Studying patterns of use of transport modes through data mining - Application to U.S. national household travel survey data set

Data collection activities related to travel require large amounts of financial and human resources to be conducted successfully. When available resources are scarce, the information hidden in these data sets needs to be exploited, both to increase their added value and to gain support among decision makers not to discontinue such efforts. This study assessed the use of a data mining technique, association analysis, to understand better the patterns of mode use from the 2009 U.S. National Household Travel Survey. Only variables related to self-reported levels of use of the different transportation means are considered, along with those useful to the socioeconomic characterization of the respondents. Association rules potentially showed a substitution effect between cars and public transportation, in economic terms but such an effect was not observed between public transportation and nonmotorized modes (e.g., bicycling and walking). This effect was a policy-relevant finding, because transit marketing should be targeted to car drivers rather than to bikers or walkers for real improvement in the environmental performance of any transportation system. Given the competitive advantage of private modes extensively discussed in the literature, modal diversion from car to transit is seldom observed in practice. However, after such a factor was controlled, the results suggest that modal diversion should mainly occur from cars to transit rather than from nonmotorized modes to transi

Relationship between Travel-Related Feelings, On-Trip Activities, and use of various Transport Means in Urban Areas

A key issue in contemporary transport research is how to achieve a better balance in the use of various travel means in urban areas, in particular, how to promote the use of both transit and active modes (feet, bicycle). However, such behavioral changes cannot be achieved fully through acting only on the relative performances of the means themselves, for example, in terms of travel times and costs. This study considered some dimensions of the traveling experience—whether the trip was important only for reaching a destination, whether it was tiring, whether it was pleasant or unpleasant—and related these aspects to the completion of activities during the trip and to the use of various transport modes. Correspondence analysis and association analysis were jointly developed for some categorical variables of the French National Travel Survey. Such a combined technique uses the strengths of each method and has proved its effectiveness. The method potentially could be used with unstructured and dispersed data sets such as so-called big data sets. The results show that, all else being equal, evaluations often depend more on a person traveling alone or with others than on the travel means used. Previous research results related to the symbolic and affective value of driving were confirmed for traveling alone, whereas the experience of traveling with others as a driver or a passenger was more similar to the use of transit service