Catherine Morency

Relative Accessibility Deprivation Indicators for Urban Settings: Definitions and Application to Food Deserts in Montreal

Accessibility research, within the context of the social exclusion dimensions of transport, has provided valuable tools to understand the potential of people to reach daily life activity locations. In this paper, model-based estimates of distance travelled are used to calculate a cumulative opportunities measure of accessibility. Multivariate, spatially expanded models produce estimates of distance travelled that are specific to both geographical location and type of individual. Opportunity landscapes obtained based on these estimates are used for comparative accessibility analysis by means of what are termed relative accessibility deprivation indicators. The indicators proposed are demonstrated with a case study of food deserts in the city of Montreal, Canada. The results of the analysis illustrate the variations in accessibility between individuals in low-income households and the reference group, and the effect of vehicle ownership for accessibility to food services, thus highlighting the social exclusion implications of these factors.

MINING PUBLIC TRANSPORT USER BEHAVIOUR FROM SMART CARD DATA

Abstract In urban public transport, smart card data is made of millions of observations of users boarding vehicles over the network across several days. The issue addresses whether data mining techniques can be used to study user behaviour from these observations. This must be done with the help of transportation planning knowledge. Hence, this paper presents a common “transportation planning/data mining” methodology for user behaviour analysis. Experiments were conducted on data from a Canadian transit authority. This experience demonstrates that a combination of planning knowledge and data mining tool allows producing travel behaviours indicators, mainly regarding regularity and daily patterns, from data issued from operational and management system. Results show that the public transport users of this study can rapidly be divided in four major behavioural groups, whatever type of ticket they use..

Accessibility to health care facilities in Montreal Island: an application of relative accessibility indicators from the perspective of senior and non-senior residents

BackgroundGeographical access to health care facilities is known to influence health services usage. As societies age, accessibility to health care becomes an increasingly acute public health concern. It is known that seniors tend to have lower mobility levels, and it is possible that this may negatively affect their ability to reach facilities and services. Therefore, it becomes important to examine the mobility situation of seniors vis-a-vis the spatial distribution of health care facilities, to identify areas where accessibility is low and interventions may be required.MethodsAccessibility is implemented using a cumulative opportunities measure. Instead of assuming a fixed bandwidth (i.e. a distance threshold) for measuring accessibility, in this paper the bandwidth is defined using model-based estimates of average trip length. Average trip length is an all-purpose indicator of individual mobility and geographical reach. Adoption of a spatial modelling approach allows us to tailor these estimates of travel behaviour to specific locations and person profiles. Replacing a fixed bandwidth with these estimates permits us to calculate customized location- and person-based accessibility measures that allow inter-personal as well as geographical comparisons.DataThe case study is Montreal Island. Geo-coded travel behaviour data, specifically average trip length, and relevant travellers attributes are obtained from the Montreal Household Travel Survey. These data are complemented with information from the Census. Health care facilities, also geo-coded, are extracted from a comprehensive business point database. Health care facilities are selected based on Standard Industrial Classification codes 8011-21 (Medical Doctors and Dentists).ResultsModel-based estimates of average trip length show that travel behaviour varies widely across space. With the exception of seniors in the downtown area, older residents of Montreal Island tend to be significantly less mobile than people of other age cohorts. The combination of average trip length estimates with the spatial distribution of health care facilities indicates that despite being more mobile, suburban residents tend to have lower levels of accessibility compared to central city residents. The effect is more marked for seniors. Furthermore, the results indicate that accessibility calculated using a fixed bandwidth would produce patterns of exposure to health care facilities that would be difficult to achieve for suburban seniors given actual mobility patterns.ConclusionsThe analysis shows large disparities in accessibility between seniors and non-seniors, between urban and suburban seniors, and between vehicle owning and non-owning seniors. This research was concerned with potential accessibility levels. Follow up research could consider the results reported here to select case studies of actual access and usage of health care facilities, and related health outcomes.

How Carsharing Affects the Travel Behavior of Households: A Case Study of Montréal, Canada

ABSTRACT Although carsharing is spreading across the world, few studies have examined its collective benefits. There is a need to analyze the socio-demographic features of users, and assess the role and impact of carsharing on the overall travel behaviors of their households. This article compares the results of two simultaneous surveys in the Montréal area: a web-based survey among carsharing users; and a regional, large-scale household travel survey. Results show a significant difference in modal split of car use between carsharing users and typical residents, for various types of households and levels of carsharing use. In all cases, carsharing members never reached the level of car use observed in the population.

Analysing the Variability of Transit Users Behaviour with Smart Card Data

This paper proposes various measures regarding the variability of travel behaviours of transit users. The analyses are performed with smart card data collected over a ten months period. The variability in terms of boarding per day and new stops frequented with the days of travel on the transit network is examined. Data mining techniques are then used to classify days of travel according to the similarity of the boarding time periods. In this view, the use of two specific smart cards is examined in more details. These experiments first show that the behaviours of regular transit users evolve with time both in terms of transit stops frequented and time of boarding. Hence, variability of behaviours also changes for various user types

Calculation of Transit Performance Measures Using Smartcard Data

This paper illustrates the use of smartcard data to estimate various transit performance measures. Combined with well-established evaluation processes, such measures can help operators monitor their networks in greater detail. The performance of the network supply and the statistics on passenger service can be calculated from these datasets for any spatial or temporal level of resolution, including route and bus stop levels.

Activity Spaces and the Measurement of Clustering and Exposure: A Case Study of Linguistic Groups in Montreal

Population segregation measurement is a topic of broad interest in the social sciences. In this paper we draw from recent advances in the spatial analysis literature to derive individualized measures of clustering and exposure. Recent research on accessibility has seen a shift from place-based measures to person-based ones. Similarly, the notion of residential clustering and exposure patterns, while typically related to the distribution of population in zonal systems, can be modified to account for heterogeneous experiences of urban space. In particular, at the individual level, the degree of clustering and exposure is related to personal mobility and the individual experience of space. In this paper we turn to the question of whether individuals belonging to different groups and living in different areas of a city observe differences in their clustering and exposure to population groups over space. The proposed procedure is applied empirically to the case of Montreal to explore how native English speakers of various levels of mobility experience exposure.

Estimation of Frequency and Length of Pedestrian Stride in Urban Environments with Video Sensors

An emphasis on active modes of transportation, that is, walking and cycling, has recently been renewed amid concerns for the environment and public health. However, the focus of research and practice that these modes have traditionally received is secondary to that received by motorized modes. As a consequence, the data on pedestrians (in particular, microscopic data) required for analysis and modeling are lacking. For instance, accurate data on the length of individual stride are not available in the transportation literature. This paper proposes a simple method to extract frequency and length of pedestrian stride automatically from video data collected nonintrusively in outdoor urban environments. The walking speed of a pedestrian oscillates during each stride; the oscillation can be identified through the frequency analysis of the speed signal. The method was validated with real-world data collected in Rouen, France, and Vancouver, Canada, where the root mean square errors for stride length were 6.1 and 5.7 cm, respectively. A method to distinguish pedestrians from motorized vehicles is proposed and used to analyze the 50 min of the Rouen data set to provide the distributions of stride frequency and length.

How Many Steps Do You Have in Reserve? Thoughts and Measures About a Healthier Way to Travel

The aim of this study was to estimate the benefits that people could achieve by trading their car for a nonmotorized mode of travel, such as walking, to make their short daily trips. For this purpose, detailed information on travel behavior gathered through large-scale travel surveys conducted in the greater Montreal, Quebec, Canada, area was used. The travel behavior observed in recent travel surveys was analyzed to estimate the number of short trips for various population segments. These surveys gathered travel and sociodemographic information for approximately 5% of the population. Data from the 2003 survey revealed that more than 7 million motorized trips were made during a typical weekday; 862,000 (11.7%) were shorter than 1.6 km (1 mi). With the appropriate speed and stride for each population segment, these motorized kilometers were converted into numbers of steps to appraise the potential physical activity benefits of making these short trips by foot instead of by a motorized mode. The results show that about 837,000 motorized kilometers could be converted into almost 1,156 million steps every day. Overall, 12.5% of the population had steps in reserve, an average of 2,660 steps per person. Such a shift in mode choice could help some people meet their required physical activity volumes through their daily travel patterns while helping to save energy, reduce pollution, and mitigate traffic congestion.

Object-Oriented Analysis of Carsharing System

Carsharing systems are gaining new members every month. However, few studies formally define the system and illustrate the systematic processing of administrative data sets to estimate indicators regarding both demand and supply objects. The first outcome of this research is the definition of the object model for a carsharing system. Rich transaction data sets, generally used for the production of monthly bills, are used to estimate indicators describing how the carsharing system is used in the Montreal area of Quebec, Canada. Indicators describing the main objects of the system—members, trip chains (transactions), cars, and stations—are estimated by using continuous data. The demand object analysis focuses on the study of members and their trip chains using the shared cars. The analysis shows that carsharing members are younger than the overall population, with an overrepresentation of 25- to 39-year-olds. The persistency of active members within the carsharing system is estimated at around 60% after 4 months and 50% after 12 months. The supply–objects analysis focuses on the study of cars and stations. Spatial dispersion of members with respect to stations used and typical use of cars is illustrated over long periods. With the increase in the number of members, transactions, cars, and stations, carsharing organizations need to find new ways to manage growth and optimize their networks. A clearer understanding of how their systems are used will help them develop enhanced planning and modeling abilities.