When people think of the automotive Factory of the Future, the first word that comes to mind is automation. They think of the "lights-out" factory that General Motors Chief Executive Roger Smith fantasized about in 1982 and Elon Musk talks about building today--plants so dominated by robots and machines that they don't need lights to work. There's no doubt that the auto industry will continue to vigorously pursue automation solutions to lower the cost of producing cars. But the reality is that any major leap forward on cost and efficiency will no longer be possible through automation alone, since most of the tasks that can be automated in an automotive factory have already been tackled. When a real Factory of the Future arrives, it will not look different because we have automated the processes we use today.
In the field of self-driving cars, algorithms for controlling lane changes are an important topic of study. But most existing lane-change algorithms have one of two drawbacks: Either they rely on detailed statistical models of the driving environment, which are difficult to assemble and too complex to analyze on the fly; or they're so simple that they can lead to impractically conservative decisions, such as never changing lanes at all. At the International Conference on Robotics and Automation tomorrow, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) will present a new lane-change algorithm that splits the difference. It allows for more aggressive lane changes than the simple models do but relies only on immediate information about other vehicles' directions and velocities to make decisions. "The motivation is, 'What can we do with as little information as possible?'"
From the first mass produced cars to passenger aircraft breaking the sound barrier, there have been numerous advances within the area of transportation that have had a profound effect on the way in which we approach travel and transport. However, the latest technological advance to begin to revolutionize transportation may come to dwarf any and all that arrived before it. And its uses are many. In this article, we'll being looking at a few examples of artificial intelligence within transportation and how it is helping to meet several of the most common and persistent challenges in this area. There are several challenges that are persistent throughout the transportation industry and that have plagued this sector ever since its inception.
For a while, people were really excited about the potential of self-driving cars, which promised to make our future commutes easier, more productive, and safer. Then came some high-profile autonomous vehicle accidents -- including two fatal crashes -- and let's just say the excitement has waned a bit. SEE ALSO: Tesla's Autopilot fails haven't shaken my faith in self-driving cars. A new survey released Tuesday by the American Automobile Association found that 73 percent of American drivers are scared to ride in an autonomous vehicle. That figure is up 10 percent from the end of last year.
Autonomous vehicles really don't know how to switch lanes as well as people do. They tend to rely on either relatively static data models that are difficult to study in the thick of traffic, or are basic enough that the car might only change lanes when it's absolutely necessary -- that is, hardly at all. MIT's CSAIL has a better way. The school has developed an algorithm that changes lanes more like humans do while respecting road safety. The new technique is a modification of a familiar concept of "buffer zones" that determine where other cars are going and how likely the driverless vehicle is to avoid a collision.
A Waymo self-driving van was involved in a car accident Friday afternoon in Chandler, Ariz. The self-driving van is not believed to be at fault, but this incident is still under investigation. U.S. drivers' fears of fully autonomous (self-driving) vehicles has risen in the past several months according to a new survey by AAA. Late last year a survey of American drivers revealed that 63% were wary of riding in a fully autonomous (self-driving) car. A new survey by AAA shows that nearly three-quarters (73%) now fear riding in a self-driving vehicle.
Police on Tuesday launched an expert panel tasked with discussing driving rules for autonomous vehicles, including a potential revision to road traffic laws. Experts in law, social infrastructure and other areas will discuss specific issues to be resolved as firms move closer to commercializing self-driving cars for public roads. The government has recently compiled a policy outline for introducing mostly autonomous cars by 2025. The panel is set to propose detailed rules such as how penalties will apply for accidents and traffic law violations involving level 3 and 4 autonomous vehicles. Level 3 autonomy allows drivers to move their attention from driving in specific situations while requiring them to take back control when the vehicle requests it.
San Jose, which was considered the "holy grail of shipwrecks," was located with the help of an underwater autonomous vehicle An autonomous vehicle was used in 2015 to locate a Spanish galleon that sunk 300 years ago off the coast of Colombia with $17 billion in treasure, the research team that helped in the discovery said on Monday. The San Jose, which was considered the "holy grail of shipwrecks," was located with the help of an underwater autonomous vehicle operated by the Woods Hole Oceanographic Institution. The institution said it was holding the discovery under wraps out of respect for the Colombian government. REMUS 6000 being deployed off the Colombian Navy research ship ARC Malpelo. The treasure--which includes of gold, silver and emeralds-- has been the subject of legal battles between several nations as well as private companies.
Last week, Apple's secretive, self-driving car project got some attention for adding more cars approved for testing in California. But despite the company's big name and the heightened curiosity over the iPhone-maker's foray into autonomous vehicles, the winner here is not the company you'd expect. We looked at the past few months of reports from the California DMV's self-driving permit program to see which of the 50-plus (and growing) companies involved are stepping up its testing. Only two companies -- Waymo, the self-driving car program from Google, and one other that has not been publicly revealed at this time -- have applied for permits for the state's truly driverless testing program, which would allow for an empty vehicle. In terms of cars currently allowed to test drive on the California road, GM's Cruise Automation dominates the big players.
The same can apply to autonomous vehicles. Methods will be established to test whether autonomous cars are likely to be safer than human drivers. In the unfortunate event of an accident where the robotaxi was at fault, an investigation by the authorities will determine whether the vehicle was indeed compliant. If it is concluded that the vehicle was compliant, but there was a sensor malfunction, then the incident would be handled in the same manner as a human-piloted vehicle would suffering from a brake or steering malfunction, which falls into the category of product liability. If it is determined that the vehicle was compliant; however, the software simply failed as a result of encountering a corner case it could not handle correctly, then traditional auto insurance can cover the damage, and a new insurance product; "A/V insurance," can cover the cost associated with the required disclosures and investigations.