Route optimization and navigation

1. ZTL and Low Emission Zone (LEZ) Permit Customization

Allow users to specify municipalities or urban areas where they hold active ZTL (Restricted Traffic Zone) or environmental access permits. Currently, the routing algorithm often defaults to avoiding these zones altogether or fails to recognize specific local exemptions. Enabling users to input their active permit zones would prevent unnecessary detours and significantly improve urban routing accuracy.

2. Battery Thermal Preconditioning Integration

Implement support or vehicle system integration to trigger automatic battery preconditioning when navigating toward designated fast-charging stations. Enabling optimal battery temperature prior to arrival is critical for maximizing charging speeds and minimizing stop durations.

3. Enhanced Turn-by-Turn Navigation Engine

Upgrade the active navigation interface and dynamic rerouting logic to match the responsiveness and fluid user experience of mainstream navigation apps. The current engine occasionally suggests inefficient secondary routes or struggles with rapid recalculations when an exit is missed.

4. Native State-of-Charge (SoC) Telemetry Integration

Expand direct, hardware-free vehicle API integrations for live SoC and consumption tracking. Reducing the dependency on third-party OBD dongles or complex manual setups would make real-time telemetry accessible to a broader user base.

5. Community-Driven Charger Reliability Feedback

Incorporate real-time user check-ins and feedback directly into charger details (similar to PlugShare integration). While live availability counts are useful, community reports regarding damaged hardware, physical access issues, or reduced output speeds provide essential context before arriving at a station.

6. Simplified Interface ("Standard Mode")

Introduce a toggleable, streamlined UI mode tailored for casual users. While deep parameter customization (such as reference consumption, degradation, and wind speeds) is valuable for power users, an automated, friction-free mode would lower the learning curve for everyday EV drivers.