Method — Robotaxi

Definition, scope boundary, and subject-specific classification model.

Definition

A robotaxi is an automated-driving application that provides an individual for-hire passenger transport function without requiring a human driver to perform the driving task within its applicable operating conditions.

Model Classification

The Robotaxi model is structured as a Conditional Classification Model.

The model represents Robotaxi through jointly relevant classification conditions rather than as a fixed set of physical components, a process sequence, a vehicle hierarchy, or a mobility-service hierarchy.

Scope Boundary

Included

Robotaxi as a semantic classification
Automated-driving condition
Individual for-hire passenger transport function
Joint classification basis
Distinction between semantic and legal classification
Distinction between Robotaxi and broader automated-vehicle classes
Distinction between Robotaxi and adjacent passenger-transport classes
Technical and operational context where relevant to classification

Excluded

Universal taxonomy of automated vehicles
Universal taxonomy of passenger transport
Complete SAE automation model
Complete operational design domain model
Jurisdiction-specific taxi regulation
Individual operators and fleets
Individual vehicle platforms
Sensor and computing architectures
Booking and dispatch systems
Fare and payment systems
Ownership structures
Market analysis and forecasts
Current website information architecture
Universal Conditional Classification Model for other semantic subjects

Classification Basis

Robotaxi classification is based on the conjunction of an automated-driving condition and an individual for-hire passenger transport function. Neither condition independently establishes the classification.

Automated-Driving Condition

The driving task is performed by an automated driving system without requiring a human driver to perform or resume that driving task within the applicable operating conditions.

The condition does not require unrestricted operation across all possible operating environments and therefore does not make a specific highest-level automation classification constitutive of Robotaxi.

Individual For-Hire Passenger Transport Function

The application provides an individual for-hire passenger transport function rather than solely private vehicle use, fixed-route passenger transport, general demand-responsive transit, or non-passenger transport.

The function does not require a particular booking mechanism, fare transaction, ownership structure, operator model, or jurisdiction-specific taxi classification.

Classification Constraints

The classification basis does not establish semantic identity with adjacent technical, operational, or legal classes.

Automated vehicle ≠ Robotaxi
Automated driving system ≠ Robotaxi
Autonomous shuttle ≠ Robotaxi
Demand-responsive transport ≠ Robotaxi
Ride-hailing ≠ Robotaxi
Legal taxi classification ≠ Robotaxi

Particular implementations may belong to or interact with one or more of these classes without those classes becoming equivalent to Robotaxi.

Jurisdictional Context

Legal classifications of automated passenger transport may differ between jurisdictions. A particular implementation may be regulated as a taxi, private-hire vehicle, automated transport service, or another category.

Jurisdiction-specific classification provides regulatory context but does not independently determine the jurisdiction-neutral semantic classification documented by this Core.

Vehicle and Service Reference

The term Robotaxi may occur in reference to vehicles and to services that deploy such vehicles. The Conditional Classification Model does not treat a Robotaxi vehicle and a Robotaxi service as identical entities and does not require a complete ontology of their relationship.

Transferability

The Conditional Classification Model documented here is subject-specific to Robotaxi.

Its use does not establish the same classification structure, number of conditions, or representational form for other automated-mobility concepts or other Semantic Cores.