Skip to main content

SICK launches all-weather 3D sensor system for traffic management

Sick has launched the TIC502 Lidar sensor traffic and warning system which is said to scan vehicles up to 100 times a second with 99% accuracy to generate a 3D profile of each vehicle. The all-weather solution can be used for counting fast lane, free-flowing and static traffic to facilitate real-time management and electronic toll charge assessment of all vehicle types according to standard international transport classifications. TIC502 has a range of up to 40 metres and minimum mounting height of 1.5
January 29, 2018 Read time: 2 mins

536 Sick has launched the TIC502 Lidar sensor traffic and warning system which is said to scan vehicles up to 100 times a second with 99% accuracy to generate a 3D profile of each vehicle. The all-weather solution can be used for counting fast lane, free-flowing and static traffic to facilitate real-time management and electronic toll charge assessment of all vehicle types according to standard international transport classifications.

TIC502 has a range of up to 40 metres and minimum mounting height of 1.5 metres above the tallest vehicle. It aims to provide a vehicle class assignment better than 98% and speed assessment accuracy is +/- 3kph up to 100kph, and +/- 3% above 100kph.

Vehicle class is measured according to TLS8+1, TLS5+1, TLS2+1 or Swiss10, into up to 30 different classes. The 3D view of traffic is integrated into a display and autocalibrated with moving traffic.

Additionally, the solution comes with a high all-weather capability between -40oC and +60oC and can also be combined with an additional 2D Lidar sensors to count axles for traffic profiling and assessment.

The traffic controller automatically stores a data history of the last 50 vehicles detected which is sent to storage in the user’s system via FTP or UNC transmission.

Neil Sandhu, SICK’s National product manager for imaging, measurement, ranging and systems, said: “The TIC502 generates 3D profiles and combines comprehensive and highly reliable data and warnings with excellent availability in all weather and all seasons. The unit can also be easily retrofitted on structures such as overhead gantries, bridges or tunnel entrances to upgrade existing traffic monitoring and control.

“The facility for adding an extra Lidar sensors to the TIC502 allows accurate axle counting, which is often used for improved toll assessment of very heavy transport vehicles, without needing the use of a full vision system.”

For more information on companies in this article

Related Content

  • Intersection management, cooperative infrastructures - what next?
    February 1, 2012
    What do recent vehicle recalls mean for future cooperative infrastructures? Anthony Smith takes a look. As ITS industry stakeholders converge on Amsterdam for the 2010 Cooperative Mobility Showcase, an unprecedentedly wide range of technologies will be on display demonstrating what might be achievable in the future from innovations based on Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications.
  • Autonomous vehicles will not prevent half of real-world crashes
    April 5, 2017
    Alan Thomas of CAVT looks at the reality behind the safety claims fuelling the drive towards autonomous vehicles
  • Kathrein boosts auto ID solutions and links up with Tönnjes
    March 20, 2018
    Kathrein Solutions says that its RRU4000 reader unit and ARU3000 antenna reader unit are the next generation family for all AutoID solutions. To meet all requirements of Industry 4.0, the systems have highly efficient integrated multicore industrial PC (iPC) to process applications, filter algorithms for data mining and business events directly on the device. The RRU 4000 series includes a flexible multiplexer to connect up to four external antennas. The ARU 3000 series includes an integrated 65°
  • Fully autonomous vehicles ‘spur LiDAR sensors mass adoption’
    January 26, 2017
    Cost-effective, high-resolution light detection and ranging (LiDAR) sensors capable of long-range object detection will be necessary for high to fully-automated driving applications. Demand for 3D mapping and imaging, better overall performance, automated processing of graphic data gathering and self-sufficient sensor with best-in-class performance in low-visibility conditions are factors driving the development and adoption of LiDAR sensors within the advanced driver assistance systems (ADAS) sensor suite