Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach

This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility.     

Investigating the capacity of continuous household travel surveys in capturing the temporal rhythms of travel demand

Transportation - Continuous household travel surveys have been identified as a potential replacement for traditional one-off cross-sectional surveys. Many regions around the world have either...     

The ambivalence of ridesharing

Ridesharing is quite a popular topic of discussion among transport authority personnel. It is perceived to be a viable alternative to classical modes of transportation, and receives a great deal of political support from transport planners. However, not much objective information is available on ridesharing behaviors. We use travel survey data to study the evolution of the ridesharing market in an urban area. Our study is based on data from four large-scale OD surveys conducted in the Greater Montreal Area (1987, 1993, 1998 and 2003). In the latest survey conducted in Montreal, car passengers were asked to identify the driver who gave them the opportunity to travel in this way. Their answers were classified according to the type of driver; for instance, a member of their household, a neighbor or a co-worker. We use this information to calibrate a model matching car passengers and car drivers belonging to the same household. This will be referred to as IHHR (intra-household ridesharing). Preliminary results reveal that approximately 70% of all trips made by car passengers are the result of IHHR. Furthermore, around 15% of those trips are questionable, in that they were exclusively generated for another individual’s purposes, consequently generating an additional trip for the journey back home. Moreover, this percentage increased over time. Objective data regarding ridesharing and its evolution in an urban area will undoubtedly help decision makers gain a clearer profile of this means of travel and help to realign attitudes on the issue.

Enhancing the Travel Survey Process and Data Using the CATI System

Abstract

This paper describes an intelligent interface developed to assist in the task of collecting detailed information regarding daily travel behaviours. The computer-assisted telephone interview (CATI) system, developed by the MADITUC Research Group for the Montreal large-scale travel surveys, is structured in three main screens (household, person and trip) and assists the interaction between an interviewer and a respondent during a phone interview. This tool enhances the quality of the data collected by performing real-time validation of the spatio-temporal details related to travel behaviours. In addition to describing the design of the CATI tool, this paper proposes some empirical measurements associated with the CATI use by the interviewers owing to the processing of numerical logs saving every action taken by the user during an interview. Using these data, variables significantly influencing interview duration are identified.     

De la légitimité du transport en commun au Québec : un exemple simple de mesure de ses contributions au développement durable

While authorities consider transit as one of the solutions to enhance sustainable mobility, they do not provide a steady funding for its operation and growth. This inconsistency between political discourse and real intervention has motivated nine transit operators from six metropolitan areas of Quebec to conduct a study on the contribution of transit to sustainability. This article first presents the process of selecting indicators. For some of the indicators developed, the estimation method is detailed, which comprises of the following factors: resources, emission prevention, contribution to daily physical activity, accessibility to public transit and to activity locations, daily savings of using transit in comparison with car use, and the relative safety of transit use. Finally, the article explains the conceptual, methodological, and informational challenges that influenced the selection of indicators and their estimation methodologies.     

Geodemographic analysis and the identification of potential business partnerships enabled by transit smart cards

Smart card automated fare payment systems are being adopted by transit agencies around the world. The data-storage characteristics of smart cards present novel opportunities to enhance transit services. On the one hand, there are fare policies, where smart card holders are given specific rebates on the use of the service based on usage patterns or levels. On the other, there are non-fare policies, for instance if holders receive advantages, such as rebates and offers, from commercial partners. The purpose of this paper is to present a geodemographic framework to identify potential commercial partnerships that could exploit the characteristics of smart cards. The framework is demonstrated using data from Montreal, Canada. Household survey data, specifically trip ends, and business data points are jointly used to determine the exposure of various types of establishments to users of the Montreal Metro network. Spatial analysis of business establishments in the neighborhood of metro stations helps to identify potential commercial partners. The results illustrate the potential of geodemographic analysis to generate intelligence of commercial interest.     

Trend analysis of activity generation attributes over time

Activity generation models are relatively poorly developed in activity-based travel demand modelling frameworks. This research investigates whether observed distributions of activity attributes (activity frequency, start time and duration) used as inputs in the activity generation component of an activity-based travel demand model have changed over time. This research empirically examines changes in the distributions of activity generation attributes over time in the Greater Montreal area (GMA), Quebec, Canada. It also focuses on how these attributes vary with peoples’ socio-demographic characteristics. This research relies on the 1998, 2003 and 2008 origin–destination (O–D) household travel surveys of the GMA. The comparative analysis at three time points in a 10-year period clearly reveals that distributions of activity attributes are significantly changing over time. Work and school activities show similar trends; frequency “1” has increased and frequency “2+” has decreased over time. The occurrence of shopping activity on weekdays is decreasing over time. Start time and duration distributions for each activity have also changed significantly over time. The research allows preparing activity attributes for the application of an activity-based model, TASHA, such that they reflect temporal changes in travel behaviour of the GMA.     

Bridging the gap between complex data and decision-makers: an example of an innovative interactive tool

Abstract

The increasing capacity of technological tools, as well as the advent of geographic information systems, has multiplied the ability to process large sets of microdata. At the same time, modeling concerns and the quest for a more in-depth understanding of individual behaviors is requiring more, and better, data. The gap between scientific modeling and informational tools for decision-making seems to be widening.

In the Greater Montreal area, large sets of microdata have been available for more than 30 years. Along with the development of modeling and planning tools, particular attention has been given to the continuous enlightening of planners and decision-makers with respect to the outcomes of the various surveys. This has led to the development of particular interactive tools, specifically addressed at local planners, which present the most significant information regarding travel and demography, for geopolitically relevant areas.

This paper presents the most recent interactive tool that has been developed for local planners in the Montreal area. It integrates information from both the most recent travel survey held in the region and the Canadian census. It offers both ease of use and relevant analytical means to assist in exploring the complex relations between spatial locations, demographic features, and activity-travel indicators.     

Transit network design using a genetic algorithm with integrated road network and disaggregated O–D demand data

Transportation - Evolutionary algorithms have been used extensively over the past 2 decades to provide solutions to the Transit Network Design Problem and the Transit Network and Frequencies...     

Modeling isoexposure to transit users for market potential analysis

Transit operators face a difficult fiscal environment and an imperative to contribute to urban sustainability. Under these circumstances, operators must find innovative ways to make public transportation attractive to broader segments of the public, while simultaneously trying to raise revenue to reduce reliance on public subsidies. Development of commercial partnerships is seen as a promising way to achieve these goals. Previous research has examined the potential of using geodemographics to assist transit agencies in the task of identifying potential partners for developing mutually beneficial commercial agreements. In this paper we describe an approach to model isoexposure to transit users as a tool to assess market potential. The approach is based on the analysis of walking behavior of transit users, and specifically distance walked at the end of their transit trip. Spatial modeling is used to geographically project estimates of walking distance for a desired demographic profile at a specific transit facility. After expanding the estimates using sample weights, overlays of these estimates can be used to generate variations in exposure to transit travelers at different locations in space. The approach is demonstrated using the case of Metro users in Montreal, Canada. The case study demonstrates the use of isoexposure profiles as a novel approach to generate marketing intelligence. This should be of interest to transit agencies and businesses interested in developing partnerships.