GPS Tracking Applications
Tracking applications allow users to share information generated by GPS in their mobile devices about the paths they use to travel. These data are an excellent source of planning information because they show paths really taken by users and can provide real time information about speeds or performance conditions. Many tracking applications allow users to add information to maps such as problems.
Waze is the most familiar tracking application. It tracks users to identify real time roadway traffic conditions and allows users to enter data (e.g., accident locations). Waze is combined with a travel planner that provides users on fastest routes given real time traffic conditions.
Tracking applications have also been developed for sustainable transport modes: public transport, biking and walking. Fitness applications are an especially good source of information on biking and walking.
Cities are increasingly using (buying) data from tracking applications developed by private companies. For example, many cities are working with Waze to obtain traffic data and with fitness application developers like Strada to obtain bicycling data. In some cases cities have developed partnership programs where they provide certain data to the developers and the developers provide data to the city in return. See The Social Network That Helps Planners Understand Pedestrians and Cyclists from CityLab (Nov 2017) for more.
Agencies planning to use tracking data need to consider:
- Data privacy?
- Should agencies buy data from commercial app developers or develop their own apps?
- Are application users typical (i.e. not competitive bike riders)?
- Should cities plan for typical app users?
The next sections outline tracking data applications for sustainable transport modes.
Examples: GPS Tracking Apps
Meine Radspur is an early example of using GPS tracking for bicycle planning.
Bicycle Tracking Apps
Bicycle tracking applications are one of the most popular types of GPS tracking applications. In addition to many privately developed fitness tracking applications many cities and researchers have created these applications individually. Given the large number of applications we’ve created a special page with example bicycle tracking data applications and references:
Public Transport Tracking Apps
Public transport is another field where many GPS tracking applications have been developed. In this case there seem to be more private-sector developed applications than in the case of bicycle GPS tracking applications.
In 2017 London did an experiment to anonymously track passengers to learn about travel patterns (see Rachel Dovey in Next City: What a London transit agency learned from tracking riders for a month (Feb 2017).
Here’s a link to our page with example public transport GPS tracking applications and references:
Pedestrian Tracking Apps
Interestingly, aside from pedestrian tracking that’s part of fitness applications there do not seem to be very many applications directly created to provide planning data from pedestrian trips. Probably I’ve missed some, but it could be a good market to explore.
Open Source Vehicle Tracking
Mapzen has developed the Open Traffic platform in conjunction with the World Bank. The platform uses anonymous GPS location data to develop roadway speed information. It’s available on GitHub. The Mapzen blog post Open Traffic platform released provides detailed information and references.
References: GPS Tracking Apps
- Trace Project – The EU-supported TRACE project (2015-2018) will examine geo-based crowdsourcing applications for biking and walking.
- City planners tap into wealth of cycling data from Strava tracking app – Peter Walker, The Guardian Bike Blog, 9 May 2016.
Blog Posts: GPS Tracking Apps
Three interesting articles about Crowdsourcing that appeared in late 2019:2020 and beyond: 11 predictions at the intersection of technology and citizen engagement in the DemocracySpot blog by Tiago Peixoto and Tom Steinberg. Lots of food for thought.Why Crowdsourcing Often Leads to Bad Ideas by Oguz A. Acar in the Harvard Business Review, outlining some of […]
Alan Bell has used machine learning to develop a program that analyses data from traffic cameras to identify blocked bus and bike lanes. He analysed a section of St. Nicholas Avenue in Manhattan and found that the bike lane was blocked 55% of the time and the bus stop was blocked 57% of the time […]
The Transit Alliance Miami has created a simple graphic display illustrating the time between Miami Metrorail trains (frequency) at the Government Center station. They have taken Metrorail data and displayed it in an easy to understand format. It is an excellent example of how city residents can use open data to analyse and publicise the […]
Over the holidays I had a chance to update crowdsourced-transport.com with new information. Here are the highlights: Crowdsourced Public Transport page – added: WikiRoutes – site where users can add information about public transport routes and suggest improvements (PT Mapping). Digital Matatus – an application for using smartphones to map public transport routes (PT Mapping). […]