Quantifying the sensing power of vehicle fleets

Area of Science:

• Urban informatics
• Network science
• Transportation engineering

Background:

• Sensors offer detailed urban environmental data for city health monitoring.
• Drive-by sensing on vehicles enables cost-effective, wide-area data collection.
• The required number of vehicles for adequate city coverage remains unaddressed.

Purpose of the Study:

• To determine the number of vehicles needed for effective city-wide sensing.
• To analyze the sensing capacity of a taxi fleet for urban monitoring.

Main Methods:

• Analytical modeling using a ball-in-bin model.
• Simulation of taxi movements and their spatial coverage.
• Validation against taxi movement data from nine major cities.

Main Results:

• A small taxi fleet can sense a significant fraction of a city's street network daily.
• The findings are universal and applicable across different urban environments.
• Taxi movement patterns exhibit unique spreading properties, with stationary densities following Zipf's law.

Conclusions:

• Drive-by sensing with taxis is a highly efficient method for urban monitoring.
• The study provides crucial insights for urban planners and smart city initiatives.
• Minimal vehicle numbers are sufficient for comprehensive urban data acquisition.