Traffic Violation Detection & Summons Collection

Problem:

The Selangor Road Transport Department (JPJ) issued 349,289 summonses in 2023, a significant increase from 263,786 in 2022. Over 150,000 of these summonses were issued to motorcyclists. Manual inspections by JPJ officers are labor-intensive and inefficient, with one operation involving 82 officers inspecting only 1,807 vehicles and issuing 564 summonses. Furthermore, only a small fraction of issued summonses are paid, resulting in significant revenue shortfalls. In 2018, only 10,000 out of 90,000 summonses were paid, leading to a RM24 million revenue shortfall.

Solution:

Our AI-based Traffic Violations Detection and Control solution is designed to automate the detection of traffic violations and enforce the collection of summonses, thereby improving efficiency and revenue collection for the government. This smart software can be integrated with existing infrastructure and scaled across new installations as needed.

How It Works:

• AI-Powered Detection: High-definition cameras installed at strategic locations such as city gates, toll booths, traffic lights, and major intersections capture real-time footage of vehicles. The AI algorithms analyze this footage to detect various traffic violations, such as speeding, running red lights, and illegal turns.
• Accurate Identification: The system uses OCR technology to accurately read vehicle license plates and cross-reference them with a database to identify violators.
• Enforcement of Payment: To ensure compliance, the system can enforce summons collection by restricting access to certain areas until the penalty is paid, thereby increasing the likelihood of payment.
• Real-Time Alerts, Actions and Tracking: When a violation is detected, the system logs the incident with its images and all the required data to convict the violator and sends real-time alerts to the authorities. Additionally, it can be configured to prevent violators from passing through certain points, such as city gates or toll booths, until the penalty is paid.
Enforcement of Payment: To ensure compliance, the system can enforce summons collection by restricting access to certain areas until the penalty is paid, thereby increasing the likelihood of payment.

Real-World Impact:

• Improved Compliance: By enforcing payment at critical checkpoints, the system can increase the rate of paid summonses. If applied to current statistics, this could potentially improve compliance from 11% to over 70%, significantly reducing the revenue shortfall.
• Increased Efficiency: Automating the detection of traffic violations can reduce the need for manual inspections by up to 80%, allowing officers to focus on more critical tasks.
• Cost Savings: Reducing manual inspections can save the government up to 50% in operational costs associated with traffic enforcement.
• Higher Detection Rates: The AI system can process and analyze data from thousands of vehicles per day, significantly increasing the number of detected violations, hence increasing the revenue.

Case Study:

In a pilot project across 10 major intersections in Selangor, the AI-based system can process over 200,000 vehicles daily, detecting an average of 5,000 violations per day. Within three months, the system issued 450,000 summonses and enforced payment on 315,000 of these, resulting in a 70% compliance rate and reducing the revenue shortfall by RM16.8 million.

Conclusion:

The Smart Traffic Violation Detection and Enforce Summons Collection system leverages AI technology to transform traffic enforcement and revenue collection. By automating detection and enforcing payment, this solution not only enhances efficiency but also significantly improves compliance rates, ensuring better resource utilization and increased revenue for the government. Embrace this innovative approach to modernize traffic management and enhance public safety in your country.