Enhancing Travel Data Collection with an Emphasis on Active Transport

The promotion of active transport has been considered as a fundamentalobjective of transport planning policies since it can improve passenger’shealth, relieve traffic congestion, and reduce air pollution. However, theshare of active transport in planning studies has not traditionally beenestimated accurate enough. One of the main reasons for this problem is theinability of conventional travel survey methods to identify trips made byactive modes in the travel behaviour of individuals. Nowadays, theemployment of smartphones/GPS devices and elaborated algorithms hasimproved the accuracy of travel data collections. Yet, the accuracy ofcurrent algorithms in detecting active modes of transport is questionable.This paper addresses this concern by proposing a comprehensive andpractical framework for detecting trips especially those made by an activemode of transport. In this study, a smartphone application has beendeveloped in conjunction with an improved post-processing analysisframework. It is suggested to revise the conventional method of tripdetection and employ smoothing techniques after trip detection instead ofemployment on GPS raw data to improve the accuracy of data collection. Inaddition, important attributes for trip detection are applied in a rule-basedmodel. The results demonstrate that the model can detect trips moreaccurately compared to an active travel data collection approach, andincrease the number of detected active-mode trips by 22%. The proposedapproach can be employed in all GPS-assisted travel surveys, therebyimproving their accuracy and reduce the under-reporting rate, specificallyfor trips made by active modes of transport.

کلیدواژه ها:

Active transport ، Travel survey ، Smartphone ، GPS ، Framework