AI (artificial intelligence) is revolutionizing every area of modern life, including transportation and intercity bus travel. Mass transit systems are being modified to use AI technology and applications to help reduce the number of single-passenger vehicles on the streets and lower emissions and fuel consumption.
Artificial intelligence refers to computers and technologies that are capable of learning and thinking like a human without the emotional component. The goal of AI is to take big data and boil it down into actionable items and usable information. Developers want systems to be able to learn and adapt as new information is introduced and also predict the future based on historical data. AI is sometimes called machine learning.
The shift to AI in city transportation is more prevalent than most realize. It begins with the collection of a massive amount of raw data from current mass transit options, collecting information about the number of travelers, number of stops, destinations, and the cost. AI applications then sift through and analyze this data faster and more efficiently than any human being could, to find patterns and create reliable assumptions that can be used for AI vehicles. The results from all this data crunching are being used by technicians and engineers to develop automated systems for bus travel throughout cities all over the U.S.
The current application of AI for mass transit is in the planning phase. The data has been collected, and now AI is sifting through it and providing viable solutions and plans for the next phase. Some of the early results that have come out of this process are more efficient bus schedules that match up with customer needs.
Although the idea of autonomous buses seems far off, it is not. Major cities all over the United States are already testing beta models. Asia has employed autonomous buses since August of 2015. These buses use special cameras, laser radar, and a master controller computer to keep track of road conditions, traffic, and pedestrians. These early model buses currently have drivers as a backup in case something goes wrong, but they are essentially self-driving vehicles.
Public concern over the safety of self-driving vehicles versus traditional intercity buses should rest assured. The statistics prove that human error happens far more often than system failures. Autonomous vehicles are much safer than traditional vehicles driven by humans. The AI contained within self-driving vehicles continually monitors the space distance between the vehicle and other cars, people, and objects.
The most significant benefit of driverless buses is driver safety. According to the NHTSA, more than 37,000 people die in car crashes every year, and almost 95% are due to human errors. Distracted driving, drug and alcohol abuse, and other issues can make the roads unsafe. Autonomous vehicles, including buses, help to reduce traffic congestion, drastically improve safety, and help with emissions and gas usage.
With AI at the wheel, rapidly calculating alternate routes due to accidents and traffic congestion, autonomous vehicles will be much more efficient. The work being done now to collect data on schedules, routines, and customer demand will help dictate the number of busses, the most efficient routes to take, and cost-effective solutions for mass transit.
Although car manufacturers are doing a better job of controlling emissions in new vehicles, cities, have a real problem on their hands. By reducing the number of single-driver vehicles and consolidating travelers into autonomous vehicles, the amount of emissions stands to be reduced drastically, improving air quality and saving our planet as a bonus.
Fuel is not an unlimited resource, and without some changes, it will eventually run out. By moving swiftly to autonomous bus systems and more efficient mass transportation in cities, the fuel consumption will be drastically reduced with fewer cars on the road, and gas will last years longer into the future.
Bus schedules are meant to be staggered, so passengers have a choice of pick-up times. However, due to delays, sometimes, buses will arrive at the same stop at the same time. This situation is called bus bunching. One of the jobs AI will be tasked with is constantly monitoring bus stop attendance, bus schedules, delays, alternate routes, and other factors that can result in bus bunching. The efficient model that bus engineers are developing should eliminate this phenomenon. Humans can’t collect and analyze all this data at once, but computers and AI will be able to do it easily in milliseconds making small adjustments to keep everything running smoothly and on time.
The adaptation of AI in public and intercity city buses will be slow. Tests are already being conducted in some major cities with rollouts of autonomous bus fleets expected within the next 5-7 years. First, though, a lot of hardware and software will need to be put in place to assist the self-driving vehicles. Things like cameras, radar, and software are already in the works during this phase II planning session.
Intercity traffic management operations are a combined effort by bus drivers and dispatchers that help them avoid congestion, accidents, and other traffic-related issues that could delay bus schedules. Both drivers and dispatchers are working off what they can see and hear, and this results in human error and inefficiency at times. With access to hundreds of cameras and radar feeding back real-time data along with predictive analysis, AI has the advantage of being much more efficient, driving on-time schedules, and avoiding human error. Not only can AI “see” what is going on miles down the road, but it can also predict the likely future based on historical and current data.
Currently, cities use traffic cameras that perform instant VIN lookup to monitor traffic and issue tickets when necessary. These systems will be upgraded with more sophisticated models that can communicate back and forth with autonomous busses for better traffic management and monitoring of the entire system.
Experts predict that mass transit will be connected to a single mobile app where customers pay a flat fee for transportation on one of many types of autonomous vehicles such as buses, trains, cars, and shuttles. The single AI-linked app will allow travelers to book passage, pay for tickets, and review ever-changing schedules to get where they are going swiftly and efficiently.
Because all the data will be centralized, customers will have the option of picking the best ride-share solution that fits their needs. We can only speculate how soon and how far this technology will eventually go.
The overall impact of AI technology on intercity bus travel should be overwhelmingly positive with many benefits. Before, during, and after the implementation, statisticians will be gathering data to certify the results. The better people feel about safety and efficiency, the more they will use this new groundbreaking revolutionary type of travel.
About the author:
Ben is the expert technical writer for InfoTracer where he authors guides on security posture, both physical and cyber. Besides security, Ben is passionate about the automotive world and regularly test-drives new vehicles on highways and back roads. He enjoys sharing the best practices and does it the right way!
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View Comments
Hi Ben
Are there any examples of companies breaking into the AI bus space?
Thanks
Philip
There's alot of money to be made online in promoting travel.
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