Extended Abstract
Introduction:
Cities are experiencing a surge in non-motorized transportation like bicycles and scooters. This trend offers environmental advantages that are crucial for sustainable urban development. Bicycles, in particular, are attracting new riders due to their sustainability, affordability, and positive health impacts. However, encouraging cycling heavily relies on suitable cycling infrastructure. Understanding why people choose specific routes and how the built environment influences these choices is key to advancing urban planning. Advancements in technologies like volunteered geographic information systems (GIS) and GPS have made it possible to continuously track individuals' locations and share them openly. These sequential location data points, over time, form trajectories, which can be analyzed to reveal patterns and assess the role of the urban environment in shaping cycling behavior.
Extensive research has explored the role of the urban environment in influencing pedestrian and cycling route choices, informing strategies for promoting active travel in cities. However, these studies often overlook the impact of user demographics and trip purposes. This article presents a novel approach by investigating the individual and combined effects of intended uses on cyclists' route selection. Our aim is to identify which trip purposes contribute to longer cycling distances.
Materials and Methods:
Sari, a densely populated city in Mazandaran province, was chosen as the study area. Mazandaran's central location and attractive natural features, including good weather, religious sites, historical landmarks, and natural sights, contribute to Sari's strong data availability. We leveraged WikiLock, an open-source platform where users can record their movement paths with their mobile phones. This platform offers valuable data with 15-second time resolution, capturing each individual's date, time, and location. Additionally, OpenStreetMaps (OSM) data provided information about existing users within Sari.
Our analysis delves deeper into users' movement paths by identifying their stopping points along the route. We achieve this by examining consecutive recorded positions with a specific time interval. If two consecutive positions remain the same, indicating a lack of movement for at least 90 seconds, we classify this as a "stop point." These stops likely signify the user pausing their journey to visit a point of interest, potentially revealing their preferred locations within the city. Furthermore, we don't simply identify stopping points; we also analyze the users associated with these stops. This allows us to understand if specific user profiles are more likely to deviate from a direct route. To quantify the extent of route deviations, we employ the Dijkstra algorithm. This algorithm calculates the shortest possible path between a user's starting and ending points. By comparing this shortest path with the user's actual route, we can calculate the percentage deviation. This deviation percentage helps us understand the reasons behind the user's extended journey. By analyzing patterns in deviations and their association with stopping points, we can gain valuable insights into the factors that influence cyclists' route choices within the urban environment.
Results and Discussion:
To analyze the types of locations influencing cyclists' route choices, we defined a 300-meter radius around each identified stop point. This allowed us to examine existing land uses within this area and assess their potential role in causing cyclists to pause their journeys. Our findings revealed that the service and welfare category had the most significant individual impact on user stops. This category encompasses like restaurants, cafes, cinemas, and other amenities. Among these, cafes were identified as the most frequent reason for cyclists to deviate from their routes. These results suggest that cyclists may be more likely to make unplanned stops for refreshment breaks compared to other service and welfare options. Further analysis explored the impact of combined land uses. Here, the service and welfare category maintained its dominance. Cyclists with combined trip purposes that included service and welfare needs exhibited the highest percentage deviation from the shortest path. This suggests that when cyclists have a combination of errands or destinations within the service and welfare category, they are more likely to deviate from the most direct route. Interestingly, our analysis also revealed a significant influence of the Tejen River. This natural feature affected 47% of the data points, suggesting that cyclists frequently adjust their routes in response to the Tejen River's presence. This deviation could be due to factors like using bridges or designated cycling paths along the river or avoiding specific areas due to safety concerns or terrain.
Conclusion:
This study delves into the connection between cycling routes and land uses within Sari city. The goal is to equip urban planners with valuable insights for designing more efficient and cyclist-friendly infrastructure. The research reveals that cyclists often opt for longer routes to access areas with commercial, service, and amenity destinations. Interestingly, educational areas saw the least cycling activity. Based on these findings, urban planners should prioritize creating dedicated cycling paths near service and amenity locations. Additionally, incorporating green spaces and recreational facilities along these paths could further incentivize cycling within the city.