Robotic vehicles roll into reality

Self-driving or autonomous vehicles, gliding down the street without a driver actively operating any of the vehicle's control systems, are quickly emerging from the mist of sci-fi dreams.

Relying on sensors such as radar, lidar, sonar, GPS, odometry and inertial measurements to perceive their surroundings, robotic vehicles are currently being tested and fine-tuned by companies such as Tesla, Waymo, and Uber. According to the National Conference of State Legislatures, at least 29 states have enacted legislation related to autonomous vehicles.

In February of this year, Tesla CEO Elon Musk said that he anticipates the completion of a fully autonomous vehicle by the end of this year. In April, he predicted that “probably two years from now, we’ll make a car with no steering wheels or pedals.”

Fasten your seatbelt. It looks like we’re in for an interesting ride.

Ford shoos bugs from auto sensors

In testing the LiDAR sensors on its self-driving cars, Ford has gone the extra mile to make sure they can function consistently under realistic circumstances. Some of the methods Ford has employed include showering sensors with water, dirt and dust, smearing cameras with synthetic bird droppings, and enlisting a “bug launcher” that shoots insects into sensors at high speed.

Test engineers took advantage of the “tiara” on top of the car that houses the cameras, LiDAR, and radar. The tiara was used to funnel air through slots near the camera lens which created an air curtain that deflected incoming insects. Not satisfied with the results, engineers added a system of nozzles near the lens to spray washer fluid in tandem with software algorithms that would determine when a cleaning was needed. Air flowing through tiara slots were used as a drying agent.¹

Allowing self-driving cars to make more human decisions

MIT researchers have come up with an enhanced end-to-end navigation system designed to help driverless cars negotiate roads they’ve never encountered before. The system uses maps and visual data, along with machine learning, to learn the steering patterns of a human driver, and later replicate the patterns in unfamiliar territory, using only data from video camera feeds and a simple GPS-like map. “With our system, you don’t need to train on every road beforehand,” says first author Alexander Amini, an MIT graduate student. “You can download a new map for the car to navigate through roads it has never seen before.”

“Our objective is to achieve autonomous navigation that is robust for driving in new environments,” adds co-author Daniela Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science. “For example, if we train an autonomous vehicle to drive in an urban setting such as the streets of Cambridge, the system should also be able to drive smoothly in the woods, even if that is an environment it has never seen before.”²

Ford exec.: Ford autonomous vehicles will last only four years

John Rich, operations head for Ford autonomous vehicles, recently stated that Ford autonomous vehicles will last only four years. His prediction doesn’t mean the autos won’t be sturdy enough to log in high mileage—Rich thinks the vehicles are going to be used more heavily than “normal” use. His reasoning is that decreasing ownership of autos will lead to consumers hailing autonomous vehicles when needed. Such a scenario might lead to the vehicles running 24/7, and thus the accelerated mortality of the robotic carriages.³