Technology Record - Issue 22: Autumn 2021

AUTOMOT I V E , MOB I L I T Y & T RANS POR TAT I ON 117 compensate. In this way, the overall system effi- ciency is optimised and enhanced. Even operators of less flexible services can benefit from such real-time data. At a mini- mum, their schedules can be optimised to take account of probable delays based on historic performance, and slack in their schedules can- then be tactically deployed to increase inter- modal opportunity – for example near rental bike stands. Such real-time performance and state informa- tion can also be used to help car-sharing com- panies and micromobility providers figure out where to place their inventory of vehicles at dif- ferent times, and even influence demand to help achieve the best positioning. That might sound like a stretch, but dynamic pricing of journeys with better rates available for journeys that suit the operators overall plan better can help with overall system optimisation and is likely to be particularly effective in an under capacity sce- nario – rather than applying ‘first come first served’ to resource contention, you take into account the demand that provides the greatest benefit to the system by getting vehicles in the right place for the next journeys. There’s nothing here that is outside the scope of today’s analytical services and machine learning – provided you have the data. So to get started on the ITS journey, you need to invest in a city mobility data hub and persuade your operators to populate it with data. The next article in this series will explore the separation of duty between different software solutions in the following generation of ITS. John Stenlake is director of vehicle innovation & mobility for automotive, mobility & transportation industry at Microsoft.