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How data visualization helps with traffic management

How data visualization helps with traffic management
Transportation issues are a source of headache for both city residents and administrators alike. When traveling to a particular section of the city or getting back home after work, there is nothing more bothersome than being stuck in traffic for a long time. Intelligent transportation systems (ITS), therefore, have become a popular topic in metropolises across the globe. Data, and the way it’s presented, becomes critical in this regard.
That was the point raised by Luciad, a developer of data visualization tools that have various applications, including smart transportation.
According to Frédéric Houbie, Senior Product Manager at Luciad, ITS has gained importance in different parts of the world to solve traffic congestion, parking difficulties and other related issues that affect city residents’ quality of life.
Europe, for example, sees lots of transportation challenges which can be addressed by ITS solutions, he said. “In Europe, on the country level, the main issue is traffic on the highways. When you have toll payment systems, and if it's not automatic, it means there's a lot of traffic jams. Sometimes during the day you can wait half an hour before being able to pay,” Houbie said. “In Europe there’s a lot of research topics and developments in ITS. The goal is to increase the quality of life for commuters by lowering traffic and improving traffic flow.”
According to him, data generated by various sources are key in smart traffic management, whereby administrators are helped by data analytics and visualization tools to make informed decisions. That’s where Luciad’s solution comes in. “We can help visualize many different data, for example traffic flow, accidents or works in roads. This allows for what we call common picture of the status of the city. Our software helps to deal with all those data and helps the operator to make the right decision,” he said.

Sources of data

The data can be obtained from different sources for example geo locations, smart city relates systems, sensors, cameras, IoT platforms and even weather centers. Once the data is acquired it is visualized to the operator who can then decide what to do. “It is able to visualize the same information with different representations, so it could be on a map, it could be on a timeline, or it could be a list of alarms or events,” Houbie said. “When something happens an alarm is raised, which can be a blinking point on a map. The user can click on it and can see the video at the time. And then they can make the right decision, for example sending a repairman because there was a problem with the traffic light, which led to the congestion.”
One case study that Houbie cited was taxi in New York City, where taxi rides total approximately 170 million a year. It was expected that many of those rides could be replaced with a single ride on the subway to reduce traffic and even benefit customers who can get to their destinations faster and cheaper. Using LuciadLightspeed, the taxi trips, with information on pickup and drop-off location and the fare, were analyzed and compared with the subway lines and station. Various analysis were applied like spatial filtering, distance measurement and heat maps to pinpoint in which areas commuters would be better off to take the subway. NYC transportation authority can now target these locations with campaigns to make better use of public transportation.
Luciad is also now studying the prospects of including machine learning algorithms in their solution so that the system can predict traffic patterns based on historic data, Houbie said.

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