Where CANTrak
is going
The roadmap is organized by phase. Foundation and pattern intelligence features are in active development. Topology mapping and field workflow features are planned for future phases.
Core capture & analysis
Live CAN capture engine
In ProgressReal-time message capture via python-can with configurable interface and bitrate support.
Command Verification (Mode 01)
In ProgressTrigger-based capture window with pre/post payload delta reporting.
Sleep & Wake Analysis (Mode 02)
In ProgressPost-key-off monitoring with configurable threshold and parasitic drain candidate flagging.
Module Dropout Detection (Mode 03)
In ProgressPer-ID interval tracking with timestamped dropout event logging.
Spacebar Clutch trigger system
In ProgressKeyboard-based capture window with millisecond-precision timestamps.
CSV & terminal output
In ProgressStructured log export and formatted terminal output for all three modes.
Payload pattern matching & analysis
Payload pattern library
In ProgressUser-defined pattern definitions that map known payload states to human-readable labels — without requiring manufacturer databases.
Allows technicians to build a local reference of known-good and known-bad payload states for specific vehicles. Patterns are stored as YAML and matched against live capture data.
Cross-session pattern comparison
In ProgressCompare capture sessions from the same vehicle over time to identify drift, regression, or intermittent faults.
Useful for tracking down faults that only appear under specific conditions. Load two sessions and CANTrak highlights IDs where payload behavior has changed.
Sequence analysis
PlannedDetect and record the order in which arbitration IDs change state during an event — not just which IDs changed, but when.
Sequence data reveals whether modules are responding in the correct order. A module that responds out of sequence may indicate a communication delay or a fault in the upstream module.
Pattern export & sharing
PlannedExport pattern libraries as portable files that can be shared between technicians or imported into other CANTrak installations.
Topology mapping & visualization
Arbitration ID inventory
PlannedAutomatically build a complete inventory of all IDs present on the network, with transmission intervals and DLC values.
The inventory becomes the baseline for dropout detection and topology mapping. Run once per vehicle to establish the expected network profile.
Network topology map
PlannedVisual representation of the CAN network showing active nodes, message groups, and communication relationships.
Not a manufacturer wiring diagram — a live-derived map based on observed traffic patterns. Shows which IDs cluster together and which appear to be responses to others.
Module range cross-reference
ResearchOptional reference layer that maps arbitration ID ranges to likely module types based on common industry conventions.
Many manufacturers follow similar ID range conventions (e.g. 0x700–0x7FF for diagnostic responses). This layer adds context without requiring proprietary data.
Multi-bus support
ResearchSimultaneous capture from multiple CAN buses (HS-CAN, MS-CAN, LIN gateway) with per-bus analysis.
Usability & field integration
Session management
PlannedNamed sessions with vehicle metadata, technician notes, and searchable history.
Report generation
PlannedFormatted diagnostic reports suitable for repair orders and customer documentation.
GUI interface
ResearchOptional graphical interface for technicians who prefer a visual workflow over the CLI.
The CLI will always be the primary interface. A GUI is a secondary goal — it should not compromise the precision or speed of the core capture workflow.
Mobile / tablet support
ResearchOptimized interface for use on a tablet in the shop, connected to a Raspberry Pi or similar field computer.
This roadmap reflects the current development direction. Priorities shift based on real diagnostic work — if a feature proves more useful in the field than expected, it moves up. If something turns out to be less valuable than anticipated, it moves down or gets cut.
The goal is a tool that makes technicians faster and more accurate — not a tool that checks every feature box.