Skip to main content

Siemens to automate New York’s Queens Boulevard subway

Siemens has been awarded a US$156 million contract by the Metropolitan Transportation Authority (MTA) to install communications-based train control (CBTC) on the Queens Boulevard Line, one of the busiest subway lines on the New York City transit system. Siemens is supplying the onboard equipment for a total of 305 trains and installing the wayside signalling technology at seven of eight field locations.
August 28, 2015 Read time: 2 mins

189 Siemens has been awarded a US$156 million contract by the Metropolitan Transportation Authority (MTA) to install communications-based train control (CBTC) on the Queens Boulevard Line, one of the busiest subway lines on the New York City transit system.

Siemens is supplying the onboard equipment for a total of 305 trains and installing the wayside signalling technology at seven of eight field locations.

The radio-based CBTC technology provides real-time data on vehicle position and speed conditions, allowing system operators to safely increase the number of vehicles on a rail line. This results in greater frequency of train arrivals and allows MTA to accommodate more passengers on its system. The technology reduces the amount of wayside equipment and, as a result, reduces maintenance costs and service disruptions. Additionally, the technology precisely locates each train on the tracks and controls speed, improving on-time performance for riders and employees.

The system will be managed and deployed by Siemens New York City based rail automation team of CBTC experts which has been working with NYCT for over 15 years.

“Through our work on the Canarsie line, we’ve seen first-hand that CBTC technology can have a significant positive impact on ridership for the New York City subway system,” said John Paljug, head of Siemens Rail Automation. “We’re extremely excited to extend our technology partnership with the MTA and bring advanced automation technology to riders on the Queens Boulevard line.”

Development work is expected to begin on the Queens Boulevard line late this summer with the major installation beginning in mid-2017.

For more information on companies in this article

Related Content

  • Network Rail opts for Thales’ TMS
    May 30, 2014
    Thales is to provide the UK’s Network Rail with its Aramis traffic management system (TMS) at two new Regional Operating Centres (ROCs) in Romford and Cardiff. This will be the first time that the internationally proven TMS technology has been deployed in the UK, and is part of Network Rail’s significant investment targeted at improving rail network performance and capacity. When rolled out nationally, TMS technology will help Network Rail integrate, operate and manage the UK rail network through twelve
  • Enforcement comes in many guises
    June 22, 2016
    Colin Sowman looks at some enforcement case studies from around the world. It is a sad fact of life that unenforced laws are not adhered to by a sometimes sizable proportion of the public and once enforcement is seen to be lacking, some drivers can take this to extremes and authorities must decide how to regain control.
  • Civil engineers find fuel savings where the rubber meets the road
    May 23, 2012
    A new study by civil engineers at MIT shows that using stiffer pavements on America’s roads could reduce vehicle fuel consumption by as much as three per cent, that could add up to 273 million barrels of crude oil per year, or US$15.6 billion at today’s oil prices. This would result in an accompanying annual decrease in CO2 emissions of 46.5 million metric tons.
  • Coach crash-prevention system tracks drivers' eyes
    December 11, 2013
    Australian facial tracking systems developer Seeing Machines has teamed up with European coach and tour operator Royal Beuk, in a deal that will see the deployment of automated fatigue monitoring systems to ensure driver alertness and safeguard coach passengers. The Seeing Machines fatigue monitoring system is based on patented eye-tracking technology that can detect if a driver is distracted or falling asleep at the wheel. Using sensing equipment that requires no re-calibration between different drive