Digital Transformation of Used‑Car Buying: Integrated Data, AI Valuation, and VR Visualization

The core issue in China's used‑car market is the lack of transparent vehicle condition information, leading to low trust and inefficient transactions. Existing systems provide physical data integration but still require users to manually interpret collision, maintenance, and battery reports.

To address this, the platform builds a "car‑history archive" with high‑coverage accident (98%) and maintenance (85%) records, and adds offline inspection data from the "Tiantian Pai" service.

By leveraging machine learning, natural‑language processing, and VR panoramic technology, the solution integrates three dimensions—valuation, car‑history, and VR 360° view—into an interactive visual interface, allowing users to quickly and intuitively assess a vehicle's condition and price.

The valuation component tackles high‑dimensional, partially missing, and collinear features by grouping vehicles by region and model, quantifying time‑related variables, and training multiple multivariate linear regression models for each subgroup, achieving higher accuracy and interpretability than generic neural‑network or gradient‑boosting approaches.

VR panoramic imaging moves from costly studio setups to a hybrid approach using mobile‑app guided capture, gyroscope, and magnetic sensors, enabling rapid 10‑minute 360° interior/exterior imaging with automated stitching and background blurring.

Car‑history data—including accident, maintenance, and battery records—are normalized through OCR, NLP extraction of time, mileage, monetary amounts, and semantic phrases (e.g., "left‑A‑pillar‑welded"), then mapped to a four‑grade rating system across eight inspection dimensions.

For new‑energy vehicles, a dedicated battery‑data pipeline aggregates factory, usage, and anomaly metrics, applies a scoring model, and generates an online battery health report with estimated range.

Overall, the integrated digital workflow—structured, semi‑structured, and panoramic data processed by AI models—redefines the used‑car buying scenario, improves valuation precision, standardizes car‑history reporting, and delivers cost‑effective VR experiences, thereby accelerating digital transformation of the used‑car industry.