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Human Mobility Data Use Case Collection

Use cases that human mobility data is needed for in the urban setting, as described in this blog article. This is intended as a continuously growing collection.

Urban and Traffic Planning

Topic Use Case Example
control of success Compare statistics before and after actions have been taken (e.g., new road layout or bike lane), to validate the success of the action (e.g., lower speed, less traffic, more bicycles, etc.)
traffic simulation Traffic model to simulate the influence of different scenarios on traffic situations. E.g., the opening of a new shopping mall or adding a new bus line.
  • Four-step traffic demand model that uses origin-destination matrices (e.g., Visum PTV)
  • MatSim: agent-based model that uses day plans
  • BikeSim: bike simulation that uses cyclist trajectories
  • SUMO: "Simulation of Urban MObility" (SUMO) is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks.
bike infrastructure Optimize bike infrastructure: detect shortcomings through analysis of street attributes based on GPS trajectories and sensor data (e.g., bumpiness, high chance of accidents, low bike speed).
bike infrastructure Determine high-demand origin-destination connections to optimize the bike infrastructure for those routes. Propensity to Cycle Tool uses origin-destination matrices to visualize cycling demand and thereby provide a bike infrastructure planning tool.
bike infrastructure Determine the count of bikes for reports, monitoring, funding, and as a decision basis.
bike infrastructure Identify locations to place bike counters for a representative sample of bicycle ridership within a city. Article how to aggregate GPS trajectories to average hourly activity count for street-segments to determine traffic volumes and thereby suitable bike counter locations.
public transport Demand-driven short- and long-term public transport offer. Based on historic and real-time data, public transport can be optimized to fit daily routines, to account for special events (e.g., soccer games), or to satisfy real-time demands. Also, routes of public transport lines can be optimized to reduce transfers.
shared mobility Integrate new on-demand and shared-mobility offers, such as bike, e-scooter, car-sharing and offers into the cityscape and public transport network: Provision of demand-based positioning of docking stations and parking spots.
shared mobility Redistribution of shared vehicles (e-scooter & bike-sharing) and positioning of ride-hailing (e.g., Uber) and ride-sharing (e.g., Moia) vehicles based on historic demands.
shared mobility City administrations use reports on usage behavior and analysis tools to evaluate the use of micro-mobility in their cities. The mobility data specification has been established as a standard that more and more mobility service providers start to use and offer their data accordingly. The specification goes beyond human mobility data (e.g., charging status of vehicles or definition of prohibited parking zones, see this article and this MDS use case gallery) but also includes start and end locations of rentals. Service providers that combine data from multiple providers and offer analysis platforms to cities. E.g., Vianova Remix, Populus.
electric vehicle infrastructure City administrations can use mobility data of combustion engine cars to assess where charging infrastructure for electric vehicles may be needed. Operators of buildings and districts need it to plan local charging infrastructure. Operators of electric power systems (mostly distribution system operators) can use mobility data to assess the demand for e-mobility and plan their grids to handle the future demands. Electric Vehicle Infrastructure Simulator (ELVIS), Localiser: commercial software

Traffic Management and Routing

Topic Use Case Example
bike routing Optimize bicycle routing based on historic cyclist trajectories, e.g., speed and preferred routes. Cyclers is an example of a bicycle routing app that claims to use such data.
public transport (passenger load forecast) Historic passenger load data is used by public transport companies and routing applications to estimate future passenger load and display this information alongside routing suggestions so that passengers can choose routes where busses and subways aren't too crowded. Examples of public transport companies providing passenger load forecasts: Deutsche Bahn, BVG, RMV
car routing (traffic jams) Car routing that makes use of traffic jam information.
car parking Provide information on free parking spots to drivers based on data provided by sensors in smartphones (placed as dashcams on the windshield) and cars. Example companies: INRIX,Bosch, Bliq
smart traffic management system Smart traffic management systems adjust traffic lights and manage traffic flows according to real-time traffic data (e.g., acquired through sensors) to optimize traffic. studies by, e.g., Ritzwan et al., 2017, Iqbal et al., 2018 or Saikar et al. 2017.
electric car charging recommendation Intelligent planning of electric car charging based on historic data. studies by, e.g., Wang et al., 2020 or Zhang et al., 2021
matching for ridesharing Automated matching of drivers and passengers for carpooling based on historic mobility patterns. studies by, e.g., Liu et al., 2013, Li et al., 2015 or Roor et al., 2018

Other Use Cases

Topic Use Case Example
Epidemic modeling Analysis and modeling of human mobility to evaluate spreading of diseases (e.g., COVID-19) monitoring of mobility behavior during COVID-19 pandemic: Mobility Monitor RKI, Google mobility reports, Article
Disaster Management Use mobility data for analysis and prediction of mobility in crisis situations.
Emission estimation Calculate emissions produced by traffic sector
Location Analytics Identifying locations for business branches that attract the largest number of visitors.