challenge for autonomous vehicles

Vehicle Technology

challenge for autonomous vehicles


DARPA’s challenge for autonomous vehicles
Why driverless cars?

challenge for autonomous vehicles A machine is everything that helps us simplify work. By this definition, a car is a machine that helps us simplify the work of motion. However, we need some work when we use a car, we have to drive it. Wouldn’t life be easier if we could get in the car and say where we want to go and postpone our heads until we reach the destination? As fantastic as it may sound, it may be possible in the near future if the innovations showcased at the DARPA Urban Challenge in 2007 are developed to their full potential.

If you are a fan of science fiction, remember the taxi with the robot driver in “Total

Recall”, which Arnold Schwarzenegger violently dismantles when he denies his order

to “just drive” and insists on knowing the name of his destination. While you may not

see such autonomous cars on the roads anytime soon, the DARPA Urban Challenge participants give us cause for hope.

What is DARPA and how is it involved?

For those who don’t know yet, DARPA or the Defense Advanced Research Projects. Agency is the lead investigative body of the United States Department of Defense.

With a total staff of only 240, DARPA administers a budget of $ 3.4 billion for the

purpose of developing new technology for military use. In this capacity, he has made

significant contributions to various technologies that we take for granted today, such as the Internet and GPS.


is authorized by Congress to award cash prizes to further research with potential

national security applications. In this sense, DARPA started in 2004 an annual

competition, called Grand Challenge, for autonomous or driverless vehicles, which last three years (with a gap in 2006), the last of which in 2007 was designate

Urban Challenge. DARPA defines an autonomous vehicle as “a vehicle that navigates

and drives itself without a human driver and without a remote control. Using different

sensors and positioning systems, the vehicle determines all the required characteristics of its environment required to enable its performance. . the task assigned to you “.

While the first two required self-driving cars to drive through desert roads, curves and tunnels without human intervention, the latter required the cars to comply with traffic

laws in a simulated urban environment. Therefore, while the first two challenges were

more physically demanding but had little interaction between vehicles, the Urban

Challenge required individual participants to make “smart” decisions in real time based on the actions of other vehicles.

Although the competitions

were open to teams from around the world, each team had to have at least one US citizen as a member. The rationale for these competitions was the ultimate goal of making one-third of America’s ground military forces autonomous by 2015.

DARPA Grand Challenge 2004 and 2005

The 2004 DARPA Grand Challenge was held in the Mojave Desert, where 25 teams

competed for the $ 1 million grand prize. Although neither team completed the 150-

kilometer route, the Carnegie Mellon University car travel the longest (7.36 miles) and was declared the winner.

The next competition near the Lucy Gray Mountains, Nevada, in 2005 yielded significantly better results. All but one of the 23 finalists surpassed last year’s best qualification and five completed the 135-kilometer race. The Stanford University team finished first, closely followed by two Carnegie Mellon cars. The prize money was double that of the previous year.

DARPA Urban Challenge 2007

The third competition was the toughest of all and require “teams to build an

autonomous vehicle capable of driving in traffic, performing complex maneuvers such

as braiding, passing, parking and negotiating intersections.”

The development of such technology has potentially huge benefits not only for military

purposes but also for civil applications. In addition to the obvious benefit of easy travel, this technology, when revised and popularized, can alleviate traffic congestion and prevent accidents, saving thousands of lives and billions of dollars each year, as well as reducing pollution and downtime.

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