Mathematical optimisation of urban parking enforcement scheduling

Turning big data from urban mobility into balanced work shifts and predictive territorial clustering through Decision Science.

Markets

Manufacturing

Solutions

The challenge

Managing paid on-street parking enforcement across a large urban area such as Bologna is a highly complex logistical and organisational challenge. On-the-ground checks, carried out by traffic control teams, must comprehensively cover parking meters and bays, based on rigid planning.

Relying on empirical or static zoning creates significant structural inefficiencies, leaving some strategic areas under-resourced and others overloaded, which undermines service effectiveness and territorial control. Adding to this complexity is the need to plan the workforce while respecting binding operational constraints, national contracts and union agreements, all while ensuring a fair rotation of shifts.

The challenge was to move beyond manual planning and turn historical data flows into balanced patrol zones and optimised, practical daily work schedules.

How we create value

Optit responded by introducing an integrated approach based on Decision Science, structured across four sequential optimisation phases.

The algorithmic engine processes historical parking and inspection data to perform territorial clustering, dividing the city into compact, balanced macro-zones matched to shift-length workloads. The model then automates team creation, cross-referencing staff availability and calculating monthly schedules in full compliance with union and contractual rules. Finally, shift scheduling and rostering algorithms assign patrol areas to available staff each day, maximising the effectiveness of urban coverage and ensuring the widest possible rotation of zones.

Management therefore has access to an interactive SaaS platform to simulate and validate stable operational scenarios.

Impact

Optimising urban parking enforcement delivered:

Automated planning of monthly and daily team schedules.
Fair staff rotation across areas, in line with contractual constraints.
Balanced workloads, reducing overloaded or inefficient shifts.
Maximum monitoring effectiveness across the urban area.