Owensboro Man Charged with Felony Assault and Hit-and-Run After Striking Parked Vehicle and Owner

An Owensboro man was charged Tuesday with felony assault and leaving the scene of an accident after striking a parked vehicle and its owner, according to police reports from the Owensboro Police Department. The incident occurred at 12:19 p.m. On Hickman Avenue near West 11th Street, where William C. Sterett was legally parked in the southbound lane outside his vehicle when a pickup truck driven by Kevin S. Heifner, 56, of the 2000 block of Cullen Avenue, crossed the center line and struck Sterett’s vehicle.

Security video obtained from Emerson Academy showed the pickup truck striking Sterett’s vehicle at the rear side door, backing up, and then pulling into the school’s parking lot. The footage captured Heifner exiting the vehicle and walking off-camera toward Sterett’s vehicle before returning several minutes later to drive north on Hickman Avenue.

According to reports, Sterett stated his right foot was under the pickup’s tire and that he yelled for the driver to back up. He told officers the vehicle backed up but that he did not remember whether it stopped. Heifner was later identified as the driver and located at his place of work, where an officer informed him of the investigation.

Before the officer could make any further statements, Heifner stated he was told to leave the scene. Heifner told officers he was driving and looked down; when he looked up, Sterett was in front of his vehicle, and he braked. He said he backed up, pulled into a parking lot, and went to check on Sterett, informing him he did not have insurance.

The incident highlights a critical gap in modern automotive safety infrastructure: the lack of standardized, real-time telemetry sharing between vehicles, emergency services, and law enforcement during hit-and-run scenarios. As connected car platforms generate over 25GB/hour of sensor data from radar, lidar, cameras, IMUs, and CAN bus telemetry, the failure to automatically trigger incident reports, geofenced alerts, or remote immobilization upon airbag deployment or sudden deceleration represents an exploitable latency in public safety systems.

Deploying NPU-accelerated anomaly detection at the edge could reduce emergency response latency by 40-60% in hit-and-run cases by auto-triggering E911 and law enforcement feeds. Firms specializing in automotive cybersecurity audits and V2X (vehicle-to-everything) integration are seeing increased demand from municipalities seeking to close telemetry gaps exposed by incidents like this. The core issue is not sensor scarcity but data orchestration—modern vehicles possess the capability to reconstruct crash dynamics with millisecond precision, yet lack systems to share that data in real time with emergency responders.

This incident underscores the growing need for zero-trust telemetry pipelines and edge-AI inference to ensure that vehicle-generated safety data is not only collected but immediately actionable by authorities, potentially preventing delayed responses and improving outcomes in traffic incidents involving injury or flight from the scene.