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.”

UTC

Related Content

  • October 29, 2014
    Xerox counts on machine vision for high occupancy enforcement
    Machine vision techniques can provide solutions to some of the traffic planners most enduring problems With a high proportion of cars being occupied by the driver alone, one of the easiest, most environmentally friendly and cheapest methods of reducing congestion is to encourage more people to travel in each vehicle. So to persuade people to share rides, high occupancy lanes were devised to prioritise vehicles with (typically) three of more people on board and in some areas these vehicles are exempt from
  • May 10, 2023
    Austrian Bike2CAV V2X project could mark turning point in cyclist safety
    Research in Salzburg into C-ITS equips bikes with V2X tech to allow detection via ITS-G5
  • May 18, 2018
    New ANPR solutions overcome variables
    The sheer range of variables makes it difficult to find a single algorithm to ensure a 100% standard of ANPR. David Crawford investigates new processing technology. Automatic number plate recognition (ANPR), using optical character recognition and image-processing to identify vehicles, plays key roles in traffic monitoring and law enforcement, access and parking control, electronic toll collection, vehicle security and crime deterrence. Overall, system performance is well rated, with high levels of
  • January 25, 2012
    Machine vision - cameras for intelligent traffic management
    For some, machine vision is the coming technology. For others, it’s already here. Although it remains a relative newcomer to the ITS sector, its effects look set to be profound and far-reaching. Encapsulating in just a few short words the distinguishing features of complex technologies and their operating concepts can sometimes be difficult. Often, it is the most subtle of nuances which are both the most important and yet also the most easily lost. Happily, in the case of machine vision this isn’t the case: