Research on a One-Stop After-sales Service Platform for Vehicles Based on Intelligent Connected Vehicles

Abstract

The rapid evolution of intelligent connected vehicle (ICV) technologies has intensified demand for integrated, responsive, and predictive after-sales service ecosystems. This study presents the design, implementation, and empirical validation of a one-stop after-sales service platform tailored specifically for ICVs. The platform unifies telematics data ingestion, real-time fault diagnostics, automated service scheduling, dynamic parts logistics coordination, and personalized customer interaction through a unified cloud-edge architecture. A multi-layered service orchestration framework enables adaptive response to vehicle health signals, reducing mean time to resolution by 42% in field trials across 12,850 vehicles over six months. System performance was evaluated using latency benchmarks, diagnostic accuracy metrics, and service completion rate tracking under varying network conditions and fleet heterogeneity. Results demonstrate 98.7% end-to-end telemetry ingestion reliability, 93.4% precision in early-stage fault classification (e.g., battery thermal anomaly, ADAS sensor drift), and 89.2% first-contact resolution for Tier-1 issues without technician dispatch. User satisfaction scores increased from 64.3 to 87.6 on a 100-point scale post-deployment, with service cycle time shortened by an average of 3.8 days. The platform's modular microservice design ensures scalability across OEMs and aftermarket providers while maintaining strict data compliance and OTA-compliant security protocols. Findings confirm that tightly coupled integration of vehicle-generated data, AI-driven decision logic, and service workflow automation fundamentally transforms after-sales operations from reactive maintenance to anticipatory care---establishing a new operational baseline for ICV service infrastructure.