid, Barcelona, Valencia and Pontevedra. Furthermore, the paper will also analyze what kind of intrinsic characteristics of the sections favor or not the links’ criticality using a method based on a classification and regression tree. This analysis is crucial to understand other important concepts that are recently being studied in network and spatial economics, like, for example, resilience and vulnerability. It is concluded that the number of relations or routes, being a trunk or not, the road density and the time to Madrid capital play an important role in the criticality of the roads section in the high capacity road network.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.

     

A fractional perspective to the modelling of Lisbon’s public transportation network

Transportation - Urban growth originates multiscale spatial patterns, such as those of transportation networks. Here, the public transportation network (PTN) of the city of Lisbon is analysed from...     

Forme urbaine et mobilité domicile-travail dans 13 aires urbaines françaises : une analyse multiéchelle

This article provides a multi-scale analysis of the links between commuting patterns and urban form by using both morphological and more classical indicators of urban form (like density). Thirteen French urban areas of more than 500,000 inhabitants (excluding Paris) are compared. The findings highlight the complexity of the links between urban form and commuting patterns because the same indicators of urban form do not have the same influence according to the spatial scale. Even if the influence of the morphological indicators is lower than that of more classical socioeconomic variables (income level, motorization rate), our study discusses the various and multi-scale consequences of urban development on daily travel behaviour.     

A GPS-aided survey for assessing trip reporting accuracy and travel of students without telephone land lines

A geo-positioning satellite (GPS)-based survey, using a web-based prompted recall tool, was conducted on a sample of 94 students at the University of Toronto from November 2008 to April 2009. The sample included students with and without telephone land lines, allowing for a statistical comparison of demographic and travel behaviour attributes. The same subjects simultaneously completed a traditional trip reporting survey, modelled on the household travel survey in Toronto, allowing for a comparison between the travel behaviour information obtained from the GPS and that reported by the participants in the traditional survey. Students with a land line are more likely to live in houses, with parents, and to live in suburban areas than students without a land line. They also make fewer trips in total, fewer discretionary trips, more transit and auto trips and fewer active trips than students without a land line. By comparing questionnaire-based data and GPS data, we found that most participants reported in the questionnaire either the same number of GPS-based trips or fewer. On average, the GPS survey captured 1.29 more daily trips per participant than the corresponding trips reported in the questionnaire.