In the context of constantly evolving urban development, CITiO is committed to remaining at the cutting edge of technological innovation. Unified occupancy, our latest development, enables us to improve public transport network monitoring efficiency. This article looks at the techniques we use to improve reliability and enrich mobility data.
The challenges of urban mobility and unified occupancy
At the heart of urban mobility is the completeness, accuracy and reliability of ridership data. Inaccurate and incomplete passenger counting data can distort the understanding and estimates of passenger flows. CITiO’s unified occupancy addresses these problems by making counting data more reliable and extrapolating it through an iterative and innovative process.
The unified occupancy algorithm is used to determine the total number of passengers in each vehicle. Currently, it is possible to determine occupancy in vehicles equipped with counting sensors, but this does not cover the entire vehicle fleet. Moreover, if only ticketing data is used, passengers without a valid ticket, in particular fare evaders, are excluded, so the total occupancy of the network is therefore not represented. This information is crucial for adjusting transport provision, for example, by adding extra buses at peak times.
Previously, this analysis was done at network-level, taking into account all passengers in all vehicles, but unified occupancy offers a more detailed study of the state of the network in terms of ridership. Unlike competitors’ methods that take into account global occupancy at the network level, unified occupancy now makes it possible to accurately count the number of passengers on board each vehicle in the fleet. This granularity gives a more detailed picture of ridership, enabling a detailed analysis of journeys by time period and geographical zone. Our approach is based on the modelling of fraud rates, an approach that, to our knowledge, the team at CITiO is the first to adopt.
Unification and fraud modelling
The fraud rate is valuable data for the authorities that organise mobility (AOM) and operators, but it is difficult to obtain for reasons related to the reliability of measurement methods. There are unexplained discrepancies between what inspectors measure on-the-ground and fraud investigations (*).
However, by integrating ticketing and counting data, we have been able to model fraud not only at station level, but also across the whole network, providing an accurate assessment of real occupancy. The fraud rate obtained in this way is then applied to ticketing data for routes that do not have counting systems, providing a more complete picture of network ridership. Using this approach, we have been able to reconstruct non-observed occupancy for each station on each route.
The impacts of unified occupancy
The unified occupancy process produces exhaustive and accurate information on the total occupancy of transport networks, by integrating both ticketing data and counting measures.
The adoption of unified occupancy has led to a noticeable improvement in data accuracy. Our metrics tracking tool plays a key role in analysing these data, enabling accuracy and continuous monitoring of performance. It provides exhaustive knowledge of ridership at any point on the network at any time of day. This not only enables more efficient transport network management but also a better passenger experience.
The future of mobility with CITiO
Unified occupancy demonstrates CITiO’s commitment to innovating for more efficient and intelligent urban mobility. By combining technical expertise and professional knowledge, we are paving the way for reliable and optimised public transport solutions.
(*) source: Egu, O., & Bonnel, P. (2020). Can we estimate fare evasion accurately without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data. Public Transport, 12(1), 1-26.
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Audrey Fleurot