Most of us don't like to wait at traffic signals till the light turns green to move past them. Sometimes, we try to bypass the signals and end up getting caught in the process, followed by paying a hefty fine. At times, this can also result in accidents. It's true that waiting at the signal is very tiring and it costs us in terms of fuel wastage and time, while damaging the environment. Motorists and policy planners want a practical alternative to end this nuisance, albeit a minor one. Researchers at the Massachusetts Institute of Technology (MIT) think they've uncovered one.

Figure 1. AI Can Make Traffic Signals Less Chaotic, Roads More Organised for Motorists in Future

Figure 1 shows Using AI, the car’s velocity may be adjusted in a means that it reaches the following sign simply in time to go via it with out having to attend for the color to alter to inexperienced. In their examine, revealed on the pre-print server arXiv, the researchers exhibit a machine studying strategy that may be taught to manage a fleet of self-driven automobiles in a means that retains site visitors’s move easy.

As a result, the researchers devised a workaround known as reward shaping. They provided the system domain with information it couldn't have learnt on its own by using reward shaping. They penalised the system in this scenario anytime the vehicle came to a complete stop, so it would learn to avoid doing so in the future.

They tested their control algorithm using a traffic simulation platform with a single intersection once they had constructed it. As automobiles neared the crossroads, their system did not cause any stop-and-go traffic. When cars are forced to come to a complete stop due to stalled traffic ahead, this is known as stop-and-go traffic. [3]

More cars passed through a single green phase in simulations, outperforming a model that simulates human drivers. When compared to previous optimisation strategies aimed at avoiding stop-and-go traffic, their approach resulted in higher fuel savings and lower emissions.

If all vehicles on the road are autonomous and linked with their system, they can reduce fuel consumption by 18 percent and CO2 emission by 25 percent, while improving travel speed by 20 percent, they say. Even if only two percent of vehicles are autonomous, they can offer at least 50 percent of the total fuel and emission reduction benefits.

References:

1. https://newslogic.in/science/ai-can-make-traffic-signals-less-chaotic-roads-more-organised-for-motorists-in-future-say-mit-researchers/
2. https://180gadgets.com/ai-can-make-traffic-signals-less-chaotic-roads-more-organised-for-motorists-in-future-say-mit-researchers/
3. https://news.zordo.in/ai-can-make-traffic-signals-less-chaotic-roads-more-organised-for-motorists-in-future-say-mit-researchers-228930.html
4. https://gadgets360.com/science/news/ai-traffic-signals-less-chaotic-motorists-future-mit-research-3021763

Cite this article:

Thanusri swetha J (2022), AI Can Make Traffic Signals Less Chaotic, Roads More Organised for Motorists in Future, Anatechmaz, pp.109