| |April 20189CIOReviewwider use of all lane running on motorways and the ef-ficient planning of road works.The best starting point to implement an ITS is with collecting data and running algorithms with it to find out the source of the current problem and forecasting what will happen next. If we know what can be the pos-sible areas of bottlenecks in the next few hours, the traf-fic management system can be pressed into action to avoid the gridlocks. Longer range forecasting will help policymakers and transportation professionals to know when and where congestion is worst, to prioritize investments with lim-ited budgets. Scientists at Nanyang Technological Uni-versity in Singapore have developed a new intelligent routing algorithm that attempts to minimize the occur-rence of spontaneous traffic jams. A team from the Texas Advanced Computing Center (TACC), has demonstrated that AI can help to optimize traffic flow. Their work is on developing searchable traf-fic analyses using deep learning and data mining. The tool uses the raw data generated from traffic cameras, with their algorithm capable of recognizing the various objects in the footage and then characterizing how those objects move and interact. This information can then be queried by traffic planners to better understand the transport network.The system automatically tags each object it encoun-ters in the raw data and then tracks their movements throughout the footage. By comparing outputs from each frame, the algorithm discovers relationships among the objects. The system was tested in two practical use cases. The first saw it count the number of vehicles trave-ling down a road while the second identified near-misses between vehicles and pedestrians. The results showed that the algorithm was around 95% accurate when counting the vehicles.According to a McKinsey report, Artificial Intelli-gence and Machine Learning will be the technological foundation for both ITS and autonomous vehicles. The convergence of Internet of Things in connected cars, autonomous vehicles, and sensor-based traffic manage-ment systems will become a reality with the launch of 5G. One of the key advantages of 5G is low latency which will help autonomous vehicles to respond in real time to dynamic situations.The lower latency and high throughput of 5G will support connected cars, transportation, and retail lo-gistics that consist of fleets of connected/driverless ve-hicles transporting people and goods. The key network requirements for mission-critical automotive driving are high throughput and low latency up to 100 milli-seconds. A journey from A to B in a driverless vehicle could involve vehicle-to-vehicle connections, connec-tions between vehicles and street infrastructure for traf-fic management, and high-speed reliable connectivity to support cloud applications which will be made possible by 5G. Failure is not an option in these cases.These technological advancements are making pos-sible improved transport. The governments across the globe are also taking initiatives to focus on research of cutting-edge technology related to advanced products such as vehicle ad hoc networks. These major trends are poised to fuel the growth of the global market for intel-ligent transport systems which according to estimates is likely to cross $30 billion by 2022. The lower latency and high throughput of 5G will support connected cars, transportation, and retail logistics that consist of fleets of connected/driverless vehicles transporting people and goods Amitabh Ray
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