Four killed, 3 hurt as truck rams into stationary MUV in Prayagraj’s Soraon
Eight people from the same village were going to Kanpur in a MUV after offering Pind Daan to their ancestors in Gaya
Four people died while three others were critically injured in a road accident, as an unidentified vehicle rammed into a Bolero MUV parked on a highway under Soraon police station area of Prayagraj, in the wee hours of Monday.

The deceased include Suresh Bajpai, 55 and his wife Tara Bajpai, 50, along with his uncle Ram Sagar, 65, and nephew Suresh Saini, 50, while Mamta Devi, Prema Devi, and Komal Devi were admitted to hospital in a critical condition.
Eight people from the same village were going to Kanpur in a MUV after offering Pind Daan to their ancestors in Gaya. Their MUV broke down late at night on the highway. Unable to repair the vehicle, the family parked the MUV by the roadside and slept in front of it.
A truck collided with the MUV at around 4 am on Monday. Owing to the severe impact, the Bolero ran over all the four people sleeping in front of it, killing them on the spot. In the incident, of the remaining four present inside the vehicle, three of them, all women, were critically injured. The fourth person, inside the vehicle, a 60-year-old man, survived the accident without any injuries.
According to deputy commissioner of police (trans-Ganga), Kuldeep Singh Gunawat, Dial 112 service received information about the accident in Soraon area at around 4am. The three injured women have been admitted in a critical condition to Swaroop Rani Nehru (SRN) Hospital for treatment. Premnarayan, 60, the only person not injured in the accident, narrated the incident to the police. As per the DCP, CCTV footage and toll records of the area were being examined to determine the cause of the accident.
In the accident, the MUV was severely damaged with blood splattered all over the road at the site of the mishap.
According to SHO of Soraon police station, Keshav Verma, the truck driver who hit the MUV escaped from the scene with the vehicle and records of the nearest toll booth as well as CCTV footage of the area were being scanned to identify him.