- AI and Deep learning algorithms - No tradeoffs between high accuracy rate and low false alarm rate as traditional systems,
- 95%+ detection rate and less than 1/cam/day false alarm rate,
- Proven in detailed tests by respectable authorities worldwide FDOT (USA), CALTRANS (USA), Finnra (Finland), Netivei Israel (Israel), Ashghal (Qatar), ...
XAID™ Traffic Video Analysis - Automatic Video Incident Detection (AVID) system based on AI machine learning and cognitive recognition achieves less false alarms ratio and better detection accuracy than traditional non-AI video incident detection systems (up to 3x better detection rate, 4x less false alarms, 2x better classification then traditional systems). This creates the new reliability standard in video detection industry.
XAID™ performs incident detection and classification in real traffic environment. Verified in comparative tests, in realistic conditions (all weather conditions, bad illumination, poor video streams ...), it meets needs and expectations of Traffic Agencies on systems for video analytics.
Example of video analytics
XAID™ Case Study Floyfjell Tunnel
XAID™ Case Study for the Keilaniemi Tunnel
XAID™ Case Study Bus Lane Management System
1. Main functionalities
Real-time incident detection. Real-time traffic measurement. Area of use
Wrong-way driving, stopped vehicle, traffic slowdown/congestion, slow vehicle, pedestrian on the road, reduced visibility (smoke), debris on the road, moving object (animal detection).
Average vehicle speed, traffic volume, classification, occupancy, levels of service.
XAID™ is specifically designed to work in tunnels, freeways, arterials and bridges.
High accuracy and robustness – it learns in its working environment
Less false alarms and higher detection accuracy thanks to AI-based approach.
Not affected by common problems, e.g., camera vibrations, weather conditions, variations in illumination, low video quality.
Thanks to its learning capabilities it can adapt to environmental conditions through project specific tuning providing best possible performance for a specific environment.
New generation of computer vision algorithms
State-of-the art object detection and classification based on deep learning.
A 100+ layer deep neural network trained on more than 50M samples (and counting) provides accurate object detection, object segmentation and classification even in highly dense traffic.
Set-up and configuration, modes of integration
Works on existing commonly used cameras for traffic monitoring or newly installed cameras for XAID™. Features intuitive and user-friendly configuration tool – the user can modify detection zones, alarm thresholds and many more.
Integration to 3rd party systems via number of interfaces (REST, TCP/IP, NTCIP C2C, MODBUS).
2. Advanced functionalities – step further to incident management
XAID™ can be used for incident detection and traffic measurement on video cameras and integrated into a 3rd party management/monitoring system via numerous interfaces it provides. Another possibility is to use XAID™ in combination with Telegra’s solution for traffic management and monitoring – topXview™ - to provide following advanced functionalities and improvements:
Integrated video management system with video analytics
Native integration of video analytics and topXview™ video management system provides many useful functionalities, such as: embedding detection metadata into recordings, alarm-based recording, list of most recent alarms, setting different alarm thresholds during different time periods, enabling/disabling alarm reporting during configured periods and many more.
Response plans based on incidents
If an incident is detected by XAID™ the user can automatically or on “one-click” control equipment on the road from topXview™ to warn the road users and obtain better situational awareness. E.g., PTZ cameras can automatically focus on the location of the incident and appropriate messages can be set on variable message signs.
Decision support system for traffic flow optimization
Many advanced traffic management functionalities, such as reversible lanes, unplanned lane closure management, dynamic shoulder running and similar utilize information about current traffic state to propose appropriate actions to operators. XAID™ can be used as an input to topXview™ decision support system which provides suggestions for traffic flow optimization and consequently manages equipment to inform travellers on how to use traffic lanes.
Monitoring traffic conditions
XAID™ can serve as a source for measuring Traffic Key Performance Indicators (TKPI), such as travel time, levels of service, presence of congestion, traffic density. Thanks to topXview™ built-in traffic network model TKPIs can be related to physical lane on a road segment. The TKPIs (e.g. travel time) can then be disseminated to users through different channels.
Improved focus on relevant information
Awareness of incidents’ location, location of equipment on the road and operator actions all influence the severity of information that needs to be presented to the operator. Is another detected stopped vehicle on a road segment on which warnings are already set to variable message signs more important than stopped vehicle on a road segment with no warnings at all?
Intelligent object search
Detected metadata (speed, class, alarm state, etc.) are stored in database for each object passing through the XAID™ detection area. The user can select time interval and apply different filters to obtain images of objects matching set filters within the specified timeframe.
3. Solved Problems of Traditional AVID
Working in direct light on the exit of the tunnel
Automatic Video Incident Detection is the fastest way to detect a traffic incident and, as such, exponentially increases awareness about traffic conditions, and traffic safety. Video detection systems require ideal working conditions (camera placement, constant illumination, environmental impacts, moving traffic), to reach ideal performance. In real life operation, ideal working conditions are not met. Traditional AVID systems are typically far from performance rates stated in their brochures (detection rate is typically <50% and false alarm rate is typically >5/camera/day). The main advantage of XAID™ system, comparing to traditional systems, is ability of learning (fine tuning) which is based on Artificial Intelligence and Machine Learning algorithms. Learning ability of XAID™ enables it to learn how to perform in real-life conditions and tune its performance as close as possible to theoretical. Traditional systems do not have learning capability. Technical specifications of video analytics systems describe operation and performance of the system in theoretical (ideal) conditions. In real applications, cameras are usually not ideally positioned, illumination is not ideal and environmental influences are expected (shadows, obstacles, etc). Because of these reasons, ideal performance of the system most likely cannot not be reached. Yet, XAID™ will reach much better performance than traditional systems, due to its fine tuning ability.
4. Connection Between AVID and Safety Management
With hundreds of cameras deployed throughout highways and tunnels delivering the immense amount of information simultaneously, it is impossible, even for a group of human operators, to monitor and evaluate the information effectively or efficiently. Reliable Video Automatic Incident Detection system is a must in such environments because it signiﬁcantly improves the efﬁciency of trafﬁc management systems. It automatically reports dangerous situations and irregular trafﬁc conditions, such as stopped vehicle, slow vehicle, driving in opposite direction, pedestrians in trafﬁc lanes, dropped cargo, ﬁre/smoke in a tunnel, or trafﬁc congestion.
Main constrains in Video Automatic Incident Detection industry is never ending trade-off between the need to have the least possible number of false alarms and still not to miss some of alarms that did occur on the road. Today’s traditional AID systems have come to dead end with technology currently being used.
XAID™, the new generation of AID has done a big step further and solves critical issues traditional AID systems can’t solve - unique and the most advanced algorithms based on cognitive recognition open path to the new reliability standard in video detection industry. Machine learning setup process enables fine tuning for the best fit to the particular scene and environmental condition, and experience-based improvement in reliability and accuracy.
5. Complete Platform for Video Surveillance and Video Analytics
XAID™ combined with particular topXview™ modules provides complete platform for video surveillance and video analytics
- Complete CCTV package: surveillance, real-time automatic incident detection and traffic statistics,
- Out-of-the-box integral solution eliminates integration challenges between separate video Automatic Incident Detection (AID) systems and video management systems,
- State of the art Video Management System (video layouts management, video players, video wall management, video recording and reviewing, PTZ controls, support for latest video standards),
- Industry’s proven and most precise Video Analytics System currently available on the market:
- Incident detection and vehicle classification / traffic statistics,
- Artificial Intelligence algorithms and Deep machine learning – provides highest detection rate and lowest false alarm rate without trade-offs between them (as in traditional systems),
- Expertise and transparency from the beginning (realistic execution schedule, realistic expected performance),
- Customizable alarm management,
- Automatic incident recording,
- Detection metadata natively overlayed over live and recorded video,
- Intelligent filters based on detection metadata for video summarization,
- Easy to interface with Traffic Management Systems, SCADA systems or other incident management systems - Restful API for exchange of incident data, NTCIP C2C, Advanced proprietary TCP interface,
- Optional incident management and decision support system.