Road traffic particularly affects the amount of CO2 released into the air.
This is caused by the significant number of drivers, who generally prefer to take their car to avoid the problems of saturation, breakdowns, congestion and prices posed by public transport.
Quite logically, public transport helps to reduce individuals’ CO2 emissions by bringing several users together into the same means of travel.
There are many actions that can be taken to encourage travellers to use various means of public transport. However, this is not enough: public transport offerings that offer users’ the comfort that they expect by using the data generated from the passenger flows now need to be developed.
Thus, data on train passage times, crowds measured using sensors (travel cards validated in the station for instance), user surveys, and even crowdsourcing, can help improve traffic flow and quality of service.
LINCOLN, ALTEN Group’s data specialist subsidiary, is supporting a global urban travel operator on a project to improve passenger comfort by collecting millions of pieces of data.
LINCOLN’s data experts set up and industrialise artificial intelligence algorithms that can integrate this multitude of data in real time.
This work contributes to:
- Improving information on travel times, incident reporting, train arrival times
- Encouraging commuters to change their travel behaviour,
- Controlling the influx of travellers on trains and on platforms, especially during the COVID period.