Parkopedia launches AI-Driven API to tackle EV charging anxiety

Parkopedia, a leading provider of connected-car services, has launched an advanced EV Reliability and Utilisation API.

The new dataset is designed to help automotive manufacturers (OEMs) eliminate “charging anxiety” – the modern driver’s fear of arriving at a broken or heavily congested public charging station.

As electric vehicle ranges improve, industry data shows that the barrier to mass adoption has shifted from battery range to infrastructure dependability.

Recent research highlights that up to 43% of public chargers are effectively unavailable at any given time, driven by a 25% equipment failure rate and severe peak-time congestion.

Parkopedia’s enhanced API integrates directly into vehicle navigation systems to give drivers real-time transparency through three core features:

• A-to-F Reliability Scoring: Dynamic grades based on historical success rates, allowing navigation systems to steer drivers away from faulty units.

• Predictive Utilisation Histograms: Time-based occupancy data that helps drivers bypass peak-time congestion by identifying the best hours to charge.

• Pricing Transparency: Clear, upfront displays of the total session cost, including energy prices and any potential idle or overstay fees.

The system builds upon Parkopedia’s existing database of locations, connector types, and charging speeds to create a more dependable ecosystem for mainstream drivers.

“For OEMs, the charging experience is now a core component of brand loyalty,” said Duncan Licence, Head of Automotive & Data at Arrive.

“As we move from early adopters to the early and late majority, drivers expect the same ‘plug-and-play’ reliability they had with ICE vehicles.

“Our unique data allows automakers to act as a trusted companion, guiding drivers away from broken or congested infrastructure and directly to a successful charge.”