Boots on the ground.
That used to be the measure of parking policy. The more people you had patrolling the streets, the better you could encourage compliance and the better you could ensure the smooth flow of traffic – all to benefit economic activity, cleaner air, and societal wellbeing.
While the aims remain the same, the old rules no longer apply. At least they shouldn’t. The inefficiencies of simply increasing the volume of parking enforcement staff is being exposed by a more intelligent, data-driven, end-to-end approach to kerbside management. At Conduent Transportation we call this data led deployment.
In practice, this means optimising shift patterns and ensuring beats are neither too large nor too small, but just the right size to be effective, which is the Goldilocks test of parking management. It also means creating predictive models that identify the optimum routes to patrol hour-by-hour, day-by-day.
Conduent Transportation is speaking with a number of existing clients on how parking management will be affected by the increase in controlled parking zones. Ordinarily, a typical parking operator would simply put more feet on the ground. We’ve been looking, instead, at more intelligent deployment. One technology we are pilot-testing is Scanbike, a three-wheeled moped with in-built camera that patrols the streets collecting registration plates, comparing the information collected against both parking and non-parking databases. In this context, it will be data we hold on transactions for parking payments made via pay-and-display machines and through cashless parking apps for paid sessions and permits.
Scanbike data has two uses – one immediate and tactical, the other long-term and strategic. In the immediate term, the data collected guides on-the-day teams toward live cases of potential non-compliance. In the longer term, the profiling of parking activity informs resource allocation optimisation decisions, enabling local authorities to gain a more comprehensive service without a proportional increase in resources. In other words, the information collected can help teams locate likely hot spots and move them away from areas of relative inactivity.
In addition, data collected is used to understand the types of vehicles in specific areas, by fuel type, engine size and emissions. This information will enable clients to use data to inform future policy decisions and model the impact on air quality and revenue required to maintain the service.
There is a real incentive now to transform parking services to gain greater efficiency. It’s time to stop dusting off the old specifications and hoping the solutions of the past remain relevant in the future. Unless parking is reimagined and an end-to-end approach is taken, there is a danger that the solutions delivered in five, six-, or seven-years’ time may be exactly what was asked for but completely outdated and inefficient.
An end-to-end approach is a service that blends, people, technology, and data – the best way to ‘future-proof’ results. It is, after all, outcomes not outputs that will drive greater efficiency and optimise kerbside management.
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