Ideaz

Problem

The traffic congestion due to poor management of signals is a major problem in India. During my daily trips to university and home, I often find myself wasting time at red lights that serve no purpose because there is no traffic at the other intersections. Not only does this delay travel, but it results in wasted fuel, added emissions and unnecessary stress for commuters. Especially near my house , the police have to stop the traffic signal completely and manually control the traffic everyday as there is more traffic on one side of the road.This problem affects me personally as I reach home late almost everyday disrupting my university-life balance. The challenge is more critical with developing cities as the traffic is unmanaged and varying at maximum extent in a day.

What Already Exists

At present, most traffic signals in Indian cities work on pre-fixed timings. The red, yellow and green phases are predetermined according to historical traffic surveys. For instance, the traffic signal may stay green one way for 60 seconds, and the other 30 seconds, with no regard for whether cars are queued up or not. Some cities like Bengaluru, Delhi or Hyderabad have implemented the use of adaptive traffic control systems with pre-deployed sensors, inductive loops and high-resolution cameras. They time themselves in real time according to the flow of vehicles.

Why the solutions are not ideal

Fixed-time systems have become outdated due to their inability to adapt in case of sudden variation like an accident, festival rush or late night empty road. So many vehicles are unnecessarily idling, which leads to increased commute times and wasted fuel. Adaptive solutions available in metro cities, on the other hand, are expensive. The infrastructure of high end cameras, underground sensor loops and networking take a heavy investment and maintenance , in dusty and monsoon India, where power can be irregular , these systems frequently fall apart. When they fail, police officers have to step in the road and manage circulation. This is the opposite of automation. Also, there is no easy way to expand these expensive systems to smaller towns, making a majority of the country with inefficient fixed time signals.

What We Can Do Better 

With my limited knowledge of programming and algorithms, this is the best solution I can come up with. I studied MySQL and databases in grades 11 and 12, and I feel that this could be a decent approach to solving everyday traffic problems.

A more affordable adaptive solution might be found with less complicated sensors and more intelligent software. Options that are far cheaper than expensive buried loops or state of the art AI cameras, such as: 

• Infrared vehicle counters: inexpensive, weather-resistant, and easy to mount on poles.
  
  
• Basic CCTV cameras with open-source image recognition: software-based processing reduces hardware cost.
  
  
• RFID readers for buses and emergency vehicles: ensures public transport and ambulances get priority without human help.
  
  
• Solar-powered traffic lights: cuts down electricity bills and prevents signal failures during power cuts.
  
  

At the heart of the system will be a MySQL database, which stores traffic information in real-time and over time. Each signal measures: road ID, time, vehicle volume and average headway. The algorithm operates based on these data and questions this data in order to control green light dynamically. Algorithm Outline Input: The number of vehicles on the sensors at each scanned road attached to the signal.

Decision:

If one road has no cars → switch the green light to that with waiting cars immediately.

If there is a queue long enough (Q > Threshold) we should be giving them green.

In the peak periods → apply historical database information to pre-assign longer green times.

Enforce fairness so that no road waits indefinitely.

Output: Automatically update signal cycle, write new timing to the database.

Cost Savings Installation: The cost of infrared sensors and open-source software is significantly lower than that of imported adaptive systems.

Power: Solar lights are energy-saving and environmentally-friendly with high-quality.Solar powered outdoor lights are cost-effective because they are very energy efficient. Reduce your electricity costs and save you money.

While not immune to abuse and damage, LoopBox and Trailblazer are both resistant to dust, moisture and rain. Easy-to-replace sensors mounted above the road are far superior compared to wires that run in a trench under the road.

Scalability: Because it is affordable, this system can be adopted in smaller cities and towns that cannot afford expensive smart-city projects.

Reduced Police Intervention : Presently, traffic police jump signals during peak hours or in case of a signal failure. With this system: Instant detection eliminates the need for officers to be stationed on busy crossroads.

A single monitoring dashboard makes it possible for a few officers to monitor numerous intersections from afar.

Emergency vehicles can be automatically identified with RFID tags, without reliance on manual police cooperation.

Who It Benefits 

This will help a lot of people such as daily commuters (by cutting wait times) , smaller towns where the budget is limited , public transport and emergency vehicles like the ambulance move faster as signals are prioritised , and the traffic police who can focus on solving problems such as taking care of people who have no common sense to follow traffic rules. 

Small sample code on storage of data : 

CREATE TABLE trafficdata (

    signal_id INT,

    road_id VARCHAR(20),

    timestamp DATETIME,

    vehicle_count INT,

    avg_wait_time FLOAT,

    PRIMARY KEY(signal_id, road_id, timestamp)

);

IR vehicle counters (₹2k–5k), basic CCTV with open-source software on Raspberry Pi, and RFID tags for buses/ambulances. Solar-powered units cut energy costs, while a phased rollout installs sensors only on major roads.