Position Statement on Application of Traffic Intelligent Twins For Safer & Resilient Urban Transport
Submitted by Kshitij Naik, Associate Editor, The Indian Learning, Manohar Samal, Research Intern and Ruhi Tyagi, Honorary Research Member.
Huawei Cloud has had over 200 projects across eight industries which includes manufacturing, logistics and the Internet. With TrafficGo, they not only had incorporated technology with rather colossal real-time data but significantly improved the travel experience for all.
The Traffic Intelligent Twins (TrafficGo) system developed by Huawei is an inclusive artificial intelligence system that aims to create a safe, resilient and energy-efficient urban transportation system. The TrafficGo system encompasses a plethora of features that include traffic prediction, traffic light optimisation, traffic parameter awareness, road network analysis, accident monitoring and accident control.
The feature of traffic prediction enables the system to accurately pinpoint the flow of pedestrians and congestion of vehicle traffic using a multitude of data sources. Traffic light optimisation integrates and compiles data from a wide variety of sources to ensure traffic light management and coordination around the clock. Furthermore, it enables real-time optimization and is compatible with mainstream traffic signal systems. The feature of traffic parameter awareness ensures awareness of more than 10 types of traffic parameters involving motor vehicles, non-motorised vehicles and pedestrians. Few more sub-features of traffic parameter awareness includes traffic optimisation effect comparison, traffic index ranking and real-time display of geographical information system (GIS).
The road network analysis feature collects and analyses information on busy roads and intersections that enables the TrafficGo system to provide efficacious suggestions to optimise the flow of traffic. The accident monitoring and accident control feature in the system indulges in real-time monitoring and notifying heavy congestions, traffic violations, traffic emergencies, trajectories and behaviour of passenger buses, tourist coaches, commercial trucks, taxis, school buses, other vehicle types and is also employed for monitoring and notifying other related urban transport incidents.
The Traffic Intelligent Twins (TrafficGo) system has truly transformed the urban transport system of the cities where it has been implemented. Earlier, traffic was manually governed but these systems have enabled intelligent transport governance to replace it. This is possible due to the artificial intelligence technology of the system which refines traffic management by using real-time traffic flow and the integration of personnel experience in artificial intelligence. The authorities are capable of controlling and optimising a single intersection independently and as well as capable of controlling and coordinating between multiple intersections using the system. The system integrates traffic lights to a network which unifies traffic light management and increases the energy efficiency of the unified traffic lights system.
The TrafficGo systems have been implemented in the cities of Shenzhen and Beijing in China. After its implementation in these cities, average delays on one of the busiest streets of Beijing were reduced by 25.2% and the delay in nearby streets were reduced by 10% to 20%. Success in the city of Shenzhen was also seen as the utilisation of the system led to the coordinated optimisation of traffic signals at many intersections that pivotally reduced delay time and proved to be more efficient than the earlier manual system used in the city.
Few of the concrete technical benefits of utilising this system in cities are deep data mining, district-wide coordination, real-time traffic signal scheduling, precise planning and precise tracking. The system deepens data mining efforts by integrating the internet with big data for the purposes of traffic control, minimises vehicle wait time, coordinates the requirements of vehicles and pedestrians resulting in smooth traffic and accurately predicts and plans routes and trajectories in advance.
Therefore, it would not be wrong to infer that its application in two of these cities have proved to be useful and its utilisation in other major cities of the world will lead in the improvement in safety and energy efficiency of urban transport infrastructure systems. Also, the energy-saving technologies are going to be more potentially incorporated in the world markets and if it comes to road safety no government is going to step back from utilising it.
But while we introduce such systems in other Major systems around the world we need to give Data Privacy the highest priority, also such cyber attacks on such systems could have a catastrophic effect if the Cybercriminals are able to train the System in a way it is not supposed to function, we may also need to take all these factors into consideration. while we implement such artificially intelligent algorithm-based systems.
If criminals intercept into such systems, they might be able to track certain important vehicles like cash vans, oil tankers or follow and keep checks on a celebrated personality for their personal benefits. Thus, safety comes hand in hand with technology which has to be simultaneously developed.
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