AI-Based Conflict Point Analysis for Junction Safety Audits in Qatar: Enhancing Road Safety in Doha

Urban mobility in Doha has evolved rapidly over the last decade. High-capacity corridors, multilane junctions, signalised intersections and roundabouts now handle complex traffic movements throughout the day. While Qatar has invested heavily in modern road infrastructure, junction safety remains a critical concern. Traditional crash-based safety audits often fail to capture the full picture of risk. This is where road asset management Doha is being strengthened through AI-based road safety survey techniques, particularly AI-based conflict point analysis, which enables proactive and data-driven automated road safety assessment.

Rather than waiting for accidents to occur, AI allows authorities to understand unsafe interactions in real time and improve traffic conflict as part of advanced intersection safety audit practices across Doha.

Why Junction Safety Requires a Proactive Approach in Doha?

Junctions are the most complex elements of any road network. In Doha, rapid traffic growth, diverse driver behaviour and high design speeds increase the likelihood of unsafe interactions even when infrastructure complies with standards. Many serious crashes are preceded by repeated near-miss events that never appear in official crash records.

Relying only on historical crash data presents challenges because minor collisions are underreported and near-misses are never recorded. As a result, safety interventions often happen after fatalities or serious injuries. A proactive approach based on behavioural data is essential for effective AI-based traffic risk assessment in Qatar’s urban environment.

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What Is Conflict Point Analysis and Why It Matters?

Conflict points are locations where the paths of vehicles, pedestrians or cyclists intersect, merge or diverge. Each conflict point represents a potential crash location depending on speed, timing and driver response.

In junctions across Doha, conflict points arise due to turning movements, merging traffic, pedestrian crossings and signal phase overlaps. Traditional audits identify these conflicts through manual observation, which is limited by time and human judgement. AI-based conflict point analysis automates this process by continuously analysing traffic movements and identifying unsafe interactions with far greater accuracy.

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How AI-Based Conflict Point Analysis Works in Practice?

AI-based systems use video feeds captured from junction-mounted cameras or mobile survey units. Advanced computer vision models detect and track every road user, including cars, buses, trucks, pedestrians and cyclists. Each movement is mapped as a trajectory, allowing the system to identify where and when paths come dangerously close.

By measuring parameters such as time-to-collision and post-encroachment time, AI identifies near-miss events that indicate elevated risk. This process forms the backbone of traffic conflict analysis using AI, providing quantitative evidence of safety issues that would otherwise remain invisible.

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Role of AI-Based Road Safety Survey in Junction Audits

An AI-based road safety survey goes beyond short-term site visits. It captures continuous data across different traffic conditions, including peak hours, night-time operations and adverse weather.

For junction safety audits in Doha, this means risk patterns can be analysed across days or weeks instead of a few hours. Engineers gain insight into how traffic behaviour changes with volume, signal timing and congestion. This leads to more accurate AI-based road safety assessment and better-informed safety recommendations.

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AI Intersection Safety Audit for Doha’s Complex Junctions

An AI intersection safety audit uses conflict data to support engineering decisions. Instead of relying solely on design assumptions, engineers can see how drivers actually behave at a junction.

AI insights help identify issues such as late lane changes, red-light violations, aggressive turning movements and pedestrian non-compliance. These findings support targeted interventions such as signal timing adjustments, improved lane markings, revised signage and geometric modifications. When integrated with professional road safety audit practices, AI significantly improves audit reliability.

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AI-Based Traffic Risk Assessment for Better Decision Making

AI-based traffic risk assessment converts raw behavioural data into actionable safety intelligence. Conflict severity and frequency are analysed to prioritise junctions that require immediate attention.

This allows authorities in Doha to allocate resources more effectively, focusing on locations with the highest latent risk rather than waiting for crash statistics to escalate. Over time, this approach leads to measurable reductions in crash rates and improved public confidence in road safety.

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Integration With Road Asset Management Doha

For long-term impact, safety analytics must be integrated into broader road asset management Doha systems. Conflict point analysis becomes even more powerful when combined with asset condition and traffic data.

By linking conflict risk with information from road inventory inspection and traffic survey, agencies can understand how geometry, signage and traffic demand influence safety. This supports lifecycle planning and evidence-based infrastructure investment.

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How RoadVision AI Supports AI-Driven Junction Safety in Qatar?

RoadVision AI enables authorities and consultants to deploy scalable AI-based conflict point analysis across urban networks. The platform integrates AI-based safety surveys with asset data and engineering workflows.

By combining conflict analytics with pavement insights from pavement condition surveys, RoadVision AI supports holistic safety planning. Real-world applications and outcomes are demonstrated through case studies and technical insights shared on the RoadVision AI blog.

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Conclusion

AI-based conflict point analysis is transforming how junction safety audits are conducted in Doha. By focusing on near-miss events and behavioural risk, these  methods allow authorities to act before crashes occur.

RoadVision AI leads the way in AI innovation for road maintenance. Its advanced platform automates traffic surveys, delivers accurate road data, and ensures early detection of maintenance needs like cracks and potholes. Designed in full compliance with IRC standards and Qatar’s road regulations, it enables future-ready infrastructure planning that improves road safety and network efficiency.

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FAQs

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Q1. Why is conflict point analysis better than crash analysis alone?

Because it identifies unsafe interactions before accidents occur.

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Q2. Can AI be used on existing junctions in Doha?

Yes AI systems analyse video data without requiring physical changes.

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Q3. Does AI replace traditional road safety audits?

No it enhances audits by providing objective behavioural evidence.

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