First UK trial of Siemens cloud-based traffic management

Siemens Stratos journey time application is undergoing its first UK trial with South Gloucestershire Council. The council is trialling the system using data from a network of automatic number plate (ANPR) cameras to monitor the reliability of traffic times on key corridors and provide a baseline for measuring the impact of network strategies and improvements. Developed using the latest cloud-based technology, Siemens says Stratos delivers scalable real-time traffic management, information and control; fr
October 9, 2013 Read time: 2 mins
189 Siemens Stratos journey time application is undergoing its first UK trial with South Gloucestershire Council. The council is trialling the system using data from a network of automatic number plate (ANPR) cameras to monitor the reliability of traffic times on key corridors and provide a baseline for measuring the impact of network strategies and improvements.

Developed using the latest cloud-based technology, Siemens says Stratos delivers scalable real-time traffic management, information and control; from basic monitoring to strategic control of complex urban traffic environments. As a hosted solution, it offers high levels of availability, accessibility and support, in a cost effective manner and with the minimum of IT investment.

Stratos uses ANPR or Bluetooth data to calculate journey times and includes a data fusion algorithm developed by Siemens in conjunction with the Transportation Research Group at the University of Southampton. It offers flexible deployment options and browser based user interfaces with easy workflows to address individual customer requirements.
Detection, Monitoring & Machine Vision Networking & Communication Systems Urban Traffic Control

Related Content

  • June 8, 2016
    Transport Ministers call for clarity on NOx emissions, UK begins research project
    On 7 June, EU Transport Ministers debated on the best way to cut NOx emissions from diesel cars in the wake of the VW scandal. They reflected on possible ways to improve existing legislation to avoid illegal use of defeat devices and explored what technical solutions could already minimise emissions. The Dutch Presidency encouraged Member States to share the findings of their enquiries with other. The proposal to update Euro 5 legislation on the use of defeat devices would have increased uncertainties, rath
    Read More
  • April 10, 2015
    Rennicks launches Bluetooth traffic monitoring at Traffex
    Rennicks UK, in conjunction with Bluetrace, is using Traffex 2015 to launch a new traffic management system which it says is a significant leap forward in the battle to improve safety and reduce congestion. The system, developed in conjunction with Bluetrace, uses the most sensitive Bluetooth and wi-fi technology on the market to monitor and measure traffic movement from the roadside by connecting to devices inside vehicles. The data is transmitted to a central location to present a clear, real-time p
    Read More
  • September 24, 2013
    Highways Agency trials new traffic monitoring technology
    The UK Highways Agency is trialling a system to add commercially available traffic data to its existing sources to monitor traffic flow on England’s motorways and strategic roads. Similar data sources are already used by satellite navigation devices, smartphones, and applications like Google maps. The system uses data that comes mostly from vehicle tracking devices installed by fleet operators, and a proportion from mobile sat-nav type devices, including smartphone traffic applications where the user has
    Read More
  • 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:
    Read More

Highlighted Content