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How can AI decongest crowded Dhaka streets?

Published : Wednesday, 15 May, 2024 at 12:00 AM  Count : 520
Sajeeb Hasan Joy
With a population of more than 21 million, Dhaka is among the cities in the world that is expanding at the fastest rate. The citys explosive growth has brought forth several issues, one of which is traffic congestion, which is now a momentous challenge for both locals and commuters. The severity of Dhakas traffic issue and the impairment it causes to the environment, public health, and economy of the city are well-known.

About 17.8 lakh registered automobiles are speeding through less than 7% of the city that is made up of roads. Daredevils zigzagging on approximately nine lakh motorbikes avoid these, which include over three lakh private cars, one lakh vans, eight4,000+ microbuses, 78,000 trucks, 37,000 buses, 30,000 taxicabs, and thousands of other vehicles like taxicabs, covered vans, human haulers, tempos, jeeps, tractors, auto-rickshaws, nations, and so on. Amidst all of this are the sluggish rickshaw vans transporting anything from furniture to trash, and the thousands of rickshaws pulled by carefree pullers who dare to race against private vehicles by making abrupt turns on the busiest roadways. For this extensive problem of traffic jams, Artificial intelligence can be the finest solution in the country.

Artificial intelligence is expeditiously transforming the world around us, and smart city technology such as parking management systems and traffic control systems, is one of the most impressive answers it offers. AI can be used to reliably predict the flow of people, vehicles, and objects at different sites in interconnected transportation networks. Cutting-edge technology like artificial intelligence can optimize traffic flow for both citizens and cars, diverting construction-related traffic on existing routers and conducive to a downturn in accident rates. By exhausting real-time hinting to law enforcement, you can identify traffic accidents or fights and alert them. Furthermore, ride-sharing firms can benefit from this adroit automation to grasp more about their passengers. Lets pore over how artificial intelligence is converting traffic control systems in the piece that follows.

Traditionally, government officials and officers would manually monitor and rectify traffic management systems. However, with the expansion of artificial intelligence and machine learning, these systems are progressively becoming automated. Real-time traffic data from several cameras and Internet of Things (IoT) devices, including automobiles, buses, and even trains, is analyzed by AI to lower asylum risks and recurrent accidents, find patterns in the data, and manage traffic light systems.

Sensors like radar, cameras, and lasers are used in Automatic Distance Recognition (ADR) to determine how far away an automobile is from nearby objects. One of the guiding ideas of autonomous cars is this. Because ADR can be used to control speed, engage automatic braking, and put an end to traffic slowing down all at once, it helps prevent accidents. This will therefore enable us to create more effective infrastructure and roadways.

During major events like concerts, drivers can save time and avoid traffic congestion by using artificial intelligence to identify potentially congested regions ahead of time. This will make it easier for event organizers to collaborate with local authorities to find more adaptable parking choices nearby. Urban planners can make more informed decisions based on data and enhance the overall experience for all parties involved when circumstances may be adjusted in real time.

We can find and employ effective, sustainable, and financially feasible routers to assist us get to our goals with the use of AI-powered route planning in cities and nations. In the long term, this will assist us in enhancing supply chain management while addressing intricate distribution issues. Additionally, it can assist us in enhancing smart city emergency management.

As part of traffic management, offenders are automatically penalized under the law, supported by evidentiary data in photos and videos. The user is alerted when numerous people are riding bikes or motorbikes without helmets thanks to AIs ability to detect speed infractions. This keeps those two forms of transportation and other motorized vehicles out of accidents. Integrating the system with CCTV and traffic control systems can also result in a comprehensive response to the current traffic threat. Traffic can be decreased using a deep learning-trained AI-powered system. Based on system updates, travellers can arrange their itineraries. Road authorities and drivers will always be one step ahead thanks to an AI-powered system that considers every minute feature of the roads.

To facilitate traffic movements, the system has sufficient accuracy in analyzing traffic in various lanes. Drivers can cut their travel time greatly by using the data. To avoid traffic congestion, drivers and road authorities can make better decisions. Every important information regarding traffic conditions, including congestion and accidents, gives road authorities and drivers an advantage. A system driven by AI could be able to analyze traffic across several regions. To enhance traffic conditions, you can map the most effective routes and modify traffic signals.

Algorithms using artificial intelligence and machine learning can recognize less efficient cars, follow their path and speed, and alter traffic signals in front of them. This reduces fuel usage and gets rid of a lot of the inefficient starting and stopping at junctions.

The traffic system in Sweden is among the best in the world. The Swedish Transport Administration is working with computer vision and machine learning specialist Universe to help optimize the countrys infrastructure using 3DAI City, an AI program developed by Univrses, to contribute to the creation of a more secure, sustainable, and effective transportation network.

Every year, Trafikverket utilizes specialized measuring trucks to assess the quality of state-owned roads. Nonetheless, the administration is aware of the growing need for more effective road network monitoring and maintenance due to Swedens extensive population growth and urbanization. In response to this need, Trafikverketand Univrses are working together on the Digital Summer project, which will center around networked road surface monitoring. By leveraging machine learning technologies, Trafikverket will be able to improve road management in Sweden. As part of the initiative, linked car cameras will record variations in the state of road surfaces using the 3DAI City platform. Swedens roadside infrastructure will be digitized thanks to AI software, which will convert physical assets into real-time data to produce insights. Transportation officials and infrastructure managers may then effectively monitor highways and roadside assets and make more informed decisions thanks to Univrses scalable analytics capabilities. This facilitates operations and enables them to take proactive measuresthat benefit society as a whole and the environment.

Artificial intelligence (AI) offers a revolutionary approach to the difficult problems associated with traffic management, especially in quickly growing urban areas like Dhaka. Cities may improve road safety, reduce traffic, and optimize transportation networks by utilizing AI technology including automated monitoring, predictive analytics, enforcement systems, and route optimization. By incorporating artificial intelligence technologies into current infrastructure and advancing smart city projects, we can create more effective, eco-friendly, and user-friendly transportation systems that will benefit both locals and commuters. Future traffic management will be greatly influenced by AI, which will play a crucial role in establishing safer, more efficient, and easily accessible urban environments for future generations.

The writer is a student of Third year at the Department of Law, North South University



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