Passenger counting

innovation photo
Passenger counting

Smart CCTV (n.d.). Welcome to Smart CCTV – Intelligent Video Systems [online]. Available at: [Accessed 1 February 2016]

eLinux (2016). Embedded Linux Wiki [online]. Avaliable at: [Accessed 1 February 2016]

Wu, F., Lim, H., Pereira, F., Zegras C. & Ben-Akiva, B. (2013). A user-centric mobility sensing system for transportation activity surveys. Paper presented at the 11th ACM Conference.

Public Transport Operators and Authorities need to consider the following issues when designing this innovative solutions:

  1. Identification of the most promising emerging solutions
  2. Adaptability to Public Transport environment
  3. Evaluation of the estimation range offered by these emerging solutions, precision and reliability over time
  4. Design how the data provided (estimated passengers number on the vehicles) can be used for stakeholders’ purposes
  • Testing of product on a limited number of vehicles, then this role product will be implemented out across network
  • Establish reliability and accuracy of product
  • Assess feedback and monitor
System that counts passengers in vehicles are fast developing: new solutions are emerging. Passengers can e.g. be counted by WiFi, Bluetooth (not only with infra-red or cameras): hardware solutions are moving from on-board unit to easy-to-install Raspberry Pi devices and Arduino open source platforms. Although emerging solutions provide only an estimation of the passengers on the bus, collected data allow operators to make decisions to meet their preferred needs and how to maximise use of resources to meet recognised demands.

Passenger counting in a crowded environment is not an easy task; therefore Public Transport stakeholders deploy a range of techniques to provide technology-based solutions. Traditional systems based on infrared and video cameras are expensive, required high installation and maintenance costs and they are not 100% reliable. Then alternative “estimation techniques” can now be considered. Generally, the system utilises wireless devices to collect data and uses a web framework to collate and analyse it. Applications with prediction algorithms and visualisations have been developed. This is made possible by leveraging distributed monitoring systems, like the connected mobile devices - smartphones, Wi-Fi networks, Bluetooth-enabled beacons, etc. (Aro, 2014). For example, Aro (2014) explains how smartphones, associated with a network, send signals to connect to an access point with a better signal strength. Then using 3G/4G Wi-Fi access points as sensors to sense the smartphones that are nearby, enables the collection of smartphone data or pings as real-time public data, then sending them to a cloud-based system. In the last years, low-cost computing technologies for building devices became common. This includes the Raspberry Pi and the Arduino open source platforms producing microcontroller’s hardware and computer applications (Christie, 2013).

General concept
Goal-oriented/efficient organization
  • Improving customer orientation
  • Performance orientation

Innovative technologies

It is important that any data driven service is built using reliable, consistent data.

How can users be reassured that their data will not be passed to 3rd parties?

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