Every day, traffic engineers face an impossible challenge. Traditional crash data only reveals what has already happened. By the time collision statistics justify intervention at a dangerous intersection, lives have been lost and families have been changed forever. Vision Zero initiatives demand a different approach, one that prevents crashes before they happen rather than reacting after the fact.
AI-powered video analytics is changing how transportation agencies approach this challenge. By analyzing video footage from existing cameras and drones, traffic engineers can now identify dangerous patterns, quantify near-miss events, and prioritize safety interventions based on actual risk rather than waiting for crashes to occur. Transportation agencies across the Americas, Europe, to Asia-Pacific are already using these tools to make proactive, data-driven decisions that align with Vision Zero principles.
In this article, we describe five proven ways traffic engineers are leveraging AI video analytics to support Vision Zero goals and create safer streets for everyone.
1. Near-Miss Detection and Proactive Safety Analysis
One of the most frequent and most overlooked indicators of dangerous road conditions are near-misses. These critical safety events happen far more often than actual collisions, yet traditional traffic studies rarely capture them systematically. Manual video review is too time-consuming and costly to analyze the hours of footage needed to identify patterns.
This is where AI-powered near-miss detection closes the gap by automatically identifying conflict events and measuring Post-Encroachment Time (PET), the validated metric that quantifies how close vehicles, pedestrians, and cyclists come to collision. At GoodVision, we provide this technology to process extensive video datasets in hours instead of weeks, capturing every critical interaction that human observers would miss.
Real-World Applications
Transportation agencies are using this technology to assess hazardous intersections where collision history suggests problems but traditional intervention criteria haven't been met. By installing cameras (or using the existing ones) to capture 100+ hours of footage, engineers can sort tens of thousands of vehicle movements to prioritize exact locations where PET metric is dangerous. Then they can look into the details of the most severe cases to identify the specific maneuvers causing conflicts.
At suburban intersections handling high daily volumes, analysis typically reveals near-miss rates of 2-4 events per hour, with specific patterns emerging around left turns, right turns on red, or pedestrian crossings. This data provides the evidence needed to justify proactive interventions like protected signal phases, turn restrictions, or crossing improvements before serious crashes occur.
The analysis delivers results that would be impossible with manual methods, with AI processing extensive footage while saving time and reducing errors. Engineers can filter incidents, review footage with pinpoint accuracy, and combine data visualizations with actual video evidence for effective presentations to decision-makers and community stakeholders.
How It Works
The process begins with a recorded video from fixed cameras with a clear view of the target area. Once uploaded to GoodVision platform, it automatically identifies all road users and extracts full trajectories. Engineers mark reference points to translate pixels into real-world metrics, then set road user combinations based on their specific safety concerns. Our technology then searches for such trajectories and calculates PET metric for each near-collision event. GoodVision then displays conflict events with video evidence and traffic engineer can export detailed reports for further analysis in Excel format.
Transportation agencies using this approach report 90% faster analysis, 95% event coverage capturing every critical interaction, and 80% lower costs than traditional traffic forensic studies.
2. High-Risk Intersection Identification
Vision Zero requires prioritizing limited safety budgets on locations where interventions will have the greatest impact. The problem with traditional approaches is they rely on crash history, which means waiting for people to be injured before taking action. AI video analytics enables a different strategy by analyzing traffic patterns, conflict points, and near-miss events to identify high-risk intersections before serious crashes occur.
Data-Driven Prioritization
State departments of transportation and municipal agencies are now using AI traffic analytics to identify high-risk areas through conflict analysis rather than waiting for crash data to pile up. When you analyze vehicle trajectories with GoodVision, the technology reveals dangerous patterns at intersections that you might not see otherwise:
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Aggressive turning movements that create conflict with opposing traffic
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Inadequate sight lines that lead to late-braking events
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Signal timing issues that force vehicles into risky gap-acceptance decisions
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Pedestrian crossing locations where vehicles fail to yield consistently
This proactive approach aligns directly with Vision Zero principles. Instead of reacting to crashes, agencies can use data to prevent accidents before they happen.
Scalable Analysis
One advantage of AI video analytics is the ability to assess multiple locations efficiently. You can deploy cameras or drones at numerous intersections throughout your network, then process all the video data at once. This scalability allows engineers to evaluate entire corridors or districts, creating a comprehensive risk assessment that would take years using manual observation methods.
Traffic engineering firms have analyzed 60+ junctions in a single month for comprehensive network studies using this approach. They mount cameras to record traffic, upload footage to GoodVision for AI analysis, and get detailed insights into traffic volumes, vehicle classifications, and travel times. This frees up staff for strategic planning tasks while providing precise, actionable data for prioritizing safety improvements.
3. Pedestrian and Cyclist Safety Monitoring
Vulnerable road users represent a quarter of global traffic fatalities, making their protection central to any Vision Zero strategy. Pedestrians and cyclists face unique risks at intersections, crossings, and along shared roadways. The challenge is that traditional traffic counts often overlook non-motorized users or fail to capture the nuanced interactions that lead to dangerous situations.
AI video analytics provides comprehensive monitoring of pedestrian and cyclist movements. GoodVision tracks their trajectories, measures speeds, and identifies conflict points with vehicles. This detailed data reveals where vulnerable road users face the greatest risks and helps engineers design targeted interventions.
Protecting the Most Vulnerable
Transportation agencies worldwide are using this technology for road safety audits near schools, parks, and other areas with high pedestrian activity. Engineers evaluate vehicle speeds, pedestrian volumes, and traffic patterns to assess the impact of existing infrastructure and recommend additional safety measures.
Using drone technology combined with GoodVision's AI video processing, a single operator can capture aerial views of traffic patterns efficiently. You can gather multiple data points that would normally require teams of manual counters. The platform analyzes footage and delivers vehicle classification, pedestrian counts, and speed metrics in under an hour with over 95% accuracy. Compare that to what would be a weeks-long manual process.
Agencies report reducing road safety audit timelines by 80% while delivering actionable insights. The visual data helps present findings effectively to policymakers and secure funding for infrastructure improvements protecting children and other vulnerable road users.
Multimodal Traffic Analysis
GoodVision's platform simultaneously tracks vehicles, bicycles, and pedestrians, giving you a complete picture of how different road users interact. At pedestrian crossings, the technology measures walking traffic and identifies areas of frequent trajectory overlap. This helps engineers understand:
- Whether crossing times are adequate for pedestrian volumes
- Where vehicle-pedestrian conflicts occur most frequently
- How cyclists navigate through intersections alongside vehicles
- Whether dedicated infrastructure like bike lanes is being used safely
Studies show accuracy rates exceeding 99% for motorized traffic and 97% for non-motorized traffic when analyzing complex intersection scenarios. This level of precision ensures that safety improvements account for all road users rather than focusing solely on vehicle traffic.
4. Speed Analysis and Enforcement Planning
Excessive speed directly correlates with crash severity and fatality risk. Every 10% increase in average speed results in a 30% increase in fatal crashes. For Vision Zero strategies to succeed, agencies need accurate speed data to identify where speeding occurs, understand what contributes to it, and plan effective countermeasures.
AI video analytics automates speed measurement across entire roadway networks. GoodVision provides comprehensive data that manual speed surveys simply cannot match in scale or detail. The technology measures actual vehicle speeds throughout an area, not just at specific enforcement points. This reveals the true extent of speeding problems and helps engineers understand driver behavior patterns.
Evidence-Based Speed Management
Transportation agencies conducting school zone safety audits and residential area assessments use GoodVision to process video footage and deliver speed metrics alongside other traffic data. This provides a complete picture of vehicle behavior.
The analysis reveals:
- Speed distributions showing what percentage of drivers exceed limits
- Time-of-day variations in speeding behavior
- Locations where road design may encourage unsafe speeds
- Correlation between speeding and near-miss events
With this data, agencies can make informed decisions about where speed reduction measures will have the greatest safety impact. Instead of relying on citizen complaints or limited spot-checks, engineers can prioritize locations based on comprehensive evidence.
Evaluating Speed Interventions
Beyond identifying problem areas, GoodVision helps agencies evaluate whether speed reduction measures are actually working. By analyzing video footage before and after implementing changes like traffic calming features, reduced speed limits, or enhanced enforcement, engineers can measure the actual impact on driver behavior.
The continuous monitoring capability of GoodVision Live Traffic enables ongoing assessment. Municipalities integrating our AI-driven video analytics into their existing camera networks for real-time traffic monitoring gather detailed data on vehicle speeds alongside queue lengths, traffic gaps, and saturation flows. This comprehensive insight enhances traffic control optimization while providing valuable data for long-term urban mobility planning aligned with safety goals. Detection accuracy rates improve from 70-80% with traditional systems to over 97% with GoodVision's AI-powered platform.
5. Historical Trend Analysis for Safety Improvements
Vision Zero requires sustained effort over time, with continuous evaluation of whether safety strategies are working. Historical trend analysis helps traffic engineers understand how conditions are changing, whether interventions are effective, and where emerging problems require attention.
GoodVision's platform stores processed data in the cloud, so engineers can compare traffic patterns across days, weeks, months, or years. This longitudinal perspective reveals trends that would be invisible in isolated studies.
Long-Term Performance Monitoring
National and regional transportation agencies are adopting GoodVision to transform how they understand traffic patterns and transport interactions across their networks. The technology efficiently transforms raw traffic data into actionable insights, providing standard performance metrics that support long-term planning and safety evaluation.
Agencies report 50-60% savings in data processing and management costs alongside faster output generation and discovery of new insights. These savings free up resources for implementing safety improvements rather than spending limited budgets on data collection.
The platform outputs support project-specific performance metrics including traffic volumes, congestion levels, travel time reliability, and road capacity. These insights help agencies evaluate current conditions and recommend future transport system improvements. The automation capabilities streamline repetitive tasks such as counting, analysis, and reporting, allowing staff to dedicate more time to strategic planning and safety initiatives.
Supporting Vision Zero Goals with Data
Historical trend analysis enables several critical Vision Zero activities:
Measuring Progress Toward Zero Deaths: By tracking safety metrics over time, agencies can demonstrate whether their Vision Zero strategies are reducing crashes and serious injuries. This accountability is essential for maintaining public support and securing continued funding.
Identifying Emerging Safety Issues: Trend analysis reveals where new problems are developing before they result in crashes. For example, gradual increases in near-miss events at a particular location might indicate that conditions are deteriorating and intervention is needed.
Evaluating Infrastructure Changes: After implementing safety improvements, engineers can compare before-and-after traffic patterns to measure effectiveness. This evidence-based approach helps agencies refine their strategies and apply lessons learned to other locations.
Supporting Grant Applications: Many safety funding programs require data demonstrating need and projected impact. Historical traffic data from GoodVision provides the quantitative evidence needed to secure grants for Vision Zero projects.
Transportation agencies using GoodVision report that their work has influenced targeted investments and transport system changes. The ability to deliver verifiable, actionable insights ensures safer, smarter, and more efficient urban mobility, directly aligning with Vision Zero principles.
Moving Vision Zero Forward
Vision Zero is ambitious by design. Accepting any level of traffic deaths or serious injuries as inevitable contradicts our fundamental commitment to public safety. Achieving this goal requires traffic engineers to move beyond traditional reactive approaches and embrace proactive, data-driven strategies that prevent crashes before they happen.
AI video analytics provides the tools transportation professionals need to make Vision Zero a reality. By analyzing near-miss events, identifying high-risk locations, protecting vulnerable road users, managing speeds effectively, and tracking long-term trends, engineers can prioritize interventions where they will save the most lives.
GoodVision delivers measurable advantages over traditional methods:
- 90% faster analysis than manual video review
- 95%+ accuracy in detecting vehicles, pedestrians, and cyclists
- 50-60% cost savings compared to conventional data collection
- 80% reduction in audit timelines for safety studies
- Comprehensive coverage capturing every critical safety event
Transportation agencies worldwide are already using these capabilities to support their Vision Zero initiatives. From state DOTs to municipal traffic departments, from consulting firms to research organizations, traffic engineers are proving that preventing crashes is possible when you have the right data to guide decisions.
The question is no longer whether AI video analytics can support Vision Zero goals. The evidence demonstrates its effectiveness clearly. The question now is how quickly your agency will adopt these tools to start preventing crashes in your community.
Ready to support your Vision Zero initiatives with AI-powered traffic analytics? Schedule a demo to see how GoodVision's video-based safety analysis can identify high-risk locations and prevent crashes before they happen. Contact our team at sales@goodvisionlive.com or use the contact form to send us a message.