Course Content

Introduction

In urban areas, traffic congestion is one of the biggest challenges faced by emergency services such as ambulances, fire brigades, and police vehicles. Delay in clearing traffic at intersections often leads to loss of critical time, which can be the difference between life and death in emergency situations. Traditional traffic management systems operate on fixed timers or semi-automated control, which are not responsive to emergency vehicles.

To address this issue, a Smart Ambulance Traffic Clearance System has been proposed and developed using Raspberry Pi 4 as the central controller. The system ensures that whenever an ambulance approaches a traffic signal, it is detected in advance, and the corresponding traffic signal is automatically turned green for the ambulance’s route, while other directions are switched to red, thereby creating a green corridor.

In the prototype, the ambulance is equipped with an RFID tag or wireless beacon, while the traffic junction has an RFID reader/sensor node connected to Raspberry Pi 4. When the ambulance approaches the junction, the reader detects the tag and sends the information to the Raspberry Pi, which processes the input and immediately changes the traffic signal status.

The Raspberry Pi 4, being a powerful single-board computer with GPIO interfaces, is ideal for this application as it can:

• Process sensor input in real-time.

• Control traffic lights through driver circuits.

• Communicate with a control room or cloud server for logging and monitoring.

• Run flexible software (Python-based algorithms) for authentication, safety timers, and event logging.

This smart system eliminates the need for manual intervention by traffic police and ensures faster response times for ambulances. It is scalable, cost-effective, and can be integrated into existing traffic management infrastructure with minimal modifications.

Objectives

• Detect an active emergency run and continuously publish the ambulance’s authenticated location and ETA.

• Request signal priority/pre-emption at approaching junctions.

• Provide the driver with real-time navigation and route status.

• Maintain reliable fallbacks (SMS, radio, on-vehicle beacon) if data links drop.

• Log trips for audit and performance metrics (response time saved).

Methodology (System Workflow)

1. Sensing & Context

   • GPS/GNSS fixes location/speed; driver or siren-sense sets Emergency Mode ON.

   • Optional sensors: IMU (harsh braking), OBD-II/CAN (vehicle status), camera/mic (situational awareness).

2. Edge Processing (Raspberry Pi 4)

   • Fuses sensor data, validates GPS, computes ETA to next junctions, packages priority requests (MQTT/HTTPS).

   • Displays navigation + signal status to driver; triggers local beacons/LED matrix.

3. Communication

   • Primary: 4G/5G modem (MQTT/REST to backend).

   • Fallbacks: SMS to control room, V2X/LoRa/DSRC to nearby roadside units.

4. Backend / Traffic Control

   • Authenticates ambulance, propagates SPaT/MAP compatible priority to Traffic Signal Controller / IoT gateway.

   • Runs rules (e.g., max priority time, queue clearance), updates corridor signals, returns acknowledgements & new route hints.

5. Intersection Action

   • Controller advances/extends green for the ambulance approach, safely transitions other phases (with pedestrian/vehicle clearance windows).

6. Monitoring & Logging

   • Trip timeline, intersections served, time saved, link reliability; data for dashboards and QA.

Working Principle (Core Concepts)

• Priority Signalling: Grant temporary right-of-way by altering the signal phase plan when an authenticated emergency vehicle is close.

• ETA-Driven Requests: Only ask for priority within a threshold (e.g., 30–60 s out) to avoid wasteful pre-emption.

• Secure Telemetry: Signed tokens + device certificates to prevent spoofing.

• Fail-Safe Operation: If network fails, on-vehicle RF beacon or DSRC/RSU still triggers local priority; driver info remains available offline.

Key Hardware

• Raspberry Pi 4 (4GB recommended), 32-bit/64-bit OS

• GNSS module (u-blox NEO-M8/9 or similar)

• 4G/5G LTE modem (USB or HAT) + high-gain antenna

• Optional: OBD-II/CAN HAT, IMU (MPU-9250/ICM-20948), camera, microphone

• Output: 7–10″ HDMI display, buzzer/speaker, LED matrix/roof beacon, optional LoRa/DSRC/802.11p unit

• Protected vehicle power: 12 V→5 V/3 A DC-DC with surge/EMI filtering

Software Stack

• Edge (Pi): Python, paho-mqtt, requests, pyserial, GPIO/CAN libs; Map SDK (OSRM/GraphHopper/Mapbox/Google as allowed)

• Backend: MQTT broker (EMQX/Mosquitto), REST API (Flask/FastAPI), DB (PostgreSQL), rules engine for priority, dashboard (Grafana)

• Security: TLS, device certificates, JWT for API, rotating keys

Applications

• Faster emergency response for ambulances, fire, police.

• Green corridors for organ transport or disaster relief convoys.

• City-wide analytics on response time, bottlenecks, and corridor planning.