Nashik Hit-And-Run: Devotee Crushed By Speeding Pickup, CCTV Captures Incident

Nashik: A heart-wrenching incident took place this morning on the Girnare-Dugao road, located near Nashik city. An innocent devotee, who had set out for his daily worship as usual, was crushed to death on the spot by a speeding pickup jeep. The deceased has been identified as Walu Thete (aged approximately 50-55). The entire sequence of this horrific accident was captured by CCTV cameras installed in the vicinity, and the driver fled the scene along with the vehicle immediately after the crash.

According to reports, Walu Thete was walking along the Girnare-Dugao road this morning, heading towards a nearby temple for worship. As the devotee walked along the road amidst the pleasant morning atmosphere, a speeding pickup truck approaching from behind struck Thete with tremendous force. The impact was so severe that Thete was thrown onto the road and, having sustained critical injuries, passed away on the spot.

In a shocking display of inhumanity, instead of stopping to assist the injured victim after the crash, the pickup driver fled the scene. After striking the pedestrian, the driver accelerated the vehicle and made a hasty escape from the accident site. This callous act has sparked outrage among the local residents.

The entire incident was captured by a CCTV camera installed outside a shop located in the immediate vicinity of the accident site. The footage clearly shows the pickup truck speeding towards the pedestrian, followed by the violent collision. The police have initiated an investigation based on this CCTV footage, and the process of registering a case against the unidentified driver is currently underway.

Upon receiving information regarding this incident, local police rushed to the scene and conducted a spot inspection. The body has been sent to the District Hospital for a post-mortem examination. The police have dispatched teams to search for the pickup truck driver, who fled the scene, and the investigation is proceeding based on the vehicle's registration number captured in CCTV footage.