Work That Moves
the Ranks.

TRSA Project

CALTA — Mitchells Plain Local Route

CALTA was Rutco's first TRSA deployment and the project everything since has been built on. Beginning in April 2024, it was where the model was proven and stress-tested with the support of the association, TRSA and City of Cape Town.

The starting problem was visibility. In a predominantly cash operation, no one held a reliable picture of who was travelling, when, and along which corridors which made planning or fare reform guesswork.

Rutco onboarded all 31 vehicles in a single week, fitting each with AI-powered smart camera to count passengers and capture route and fare activity in real time. Within the first operating cycle the association recorded a 30% increase in declared revenue replacing manual, self-reported counts and streamlining the driver end of day cash up process for the associations operations team.

But CALTA's biggest contribution was to Rutco itself. As our first public-private partnership it capacitated our teams to receive actionable feedback which has since driven a wave of changes to the hardware, the platform and data reporting process. Every association that followed benefited from a system hardened on CALTA's routes and feedback on what the operator wants to see, and how they want to see it.

The deployment sits inside a broader collaboration with TRSA, the City of Cape Town and the Transport Consortium, feeding the growth and adoption toward the broader Mitchells Plain Automated Fare Collection (AFC) programme with SAPay. The project remains ongoing — Rutco's founding case, and its longest-running success story.

TRSA Project

Gamalakhe — Margate Main & Local Routes

Gamalakhe brought scale. Spanning both long-haul and main routes to Margate and dense local services, the association operated 185 vehicles with little consolidated data to support planning or reform.

Rutco onboarded the entire fleet with our propriety AI passenger-counting cameras, building a continuous picture of commuter trends across every route the association runs. That evidence base delivered a 22% increase in declared revenue and gave the association, TRSA and the Transport Consortium a factual foundation for route modelling and fleet optimisation.

Crucially, the work was pointed at a clear endpoint: formalisation. The passenger and route datasets are being used to underpin the feasibility of establishing a formal transport operating entity, moving Gamalakhe from an informal, cash-based association toward a structured operating entity. The Rutco scope of the project is now complete, with the data assets informing the formalisation process.

Key Findings from the Transport Consortium

• The data held up as a planning input. The central result of the engagement was validation: Rutco's commuter data was accepted as a reliable, defensible baseline from which routes and schedules could be designed and not just described.
• Demand splits almost evenly between local movements within Gamalakhe and long-distance travel to Port Shepstone and Margate, indicating that the two categories benefit from separate scheduling approaches.
• Two clear daily peaks define the fleet requirement, with significant spare capacity between them — the key lever for better vehicle utilisation.
• Ten scheduled routes were designed covering four local loops and six long-distance services with stops clustered so that average walking distance for commuters falls within international public transport norms.
• Structured routing reduced modelled kilometres per vehicle, by removing unnecessary detours and improving directional efficiency across the network there is a measured reduction in operating kilometres.
• Final Recommendation from TCC: pilot on a small number of routes before full rollout, monitoring passenger response as commuters adapt to fixed schedules and designated stops.

TRSA Project

7th Avenue — Local Route, Mitchells Plain

The 7th Avenue association already ran an established transport operating entity, but its local Mitchells Plain route had evolved through habit rather than evidence. The question was simple: are we running the right service, in the right places, at the right times?

Rutco fitted all 54 vehicles with onboard passenger-counting cameras and captured real commuter movement across the route. Together with TRSA, the City of Cape Town, and The Transport Consortium, the analysis translated raw demand data into two concrete outputs: a set of route change recommendations, and a shift toward scheduled services in place of purely demand-driven departures.

For an operating entity, that is the difference between anecdote and operations. The 7th Avenue engagement is closed, having delivered a data-backed blueprint the association can run against. This provided a compact example of how camera-driven demand data reshapes an existing service rather than just measuring it.

TRSA Project

Inanda Taxi Association

Inanda is one of Rutco's largest single deployments and most complex setups to date. Inanda Taxi Association is made up of a fleet of 339 vehicles serving a vast geography within the broader Durban catchment that needed sharper data to plan and reform its current operations.

Rutco onboarded the full fleet to model commuter trends, optimise fleet allocation and support the associations existing operations. But Inanda also served as a proving ground for the next step in Rutco's hardware. The association piloted a new front-facing camera that counts passengers in the front seat of the minibus — historically the hardest position to capture. Closing that gap gives a complete, per-vehicle occupancy count, materially improving the accuracy of both demand data and any future fare reconciliation.

That accuracy matters because Inanda is heading toward electronic fare collection. The route and passenger datasets Rutco is building now form the evidence base for the next phase of the project with full-vehicle counting already validated in the field. The engagement is ongoing.

Key Findings — Phase 1

• A baseline is established. Phase 1 confirmed definitive passenger trends across the association's operating area and produced a defensible reference point for scenario modelling.
• Emtshebeni is the dominant origin hub, with Bridge City and the Durban-bound corridors acting as primary destinations — passenger flows follow definable, repeatable corridors rather than dispersing randomly.
• A clear local versus long-distance split emerged, with seventeen provisional routes drafted — four local loops and thirteen longer services toward Verulam, Pinetown, Durban and surrounding nodes.
• Two daily peaks, with the active fleet requirement varying materially by time of day — pointing to real scope for time-based scheduling.
• Next steps: formalise the provisional routes, run scenarios against the baseline, and layer in fare schedules and cost modelling.

TRSA Project

TopStar Taxi Association

TopStar is the largest fleet in Rutco's portfolio: 402 vehicles across the Mbombela region of Mpumalanga. At that scale, manual data collection is impossible, which is precisely where a camera-based, automated approach earns its place.

Working with TRSA and the association leadership, Rutco onboarded the association's fleet to capture commuter trends continuously and at volume. The data feeds route modelling and fleet optimisation, giving the association its first consolidated view of demand across a large and geographically spread operation.

The objective is formalisation. TopStar's data programme is designed to support the establishment of a formal transport operating entity, bringing structure, accountability and planning capability to an association that has, until now, operated informally. As the largest deployment in the programme, TopStar is a live demonstration that Rutco's model holds up at real fleet scale.

TRSA Project

CODETA — Khayelitsha / Killarney

As the Western Cape's Automated Fare Collection programme expands, each participating association needs a clean data foundation before fare technology goes live. For the CODETA-affiliated Khayelitsha / Killarney association, Rutco built that foundation fast.

All 199 vehicles were onboarded in two weeks, each fitted with AI-enabled smart cameras capturing route, fare and passenger data in real time to be used to measure AFC adoption and provide a validation layer for implementation. Delivered with TRSA, CODETA, the City of Cape Town and SAPay, the deployment gives every stakeholder a shared, accurate view of how the association actually moves people and how transactions are taking place in the field.

That data does double duty: it drives immediate service optimisation and route remodelling, while providing the operator and broader project stakeholder with key commuter insights for the broader adoption of the newly implemented Automated Fare Collection (AFC) system provided by SAPay as part of the broader Western Cape AFC roll-out. The engagement is ongoing, with the association now data-ready for the transition to cashless fares.

TRSA Project

CODETA — Mfuleni / Killarney

The Mfuleni / Killarney association joined the Western Cape AFC roll-out as a smaller but strategically important node in the CODETA network. Speed and consistency mattered, the association needed to reach the same data standard as its larger counterparts to move in step with the programme.

Rutco onboarded all 72 vehicles in two weeks, fitting each with passenger-counting cameras that capture route, fare and demand data in real time. Delivered alongside TRSA, CODETA, the City of Cape Town and SAPay, the deployment gives the association and its partners an accurate, shared picture of commuter movement while providing the operator with a validation tool to support the migration to a cashless environment. The engagement is ongoing.

TRSA Project

Century City Taxi Association

The Century City association forms part of Rutco's broader Mitchells plain network deployments in the Western Cape AFC programme. Like its counterparts, it needed a fast, reliable data foundation to support the shift to electronic fare collection.

Rutco onboarded the full 72-vehicle fleet in two weeks, capturing route, fare and passenger data in real time through onboard AI smart cameras. Delivered with TRSA, CODETA, the City of Cape Town and SAPay, the deployment turns an informal, cash-based operation into a measurable one, giving planners and the association a common, accurate view of demand.

That evidence base drives service optimisation and route remodelling, and readies the association for Automated Fare Collection implementation with SAPay as part of the broader Western Cape roll-out. The engagement is ongoing.