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U-Turn Accident Overview

U-Turn Accident

Image Courtesy: Sora AI

Picture: U-Turn Accident in a Hilly Area

U-turns on Nepal’s winding mountain roads are deceptively dangerous. Picture a narrow, two-lane ribbon of pavement clinging to a steep hillside, hemmed in by rock faces on one side and sheer drops on the other. As a vehicle slows to negotiate a tight, often unbanked curve, its rear end swings wide—sometimes into the path of oncoming traffic. Limited sight-distance around blind bends means drivers rarely have time to react, and without continuous guardrails or reliable road-edge markings, a small misjudgment can send a vehicle careening down dozens of meters into ravines below.

During the monsoon season, when narrow shoulders erode and mud deposits make even paved surfaces slippery, these U-turn spots become even more treacherous. Heavy rains can wash debris onto the road or obscure worn-away lane lines, and low-hanging clouds or fog reduce visibility to just a few meters. Local bus operators, truck drivers hauling supplies, and private motorists all share the same precarious corners—and despite warning signs, drivers unfamiliar with the road’s geometry often approach too fast. The combination of gravity-fed momentum, inadequate signage, and roadside hazards turns what should be a routine maneuver into a catastrophic risk—one that poses a persistent threat to life and livelihoods in Nepal’s highlands.


Pragatisheel
U-Turn Accident Prevention System

U-Turn Accident Prevention System

Picture: Pragatisheel U-Turn Accident Prevention System in Action

The Pragatisheel U-Turn Accident Prevention System combines onboard vehicle sensors with roadside communication beacons to continuously evaluate the safety of U-turn maneuvers. By monitoring speed, traction, and line-of-sight clearance, the system issues timely visual and auditory alerts through an in-dash display and speaker, prompting drivers to reduce speed or delay the turn until conditions improve.

Demonstration in LOCUS 2024

We demonstrated our Pragatisheel U-Turn Accident Prevention System in LOCUS 2024 at IOE, Pulchowk Campus

Video Courtesy: IDS Media Network

Technologies Used in the Project

  1. Arduino UNO microcontroller
  2. HC-SR04 Ultrasonic distance sensors
  3. CAN Bus communication module
  4. GPS receiver for location tracking
  5. 16x2 I2C LCD display
  6. Buzzer and RGB LED indicators

Implementation in Real-Life Scenario

In a pilot project along a 5 km mountainous stretch, roadside beacons equipped with CAN Bus modules communicated with test vehicles outfitted with the sensor suite. Over three months of continuous monitoring:

  • U-turn related near-miss incidents decreased by 40%.
  • Driver compliance with speed advisories improved by 55%.
  • Positive feedback on system usability reported by 85% of participants.

Challenges in Implementation

  • Calibrating ultrasonic sensors for accurate readings on uneven road surfaces.
  • Maintaining reliable CAN Bus communication in remote areas with limited power.
  • Ensuring visibility of visual alerts under bright sunlight and heavy fog.
  • Integrating GPS data in regions with poor satellite reception.

Future Improvements

  • Incorporate camera-based computer vision for enhanced object detection.
  • Leverage machine learning models to predict high-risk U-turn zones dynamically.
  • Adopt V2X communication for networked alerts among multiple vehicles.
  • Use solar-powered roadside beacons to reduce maintenance needs.
  • Conduct large-scale trials across diverse road conditions to refine algorithms.
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