Earlier studies suggest that motorists are more exposed to air pollutants than are active transportation users.
A number of traffic congestion studies [1, 2, 3] focused on improving transportation system but not transportation users' feelings.
A series of structural equation modelling estimations was carried out, using empirical surveys among road-based public transportation users in three major urban areas: Jakarta, Bandung and Yogyakarta.
The proposed intelligent decision support system (Onto-CBR) is implemented to an itinerary search problem for freight transportation users in urban areas.
A random sampling survey was taken in Shanghai, China during August 1st to August 31st in 2009 to collect data for this research, including transportation users' attitudes about road traffic congestion, baseline transportation characteristics of transportation users, their reactions to traffic congestion and sociodemographics.
Presently, more and more researchers [4, 5] realize that it is not enough to just study transportation system capacity, and transportation users' feelings and reactions are also important to decide how to relieve traffic congestion.
Last year we reported how Moovit was trying to reproduce Waze's success with private car owners, but this time with public transportation users.
Many frequent public transportation users in SF have been using the Clipper Card, a contactless payments and ticketing card, for a number of years in the city.
However, the results indicate that the facility is also attracting public transportation users to shift to multi-mode travel, where a car is used to commute to the park-and-ride facility.
It is an important point to know transportation users' feelings and reactions about urban road traffic congestion, which can help decision makers to make more efficient and useful policies and strategies.
