We are proud to announce that a new version of the DataFromSky Viewer is now available and brings lots of new amazing features for the advanced Safety Analysis. Do you want to evaluate how many risky situations and dangerous driving events occurred on the road? Use our DataFromSky intelligence! We can count the milliseconds to the near accident and predict the accident before it happened!
Traffic safety is a very important subject in the traffic industry and therefore our focus in this version was mainly on the new Safety Analysis feature that detects traffic conflicts like Time to Collision, Post-Encroachment Time or Heavy Braking in the scene. The DataFromSky Viewer now becomes a first tool that allows the user to detect and interactively analyse various traffic conflict situations between different traffic objects. Besides the standard ways of detecting the preemtive traffic conflicts, we used an innovative approach to simulate traffic object movement. Due to the huge interest in the traffic Safety Analysis, you can look forward to new features regarding this topic in the near future.
Enjoy a video showing an example usage of the new Safety Analysis feature:
The development of DataFromSky Safety Analysis features is done in collaboration with FAST VUT Brno and is supported by Technological Agency of Czech Republic (TAČR, project TH02010882).
A very good summarizing article about the capabilities of DataFromSky and how the advanced image data processing is contributing to optimize the urban mobility has been published on LinkedIn. Several use cases in which the data from the sky might be helpful are described by this article:
– possibility of analyzing the traffic node in terms of traffic safety – based on the detection of risky situations, near accidents and collisions
– analysis of interaction of vehicles, cyclists and pedestrians in public areas such as in surroundings of schools, city centers, bus and train stations etc.
– studies of parking lots utilization, behavior of vehicles in a carpark
– and many other applications which you can think about
To summarize, the greatest benefits of traffic research from the aerial video using advanced software for image processing are:
A) Accurate and detailed data about traffic from the bird’s eye perspective:
– complete trajectory and moving patterns of each traffic participant
– complex OD- matrix – vehicle counts, turning movements
– speed and acceleration profile of each vehicle
– vehicle classification into categories (car / heavy vehicle / bus, / motorcycle etc.)
– measurement of travel time and stationary time (queuing time)
– advanced heatmaps based on the velocity, acceleration, traffic flow
– evaluation of traffic safety (detection of near accidents based on calculation of Time to Collision [TTC], detection of risky situations or inappropriate driving behavior, heavy breaking)
B) Reliable, detailed research without influencing traffic behavior (inconspicuous solution).
C) Ultimate traffic research, almost without a human intervention – based on the machine learning and DNN.
D) Powerful tool which can improve traffic safety and urban planning of many Smart cities.
Do you want to know more? Read the whole article – click on this link.
Safety is one of the most important aspects of the traffic industry. Many serious traffic incidents happen on the roads worldwide every day. Thanks to the huge amount of traffic information gathered by DataFromSky aerial video analysis we are able to detect near-crash events, traffic conflicts, that statistically occur more frequently than real traffic accidents. By using this proactive approach that focuses on analyzing dangerous traffic situations that can but not necessarily have to lead to a traffic accident it is possible to detect:
– aggressive driver behavior
– offensive lane changing
– short following distances
– collision-prone traffic hub areas
So far, we have implemented some of the standard safety indicators like Time To Collision (TTC), Time Exposed Time To Collision (TET), Time Integrated Time To Collision (TIT) and Post-Encroachment Time (PET) which are used to detect traffic conflicts in spatial-temporal data obtained by DataFromSky aerial video analysis. The standard evaluation of some of these indicators was extended by road users movement prediction that better reflects their behavior and achieves better results. All of the detected traffic conflicts are properly visualized in DataFromSky Viewer where they can be interactively analyzed.
More features regarding the Traffic Safety analysis are coming. The project of Traffic Safety Analysis is jointly developed with the Faculty of Civil Engineering BUT and is supported by Technological Agency of Czech Republic.
Following video demonstrates the capabilities of DataFromSky Traffic Safety Analysis:
We are continuously working on traffic behavior analysis of traffic participants in surrounding of schools and kindergartens in Denmark. DataFromSky together with COWI has created another data-rich analysis of traffic behavior nearby a school in Vejle Municipality. The analysis maps traffic near the school during the morning rush hour when many students arrive at school at the same time. It also gives a complex overview, where potential conflicts between cyclists, pedestrians and cars may happen.
Based on the analysis and its outputs, it is easier to formulate some changes which should be adopted by schools to protect the safety of schoolchildren. This analysis can also lead to better decision making done by municipalities, whether to build a new crossing or add some safety features or how it is possible to change an established behavior that is dangerous or inappropriate.
Have a look at the report in the Danish TV SYD.
Trajectories: pedestrian (pink), bicycles (blue), cars (green)
Heatmap showing acceleration of bicycles and pedestrians – displaying possible conflict areas
Another great project has been accomplished, among other things, thanks to DataFromSky analysis! DataFromSky has made a traffic study of a corridor in the city of Fairfield in Connecticut, U.S.. The data were used for an extensive Safety analysis of the whole corridor called Black Rock Turnpike. The study, created by The Connecticut Metropolitan Council of Governments (MetroCOG) and FHI, identifies strategies to create a safe and attractive pedestrian environment, a robust infrastructure for bicyclists, and linkages between residential areas and the shops, businesses and restaurants along Black Rock Turnpike.
Black Rock Turnpike is a major arterial that serves one of the city’s largest business and commercial districts. According to the estimates, approximately 20,000 vehicles utilize this corridor every day. As the results of the analysis show – although Black Rock Turnpike has a posted speed limit of 50 km/h (30 miles/h), the average speeds are between 55 – 65 km/h (35-40 miles/h). The road widths, speed, high traffic volume and numerous curb cuts create an unsafe and uninviting pedestrian environment. Click on this link to read more about the whole project.
However, what is truly remarkable about this analysis is the method how the data were recorded and analyzed. To be able to cover the whole corridor, which is roughly 1,3 km in length, up to 8 drones recording at the same time were needed! This allowed us to analyze the corridor as a complex scene, obtain the complete trajectories of vehicles for the whole analyzed route and create the detailed Origin-destination statistics! What were the key conditions for the successful analysis?
- top-down view position (bird’s eye perspective)
- space overlap – at least 10 % of overlap in the analyzed area from each side
- time overlap – all the drones started filming at the exact same time
Take a look at the video of raw output of 8 drone videos merged together:
Our solution can be used for tracking not only cars and various vehicles, but also for tracking other objects and traffic participants, for example pedestrians or bicycles. Our partner from Denmark – traffic engineering company COWI – is currently studying and analyzing the behaviour of traffic participants in surroundings of schools and kindergartens in Denmark by using DataFromSky for the analysis. It would provide a new and systematic overview of the situation during the morning peak hour, when many students arrive to school at the same time. More detailed, they are searching for some inappropriate and dangerous behaviour of road users and other participants of the traffic, which includes all the parents driving their children to schools, school buses, bikes, motorbikes, other vehicles passing by the neighbourhood and all the pedestrians. Based on this analysis it is easier to formulate some proposals of changes which should be adopted by schools to protect the safety of schoolchildren. This analysis can also lead to better decision making done by municipalities, whether to build a new crossing or add some safety features etc.
If you want to read more about this analysis and its application, visit this website, where you can find the whole article: https://cowicitycreators.wordpress.com/2017/02/22/hvor-farlig-er-skolevejen-naar-vi-ser-den-fra-luften/#more-2643
An example of mapping the behaviour of traffic users is shown in the pictures below, where different user types have different color and each line shows the traffic flow for one trajectory.
Picture: Before (1.) and after (2.) changes: Each line shows one trajectory. Pedestrians (blue), cyclists (red), drivers (green).
We are happy to announce that we have succeeded with our proposed project and get supported in Programme Epsilon 2 conducted by Technological Agency of Czech Republic:
System for Preemptive Safety Analysis of Road Network Nodes and Traffic Flow
The aim of the project is development of a preemptive quantitative system for analysis of road network nodes in terms of safety. The system will be
based on analysis of time-space information about each individual traffic member. The information will be automatically extracted with high precision
and frequency from video data collected by UAVs. The trajectory data extracted from video will be analyzed in terms of traffic safety, based on
detection of non-standard and aggressive behaviour, conflict situations, incomfort during passage etc.