Page 45 - NGTU_paper_withoutVideo

Modern Geomatics Technologies and Applications

Path Finding by Use of Volunteered Geographic Information (VGI) To Increase Public
Health In Active Travel

1
Moein Molavi Gonabadi , Mohammad Taleai 1*

1 Faculty of Geodesy and Geomatics Engineering, K.N.Toosi University of Technology
Tehran, Iran
* taleai@kntu.ac.ir

Abstract: Emerging Volunteered Geographic Information (VGI) provides a promising data source with a high
spatial and temporal resolution for studying active travel. This study aims to examine the positive and negative aspects
of cycling by harnessing cycling trajectory data. For this purpose, exposure to air pollution as a negative effect of cycling
was computed. Also, associations of environmental characteristics with cycling were investigated and cycling count was
modeled as the popularity function based on the effective parameters. Finally, a pathfinding model was developed with
the popularity as the benefit parameter and the inhalation of air pollution as the cost parameter. The results of this
study give insights into identifying high-priority areas suitable for developing cycling infrastructure which can help
decision-makers in urban planning.

Keywords: Motor Vehicles, Active Travel, Volunteered Geographic Information, Environmental Characteristics,
Path Finding

1. Introduction
Population growth and urbanization have dramatically increased the use of motor vehicles which causes problems such
as heavy traffic and air pollution for the urban community [5]. The increasing use of vehicles has created problems such as
traffic congestion and subsequent air pollution, for urban communities. Exposure to air pollution has negative effects on
people's health, including increased risk of cardiovascular disease, respiratory disease and cancer [9]. Inhalation of air
pollution depends on the amount of pollution concentration and the duration of exposure [1]. Increased travel time and air
pollution are some of the major disadvantages of urban traffic. This causes citizens to be constantly exposed to pollution in
urban commuting [12]. Researchers have introduced active travel including walking and cycling as an alternative to traveling
with motorized vehicles [4]. Selecting active travel as a mode of transportation has benefits for the health of both individuals
and society by increasing physical activity and decreasing air pollution [15].
Previous research has studied various aspects of active travel including the impact of active travel on enhancing public
health, the impact of air pollution on cyclists, providing a routing model for cycling and walking, and examining the influence
of environmental parameters such as population density, land-use diversity and road network on active travel [18].
Rodriguez and Joo investigated the relationship between topographic and demographic parameters with non-motorized
and motorized transport. They found that the slope of trails has the opposite effect on non-motorized transportation choices,
while in areas with high population density, the tendency to use public transport is less [14]. Wallen et al. have shown that the
choice of travel mode is influenced by various factors such as travel cost, personal motivation and environmental parameters
such as the crowd and the congestion of streets and sidewalks. The results of this study indicated that in terms of duration of
travel, the use of motor transport is preferable to active travel. Whereas in the more crowded areas, there is a tendency to use
more active trips [20]. Nadi and Delavar [11] presented a personalized routing model with pairwise comparison and OWA
integration operators. The proposed model enables the adoption of different decision strategies. In this study, unlike previous
articles that only considered users' preferences and used a weighted linear combination of criteria to implement a balanced
strategy, this article also provided users with the possibility of adopting different decision strategies [11]. Taleai and Yameqani
[19] proposed a method for choosing the most appropriate and healthiest route using multi-criteria decision making and GIS to
encourage people to walk more. By comparing the healthiest proposed route and the shortest route between
origin and destination, they found that the healthiest route was longer [19].
Earlier studies used traditional methods such as gathering preference surveys and manual count for data collection. Although
these methods have some advantages, using them over a broad area like a city and a long period like a year is time-consuming,
costly and practically impossible [6],[7],[16]. The deployment of mobile phones equipped with global positioning technology
has introduced new ways of collecting detailed information on cyclists' trajectories. Citizen-generated cycling data have recently

1