Open AccessEvaluating cyclist patterns using GPS data from smartphones
Author(s) -
Rupi Federico,
Schweizer Joerg
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2017.0285
Subject(s) - global positioning system , shortest path problem , matching (statistics) , computer science , path (computing) , trips architecture , transport engineering , constrained shortest path first , work (physics) , geography , statistics , mathematics , k shortest path routing , computer network , engineering , telecommunications , mechanical engineering , graph , theoretical computer science
GPS traces from cyclists are used to retrieve their path by matching the traces to a detailed, attribute‐rich urban road network. The main objective of this research is to explore the influence of road network characteristics on the cyclist's path choice behaviour. The dataset used in this study consists of ∼27,500 GPS traces, which cyclists have recorded in Bologna, Italy, over a period of 4 weeks using a special smartphone application. Work trips are extracted from all traces by selecting only straight trips during the mornings of work days. After matching the traces to a specially prepared road map, the distributions of trip length, trip time and trip speed are determined. The shortest possible path between origin and destination of each trip is determined and compared with the chosen path. Results show that most cyclists tend to use the shortest path and accept only small detours. However, comparing the shortest path with the chosen path for each trip, it is possible to identify the network characteristics causing the cyclists to deviate from the shortest path. The main results of this study indicate that the chosen paths contain more cycleways and less intersections compared with the respective shortest paths.