NTT DATAs Big Data Simulation Forecasts and Alleviates Traffic Congestion

— Field Study in Guiyang, China Achieves Smoother Traffic Flow —

Jun. 8, 2016

NTT DATA Corporation

Tokyo, June 8, 2016 - NTT DATA Corporation, a global IT services provider, announced today that it has successfully used big data traffic simulation technology to forecast traffic congestion and develop solutions for more effective control of traffic signals. This was proved to help alleviate traffic congestion and shorten journey times in a field study conducted by NTT DATA and the Institute of Software, Chinese Academy of Sciences (“ISCAS”) in Guiyang, Guizhou Province, China, analyzing data collected between February 22 and March 6, 2016. ISCAS is an institute established by the Chinese Academy of Sciences, the national academy for the natural sciences in the People’s Republic of China.

NTT DATA has been developing big data technologies for use in traffic forecasts and for the effective control of traffic signals since 2011. The field study in Guiyang followed the successful completion of a similar big data traffic simulation trial in Jilin, Jilin Province in 2014, in which the company used GPS-equipped public buses to collect traffic data.

The field study was conducted in the Guanshanhu District, located northwest of the city center of Guiyang, an area suffering from severe traffic congestion. Guiyang has implemented various transportation management and control measures that utilize traffic monitoring cameras and networked traffic signals. For its simulations, NTT DATA used data collected from 100 monitoring cameras installed at 12 intersections, capturing the movements of 1 million vehicles.

After conducting traffic simulations and determining optimized signal settings, the results were tested in real life using 100 traffic signals at the 12 intersections. During the test, vehicles passing the intersections were identified by their license plates. It was found that the time it took the vehicles to traverse the intersections was cut 10% on average and by a maximum of 51%. The average number of vehicles passing the intersections in a given time increased by 34%.

Figure

Traffic congestion and monitoring cameras in Guanshanhu District

Figure

Linkage between monitoring cameras and traffic simulation

Figure

Target areas and test results

Following the favorable results of the test, Guiyang is continuing to use NTT DATA’s solution for traffic control. Moving forward, the city aims to expand the number of intersections and accumulate more traffic data using GPS-equipped taxis. Another field study is planned for this summer.

“We are very glad to have helped Guiyang tackle traffic congestion with the aid of our big data technology,” said Mr. Hiroyuki Kazama, Head of the Evolutional IT center for NTT DATA. “Based on the increasing interest in smart-city projects, we believe that our big data technology has enormous potential for practical application.”

NTT DATA aims to realize a fully automated traffic control system by linking the analysis of data from monitoring cameras to the control of the traffic signals on a real time basis. It also plans to deploy big data technologies for traffic simulation and control in large-scale smart-city projects around the world. NTT DATA expects to generate more than 10 billion yen in cumulative business revenue by 2020.

About NTT DATA

NTT DATA is a leading IT services provider and global innovation partner headquartered in Tokyo, with business operations in over 40 countries. Our emphasis is on long-term commitment, combining global reach with local intimacy to provide premier professional services varying from consulting and systems development to outsourcing. For more information, visit www.nttdata.com.

For more information, please contact:

Media inquiries:

Ayumi Matsubara
Weber Shandwick
Tel: +81-90-9006-5841
E-mail: nttdata@webershandwick.com

News Releases.

The services, prices of products and services, specifications, telephone numbers, etc. for inquiries and other information included in news releases are the data available on the day of the release. This information may be changed at any time without notice. In certain circumstances, due to various risks or unexpected occurrences, actual results may also be different from the plans or projections in news releases.

What are you looking for?search