{"id":554663,"date":"2024-08-10T13:00:00","date_gmt":"2024-08-10T11:00:00","guid":{"rendered":"https:\/\/mybroadband.co.za\/news\/?p=554663"},"modified":"2024-08-10T13:01:47","modified_gmt":"2024-08-10T11:01:47","slug":"self-driving-cars-improve-traffic-even-when-most-other-vehicles-are-driven-by-people","status":"publish","type":"post","link":"https:\/\/mybroadband.co.za\/news\/motoring\/554663-self-driving-cars-improve-traffic-even-when-most-other-vehicles-are-driven-by-people.html","title":{"rendered":"Self-driving cars improve traffic \u2014\u00a0even when most other vehicles are driven by people"},"content":{"rendered":"\n

Robotic vehicles can optimize the flow of traffic<\/a> in cities even when mixed in with vehicles driven by humans, thereby improving traffic efficiency, safety and energy consumption, my colleagues and I found.<\/p>\n\n\n\n

Robot vehicles are no longer a sci-fi concept: Cities around the world have been testing autonomous robotaxis<\/a> since 2016<\/a>.<\/p>\n\n\n\n

With the increasing presence of robot vehicles in traffic and the foreseeable long period of transitioning from mixed traffic to fully autonomous traffic, my team and I wondered whether robot vehicles and their interactions with human-driven vehicles can alleviate today\u2019s notorious traffic problems.<\/p>\n\n\n\n

I am a computer scientist<\/a> who studies artificial intelligence for transportation and smart cities. My colleagues and I hypothesized that as the number of robot vehicles in traffic increases, we can harness AI to develop algorithms to control the complex mixed traffic system.<\/p>\n\n\n\n

These algorithms would not only enable all vehicles to travel smoothly from point A to point B but, more importantly, optimize overall traffic by allowing robot vehicles to affect vehicles driven by people.<\/p>\n\n\n\n

To test our hypothesis, we used a branch of AI known as reinforcement learning<\/a>, in which an intelligent agent learns to maximize cumulative rewards through interaction with its environment.<\/p>\n\n\n\n

By setting rewards for simulated robot vehicles to prioritize goals such as traffic efficiency or energy consumption, our experiments show that we can effectively manage mixed traffic at complex real-world intersections<\/a> under real-world traffic conditions in simulation.<\/p>\n\n\n\n

Our algorithm teaches the robocars to optimize traffic flow by communicating with each other.<\/p>\n\n\n\n

The collective system of cars aims for smooth traffic flow even as each individual car decides when to enter an intersection based on its immediate environment.<\/p>\n\n\n\n

Because the robocars are dispersed among cars driven by people, all traffic is affected by the algorithm.<\/p>\n\n\n\n

We found that when robot vehicles make up just 5% of traffic in our simulation, traffic jams are eliminated<\/a>.<\/p>\n\n\n\n

Surprisingly, our approach even shows that when robot vehicles make up 60% of traffic, traffic efficiency is superior to traffic controlled by traffic lights<\/a>.<\/p>\n\n\n\n

\"\"
Simulating a blackout at a traffic intersection. The top row shows traffic conditions without robovehicles. The blackout occurs at the 5-minute mark. Congestion forms rapidly within 15 minutes. The bottom row shows traffic with 50% robovehicles. The blackout causes no congestion. Wang et al<\/a><\/figcaption><\/figure>\n\n\n\n

Why it matters<\/h2>\n\n\n\n

Traffic is worsening in every major city across the globe, leading to significant economic and environmental costs<\/a>.<\/p>\n\n\n\n

It is one of the most challenging problems society faces today. Current traffic control methods, such as traffic lights, have limited effectiveness in reducing delays and congestion<\/a>.<\/p>\n\n\n\n

AI-driven robot vehicles offer a potential solution, but existing studies often assume universal connectivity and centralized control<\/a> of all robot vehicles, a scenario that is not likely to materialize anytime soon.<\/p>\n\n\n\n

The transition to fully autonomous traffic is likely to be gradual<\/a>, resulting in a prolonged period of mixed traffic with both robot and human-driven vehicles.<\/p>\n\n\n\n

This led us to develop control algorithms that use robotic vehicles to harness the societal benefits of autonomous transportation systems without requiring all or even a majority of vehicles to be autonomous.<\/p>\n\n\n\n

What other research is being done<\/h2>\n\n\n\n

Recent studies have demonstrated the potential of mixed traffic control<\/a> in scenarios such as ring roads, figure-eight roads, highway bottlenecks and merges, two-way intersections and roundabouts.<\/p>\n\n\n\n

However, these scenarios typically lack real-world complexity and only involve a limited number of vehicles that need to be coordinated.<\/p>\n\n\n\n

Our work is the first to demonstrate the feasibility of controlling mixed traffic via robot vehicles at real-world, complex intersections.<\/p>\n\n\n\n

Being able to control traffic at these intersections is an essential step toward citywide traffic control.<\/p>\n\n\n\n

What\u2019s next<\/h2>\n\n\n\n

We plan to expand our framework to incorporate additional driving behaviors for robot vehicles, such as frequent lane-changing.<\/p>\n\n\n\n

We also plan to test our approach on a variety of intersection types, and we want to test our approach under real-world vehicle-to-vehicle communications.<\/p>\n\n\n\n

Ultimately, our goal is to achieve effective and efficient mixed traffic control at the scale of cities<\/a>.<\/p>\n\n\n\n

\n\n\n\n

The Research Brief<\/a> is a short take on interesting academic work.<\/em><\/p>\n\n\n\n

Weizi Li<\/a>, Assistant Professor of Computer Science, University of Tennessee<\/a><\/em><\/p>\n\n\n\n

This article is republished from The Conversation<\/a> under a Creative Commons license. Read the original article<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Robotaxis have caused problems, but a study shows that they have the potential to improve traffic conditions.<\/p>\n","protected":false},"author":340972,"featured_media":554664,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_sma_x_autopost_status":"idle","_sma_x_autopost_error":"","_sma_x_post_id":"","_sma_facebook_post_id":"","_sma_instagram_post_id":"","_sma_x_attempts":0,"footnotes":""},"categories":[92837,29366],"tags":[88065],"class_list":["post-554663","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-motoring","tag-autonomous-cars"],"_links":{"self":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/554663"}],"collection":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/users\/340972"}],"replies":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/comments?post=554663"}],"version-history":[{"count":3,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/554663\/revisions"}],"predecessor-version":[{"id":554669,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/554663\/revisions\/554669"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/media\/554664"}],"wp:attachment":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/media?parent=554663"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/categories?post=554663"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/tags?post=554663"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}