Sick takes the high road for complex traffic management

Sick is taking advantage of Traffex to launch its TIC102 laser measurement system at Traffex 2013, part of the company’s growing portfolio of vehicle and traffic management solutions in the UK, Following the acquisition of the Swiss-based company ECTN. The TIC102 offers real time vehicle profiling and classification for multi-lane, free flowing or stop-go traffic. As well as providing collection data for tolls, it can be used for monitoring vehicle speed, vehicle dimensions and vehicle intervals, even with
April 16, 2013 Read time: 2 mins
536 Sick is taking advantage of 136 Traffex to launch its TIC102 laser measurement system at Traffex 2013, part of the company’s growing portfolio of vehicle and traffic management solutions in the UK, Following the acquisition of the Swiss-based company 535 ECTN.

The TIC102 offers real time vehicle profiling and classification for multi-lane, free flowing or stop-go traffic. As well as providing collection data for tolls, it can be used for monitoring vehicle speed, vehicle dimensions and vehicle intervals, even with rapid lane changing behaviour.

“The TIC102 is based on high-performance SICK lasers to ensure reliable vehicle detection even at night and in bad weather,” comments Gary Young, Sick UK traffic management segment manager. “It was developed by Sick subsidiary ECTN, and has been successfully proven on autoroutes across Europe, where it provides highways authorities with a wealth of safety and revenue information, especially for tolls, tunnels, rail crossings and bridges.”

The TIC102 is designed to be gantry- or bridge-mounted, with up to three slave sensors and one processor sensor unit, covering four lanes. In addition to its own data collection, the device can be used as a trigger for DSRC (dedicated short range radio communications) and automatic number plate recognition cameras, and so can be integrated with a number of different traffic management systems.
.
The TIC102’s live 3D view of traffic is integrated into one, easy-to-use display, and is simple to install and configure, auto-calibrating with moving traffic. Remote access allows easy maintenance, and as the processor stores data independently, it can also be used for temporary traffic data collection, such as with road lane closures and speed restrictions.
Urban Traffic Control

For more information on companies in this article

Related Content

  • Theia’s compact 4K telephoto lenses
    May 1, 2022
    Portfolio is particularly good in NIR illumination with only a five micron focus shift
    Read More
  • Wireless - the future of vehicle detection
    July 23, 2012
    Peter Cattell of Clearview Traffic analyses different wireless communications methods and explains how these are changing the face of vehicle detection. With the continued expansion of traffic data collection solutions, providing a robust, reliable, scalable and secure method of collecting information becomes increasingly important. Over many years, various mobile wireless technologies have been utilised to make the remote collection of data a reality but recent developments are changing the way that this w
    Read More
  • Sensor solutions cuts maintenance and emissions
    December 8, 2014
    The new raft of sensor technology can provide cost savings as well as additional functionality, as David Crawford discovers. Austria’s third-largest city, Linz, with a population of around 200,000, is recording substantial savings in its urban tram network within 18 months of introducing a new, high-technology approach to its public transport management. Tram, bus and trolleybus operator Linz Linien forms part of city utilities management company Linz AG, which has been carrying out a wide-ranging Smart Cit
    Read More
  • IRD trusts in AI for traffic count and classification
    October 13, 2020
    IRD has announced its iTheia video-based traffic counting and classifying system that uses artificial intelligence (AI). Instead of classifying vehicles based solely on axle spacing or vehicle length parameters, iTheia classes vehicles based on visual input and a machine learning algorithm.
    Read More

Highlighted Content