DataLens: Pioneering Safer Intersections Through Near Miss Detection
Over the past decade, there has been an escalating emphasis on the prioritization of safety within the realm of transportation engineering professionals. While Department of Transportation entities are embracing Vision Zero objectives and goals aligned with the Safe Systems framework, the bedrock of safety analysis continues to rely on historical crash records meticulously documented by law enforcement personnel. Although this approach holds value, its efficacy wanes when evaluating the real-world impact of recently implemented countermeasures, newly redesigned intersection geometries, or situations necessitating swift response to citizen grievances, without the luxury of a three-year timeline.
What sets us apart is solving the three long-standing obstacles to widespread use of the technology. First, we are a data collection firm that develops software, so we not only process video with our AI platform but we manage the critical aspects of video collection. Second, near miss analysis is often cost-prohibitive. We’re making near miss analysis cost-effective for a wide array of projects, thereby elevating safety at every intersection. Third, in contrast to many existing companies providing near miss analysis, which typically operate on timelines measured in months, our process yields results within a matter of days. At QC, we ensure that your near miss analysis is delivered with the same expediency as our turning movement counts.
Technological remedies, such as systems capable of calculating Post-Encroachment Times (PET) and Time to Collisions (TTC), exist; however, these software solutions are frequently beyond the reach of agencies constrained by resource limitations. Boasting a nationwide presence, we possess a formidable track record in the domain of traffic data collection, serving a diverse array of firms and agencies across the entire country. Our unique position extends beyond mere video footage capture at intersections; it encompasses the utilization of our exclusive AI-powered platform, called DataLens, enabling the provision of comprehensive reports and videos detailing near miss conflict analyses. In effect, agencies now have at their disposal a cost-effective avenue to enhance safety measures at every intersection, a choice that stands in stark contrast to alternative approaches.
Whether deployed autonomously as a robust safety instrument or employed synergistically to augment and validate pre-existing safety assessments, QCs near miss conflict analysis reports stand as a potent means to advance your safety benchmarks and objectives while prudently managing project expenditure.
Improved Traffic Planning and Optimization
DataLens employs the PET methodology, bringing about a significant boon to traffic planning and optimization. By accurately detecting near misses and potential safety incidents at intersections, DataLens provides crucial data that can inform countermeasures. With insights into high-risk movements and conflict points, transportation engineers and planners can devise more effective traffic signal timing and intersection designs.
Enhanced Intersection Safety
DataLens’ ability to identify near misses directly contributes to intersection safety. By pinpointing collision points, practitioners can proactively address safety concerns and implement tailored measures to prevent accidents. The insights gained from DataLens allow for identification of trends and patterns in hazardous behaviors, leading to targeted educational campaigns, enhanced signage, and infrastructure adjustments that mitigate safety risks. As a result, the system plays a pivotal role in creating safer intersections for all road users, from pedestrians to motorists.
Reduced Manual Data Collection Efforts
One of the most notable advantages of DataLens is its ability to drastically reduce the need for costly data collection efforts. Traditionally, collecting intersection safety data required labor-intensive processes involving on-site observations and data entry. Newer methods involve video analysis approaches that are cost-prohibitive to perform on a routine basis. With DataLens, video analysis automates the detection of near misses alongside the production of turning movement count data, eliminating the need for more complex and costly video analysis processes. This not only saves valuable resources but also accelerates the data collection process, allowing for more frequent and consistent safety assessments without straining public budgets.
Data-Driven Decision-Making for Infrastructure Improvements
DataLens empowers decision-makers with comprehensive, data-driven insights that pave the way for informed infrastructure improvements. By analyzing near miss occurrences and PET values, practitioners can prioritize and justify investments in intersection redesign, signal upgrades, pedestrian infrastructure enhancements, and more. This approach ensures that limited resources are allocated efficiently to address the most pressing safety concerns. DataLens’ data-driven approach fosters evidence-based decision-making, leading to well-targeted interventions that have a tangible impact on intersection safety and overall traffic management.