Two-way Green Wave Band Based on Traffic Big Data
2018.03.14
A green wave band is mainly built to avoid red lights on a given section of road, which reduces waiting time at intersection and ensure continuous flow of traffic. To improve travel efficiency and reduce vehicle wait time at intersections, the Shenzhen traffic police brigade and the Shenzhen traffic research center jointly built a two-way green wave band on a pilot road. This green wave band is 7.6 kilometers long and includes 12 signal control intersections. It is located on Guangqiao Road (Yutang to Huaxia Section 2), which is the main road in Guangming New District. In addition to the green wave band, Shenzhen traffic police brigade closely follows traffic flow at all intersections through electric police data and floating car big data at each surveillance spot. They also use simulation software supported by big data to carry out online simulations. The online simulations are combined with the embedded signal control algorithm to iteratively optimize the signal coordination parameters. To verify the operational performance of the green wave band, Shenzhen traffic police analyzed real-time data of vehicles, including average speed of vehicles on the road, delays of vehicles at intersections, and number of stops during the whole journey. Congestion on Guangqiao Road (Yutang-Huaxia Section Two) was significantly reduced after the two-way green wave band was built. Vehicles can pass almost directly through this section of road without having to wait at intersections, thus greatly reducing delays. Completed LOCATION Shenzhen City, Guangdong Province, China OWNER/IMPLEMENTATION UNIT Shenzhen Traffic Police Brigade KEY WORDS Smart transportation;traffic big data;online simulation based on big data;green wave band PROJECT COMPLETION/EXPECTED COMPLETION DATE July 2017 CASE DESCRIPTION KEY DATA PROJECT-RELATED PARTIES CURRENT PROGRESS INNOVATION POINT The green wave band applied transit-related big data to optimize traffic light signals and successfully reduced congestion and delays. RELATED LINKS