Spending 900 days of traffic jam artificial intelligence for a lifetime

People living in big cities face the same most annoying thing every day. They are afraid of traffic jams, blocked on the road, late for work; they can’t be punctual when they go to work; they are upset. According to the 2016 data, the average daily traffic jam in Beijing is about 3 hours. Calculated in this way, it is equivalent to 30 days of traffic jams a year. You must know that there are 10 days of legal holidays in a year. According to the 30-year driving time in a lifetime, it is equivalent to 900 days of time spent on traffic jams. When can I have a solution?

On March 23, at the forum of “Artificial Intelligence + Traffic: Awakening Sleeping Data, Making Cities Smarter”, Ma Xiaolong, a signal control expert from Hisense, gave a solution based on artificial intelligence technology. Through the deep learning model, the data brain is the core, real-time monitoring and analysis of road traffic, according to dynamic traffic data, automatic switching and deployment of signal time, the most intuitive change is that the traffic time is no longer fixed, or even the entire green light does not stop.

The “Data Cube” developed by Hisense enables traffic prediction based on deep learning, and can complete the visual analysis of 1 billion large-scale traffic big data within 30 seconds, achieving an industry breakthrough. Ma Xiaolong explained, “General cities generate tens of millions of massive traffic data every day, but how to use these data is a problem for city managers. Now, with this technology, big data reflects the traffic problems. Quickly solved."

For example, in the past, for traffic jams, it was often more than ten minutes after the congestion occurred. The traffic police received the alarm and then deployed police to the scene. Not only is the reaction process long, but it is also prone to increased congestion and potential safety incidents. Hisense established a traffic prediction based on deep learning. “Based on massive traffic data, it analyzes the regularity and similarity of traffic operations, establishes an intelligent learning model, predicts traffic parameters such as traffic through deep learning, and predicts congestion areas, etc.” Ma Xiaolong In this way, it is possible to predict the congestion area and time, and plan the deployment, signal deployment, information dissemination, and police deployment in advance.

Yan Sangang, general manager of Hisense's Smart City Division, said that these seemingly nascent artificial intelligences have been put into use in the transportation sector. He said: "Using big data and artificial intelligence technology in urban management and people's livelihood services, let data help cities to think and make decisions, and build smart cities that can self-regulate and interact with humans."

At present, Hisense and Beijing have already carried out relevant cooperation on urban transportation operation and maintenance services, and look forward to achieving overall construction through joint planning. Hisense said that world-class technologies and solutions such as traffic big data technology and advanced brain signal control systems based on data brains, if systematically used in Beijing, planning and overall construction, Hisense has the confidence to slow down traffic congestion in Beijing.

Yan Sangang, general manager of Hisense Network Technology's Smart City Business Unit, said that although China's IT operation and maintenance has developed rapidly in recent years, compared with mature markets in Europe and America, China's IT operation and maintenance is still in its infancy, and there is widespread “heavy construction and light transportation”. The phenomenon of "dimensionality." In Beijing's urban transportation operation and maintenance project, Hisense will carry out traffic signal timing adjustment and control scheme design work, and use the Hisense Yunwei cloud platform to automatically diagnose common faults of 19 categories of equipment, with equipment coverage reaching 90%. The above will effectively improve the usability of the device and improve the system application effect.

It is worth mentioning that since the 2008 Beijing Digital Olympics Intelligent Transportation Project, Hisense has continued to cooperate with Beijing in the field of signal control and rapid transit.

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