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Pictures of the Future



Mr. Sebastian Webel
Mr. Sebastian Webel


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Werner-von-Siemens-Straße 1
80333 Munich

Pictures of the Future
The Magazine for Research and Innovation

Urban Mobility

An App that Could Cut Gridlock

Not only are chronic traffic jams a challenge for Wuhan’s police; they are also a daily headache for thousands of the megacity’s motorists.

The traffic situation in Wuhan, China, can only be described as chaotic — and that’s not a good basis for automatic traffic management in a megacity. Together with municipal authorities, Siemens Corporate Technology came up with a brilliant idea: incorporating the police force into the system.

It’s the 8 a.m. rush hour in Wuhan. At the intersection of Luoyu Road and Zhongnan Road, cars are lined up for hundreds of meters, as they are every morning. Hanzhong Zhang, the traffic policemen who is responsible for this intersection, uses his walki-talkie to call his colleague, who is managing the next intersection over. After a brief discussion, Zhang reaches for the last resort. It’s a gray box on the roadside, with a Siemens logo that can be seen faintly through a thick layer of dust. Zhang opens a flap on the box and presses several buttons. The traffic signals for the cars turning out from Zhongnan Road suddenly turn red. The traffic jam on Luoyu Road becomes a bit shorter, but there’s still not a smooth flow of traffic by any means. The chaos doesn’t begin to calm down until after 9 a.m., when pedestrians have a slightly better chance of crossing the intersection in one piece.

The traffic in Wuhan is nightmarish. In this city of ten million, it has increased dramatically in recent years. At the behest of the city, Siemens installed an Urban Traffic Control System in 2007. The system encompassed traffic controllers at more than 400 intersections — about two thirds of the city’s major traffic hubs. The controllers automatically switch the traffic lights on and off. By now it is obvious that this automatic system can no longer manage the traffic flow during rush hours, because it is based on the assumption that drivers will behave in a predictable way. However, that’s an illusion. When traffic jams keep lengthening and drivers have to wait longer than they like, even red traffic lights are not an obstacle. In case of doubt, the boldest driver wins. At that point, Mr. Zhang has to intervene. He uses the buttons in the controller box to control the traffic lights manually.

By integrating the knowledge of policemen, the system deals more flexibly with the uncertainties of traffic.

Authority Versus Automatic Systems

Automatic systems versus authority — that used to be a strictly either/or situation. If a policeman switches over to manual control, valuable information about the traffic situation is lost. That’s because Mr. Zhang can only see what’s happening at his intersection. He doesn’t have an overview of the traffic situation on the access roads, which in some cases is measured by means of induction loops. The challenge now is to create a solution that combines the advantages of both systems.

Two years ago, Wei Qiu, a Technical Manager at Siemens Corporate Technology in China, decided to tackle this challenge. In a workshop structured according to the principles of Industrial Design Thinking, he worked with members of the police force and the city administration of Wuhan to find out the customer’s needs. That included the needs of the city’s police force, the traffic authority, and the urban planning bureau. Research activities included a survey of Wuhan’s policemen and taxi drivers. The result was a concept that is simple and yet revolutionary: equipping the traffic policemen who work at troublesome intersections with a smartphone app. The app serves as an information terminal that calculates traffic density on the basis of data from the Traffic Control System. In addition, during rush hours the app enables users to remotely operate the traffic lights manually. As a result, Mr. Zhang doesn’t have to stand on the roadside behind the controller box in order to direct traffic. Instead, he can be an imposing presence on one of the traffic islands in the middle of the intersection.

With a population of over eight million, Wuhan is one of China's biggest cities.

Turning Taxis into Congestion Sensors

Siemens set up an Innovation Center in a suburb of Wuhan in May 2013. The center is a branch of Siemens Corporate Technology that works closely with local authorities in order to develop an infrastructure for data services for future mobility management. At the center, several researchers are working on the implementation of the app concept. Yi Liu, one of the researchers, demonstrates on a tablet computer exactly what the app could look like. On a map of the intersection, red and green arrows show which cars have the right of way and which ones don’t — if all of the drivers obey the rules. It also shows the length of the line of cars waiting for a green light. This information comes from induction loops embedded in the asphalt and from Siemens controller boxes. But the most valuable data Siemens receives comes from the city’s traffic authority: information about the speed of almost all of the city’s 20,000 taxis. The taxis send their GPS position data via mobile radio to a platform run by the traffic authority, and Siemens then receives information about the average speeds of the taxis. That yields a good overview of the traffic flow throughout the city. Plans call for the app to be ready for use at the end of 2015. At that point, the first group of policemen will be equipped with smartphones and the app.

At the Siemens Innovation Center in Wuhan, several researchers are working on the implementation of the app concept.

The concept still has to overcome a number of obstacles. For one thing, even an induction loop doesn’t know where a traffic jam ends. That’s partly because drivers are constantly changing lanes — an activity that is almost a national sport in China. If the app is really to provide policemen with a better basis for making decisions about manual interventions, far more data will have to be fed into the system. This data could come from cameras mounted on traffic light masts facing oncoming cars, or from radar speed monitors, or from magnetic sensors that are much cheaper and more robust than induction loops and send their signals via radio to controllers.

Please Start Your Engines!

The Siemens concept is based on a “bottom-up” philosophy.  Data from roadside controllers is processed with Siemens algorithms and then made available to policemen, the traffic authority, and the urban planning bureau by means of a Smart Data Service Gateway. These recipients then derive their own services from the data. One possible service would involve using the Gateway to send a message to the smartphones of waiting drivers to tell them to start their engines just before the traffic light turns green.

On the drive back from the Innovation Center, Technical Manager Qiu stops his car next to a traffic light controller that bears the name of a competing company. These controllers are cheaper than the ones from Siemens, but they aren’t networked; as a result, they’re not suitable for managing the traffic of the future. According to Qiu, the Smart Data Service Gateway expands the scope of competition by adding a data service dimension, and that gives Siemens an advantage. “By integrating the knowledge of policemen, our system deals more flexibly with the uncertainties of traffic,” he says. Automatic systems where it makes sense to use them, plus authority where it’s needed — it could add up to a little less gridlock for many Wuhan motorists.

Bernd Müller