Thursday, September 17th

By Arthur Atangana

Tesla has promised fully functional self-driving technology for a while now, but it might come sooner than expected, if Elon Musk is to be believed. On Sunday, he revealed on Twitter that a private beta of the new technology will be released, with a full fledge integration into the US market in December. Whether Tesla can keep the promises made by its CEO remains to be seen, but should the company deliver, it will reaffirm its dominance in the AV sector.

The Pittsburgh based startup Seegrid has finalized a $52 million round of investments for its industrial autonomous vehicles. The company has built warehouse vehicles dedicated on moving heavy loads. With two models already on the market, a pallet truck and a tow tractor that can move 8,000 and 10,000 pounds respectively, Seegrid’s valuation has grown since its humble beginnings to over $400 millions, Bloomberg reported.

If automation is coming to a variety of vehicles, some applications keep on surprising everyone. Beijing company Idriverplus recently raised $14.6 million to ramp up the production of its autonomous street cleaning robot Woxiaobai, VentureBeat reported. The company is also developing other AV technology, and is also bringing to market an autonomous delivery vehicle called the Wobida.

Image Credit: Idriverplus

When Uber’s self-driving car tragically struck and killed a pedestrian back in 2018, autonomous vehicles where placed under the spotlight. The legal ambiguity around who should be responsible came to a stop in 2019 when the office of the prosecutor in Arizona said that Uber would not face criminal liability. This Tuesday, The New York Times reported that the safety driver operating the vehicle was charged with negligent homicide.

A new algorithm targeting autonomous vehicle safety has been developed at the Technical University in Munich, Germany. Despite it needing extensive testing, the algorithm theoretically reduces greatly some of the most important weaknesses of current software: Pedestrian avoidance, turning left at an intersection, and changing left. Techxplore reported that despite the great promises of these types of algorithm, a growing number of researchers warn that depending on algorithm for these types of improvements may overlook the opportunity for human drivers to collaborate with artificial intelligence.