Parking accurately and safely in highly constrained spaces remains a critical challenge. Unlike structured driving environments, parking requires executing complex maneuvers such as frequent gear shifts and steering saturation. Recent attempts to employ imitation learning (IL) for parking have achieved promising results. However, existing works ignore the multimodal nature of parking behavior in lane-free open space, failing to derive multiple plausible solutions under the same situation. Notably, IL-based methods encompass inherent causal confusion, so enabling a neural network to generalize across diverse parking scenarios is particularly difficult. To address these challenges, we propose MultiPark, an autoregressive transformer for multimodal parking. To handle paths filled with abrupt turning points, we introduce a data-efficient next-segment prediction paradigm, enabling spatial generalization and temporal extrapolation. Furthermore, we design learnable parking queries factorized into gear, longitudinal, and lateral components, parallelly decoding diverse parking behaviors. To mitigate causal confusion in IL, our method employs target-centric pose and ego-centric collision as outcome-oriented loss across all modalities beyond pure imitation loss. Evaluations on real-world datasets demonstrate that MultiPark achieves state-of-the-art performance across various scenarios. We deploy MultiPark on a production vehicle, further confirming our approach's robustness in real-world parking environments.

Ensuring the safety of road vehicles at an acceptable level requires the absence of any unreasonable risk arising from all potential hazards linked to the intended au-tomated driving function and its implementation. The assurance that there are no unreasonable risks stemming from hazardous behaviours associated to functional insufficiencies is denoted as safety of intended functionality (SOTIF), a concept outlined in the ISO 21448 standard. In this context, the acquisition of real driving data is considered essential for the verification and validation. For this purpose, we are currently developing a method with which data collect-ed representatively from production vehicles can be modelled into a knowledge-based system in the future. A system that represents the probabilities of occur-rence of concrete driving scenarios over the statistical population of road traffic and makes them usable. The method includes the qualitative and quantitative ab-straction of the drives recorded by the sensors in the vehicles, the possibility of subsequent wireless transmission of the abstracted data from the vehicles and the derivation of the distributions and correlations of scenario parameters. This paper provides a summary of the research project and outlines its central idea. To this end, among other things, the needs for statistical information and da-ta from road traffic are elaborated from ISO 21448, the current state of research is addressed, and methodical aspects are discussed.

Austin Russell is the 25-year-old founder and CEO of Luminar, a startup in Silicon Valley that makes LIDAR sensors for self-driving cars. LIDAR technology had been used for short-distance mapping, but Luminar claims to have a functioning LIDAR that works at 250 meters, which is a breakthrough. Luminar recently went public, making Austin today's youngest self-made billionaire. And when it comes to self-driving cars, youth is definitely an advantage -- Austin told me we're still years if not decades away from fully self-driving cars, and there's a lot of work to be done to make them safe, effective, and ubiquitous. That work is racing ahead -- Luminar has deals with Volvo, Audi, Toyota, and others -- but building a complete self-driving car is still a long-term project. This transcript has been lightly edited for clarity. I'm very excited to talk to you. You are, as far as the last thing I read, the youngest self-made billionaire in America, your company just went public in a SPAC [special purpose acquisitions company]. And come Pi Day, 26. You were born on Pi Day? So, Luminar, it's a company that makes LIDAR sensors. You have a number of deals to supply LIDAR sensors to major automakers. I want to talk about all of that. One thing that I always get frustrated by in origin stories is no one ever really talks about act two. In 2012 you were at Stanford, you had this idea to do LIDAR sensors. I want to talk about act two for a little bit. Just that middle part of going from "I've got a great idea," to "This company is actually up and running and functional." So give me a sense of, at the beginning you were a student at Stanford, you got a Thiel Fellowship from Peter Thiel. What was the next step? Did you sit down and build a LIDAR sensor?

The CEO of Intel Corp-owned Mobileye on Tuesday laid out plans for a self-driving car system for 2025 that could use house-built lidar sensors rather than units from Luminar Technologies Inc. Luminar shares closed down 17.6 percent after Reuters reported the move. In November, Mobileye signed a supply agreement with Luminar to use its lidar units in the first generation of Mobileye's driverless vehicle fleet. Luminar told Reuters that there has been no change to that agreement and that Luminar has also supplied lidar units for Mobileye development vehicles for nearly two years. Luminar said its units, which are only one part of Mobileye's broader self-driving system costs, are priced at less than $1,000 and exceed Mobileye's cost and performance requirements. Amnon Shashua, CEO of Mobileye and an Intel senior vice president, told Reuters that Mobileye's first generation of full self-driving kits -- which will include Luminar's lidar units along with a range of other chips, sensors and software -- will cost between $10,000 and $20,000.

We are encouraging questions from readers about electric vehicles, and charging, and whatever else you want to learn. So please send them through and we will get our experts to respond, and invite other people to contribute through the comments section. Hi Bryce –To future proof an EV purchase, which models available in Australia have an autonomous mode that can be switched on when the law of the land allows it to happen? Hi John – you ask an interesting question, although I think I'll reframe it slightly to ask'what is autonomous driving, and is it safe?' At the end of that explanation, I am hoping you will be able to answer your own question without my help!

Byton, the new China-based company that unveiled a tech-centric all-electric SUV concept at the big tech trade show CES in January, is now tapping some outside experts to bring self-driving car technology into their future vehicles. Byton announced Monday that it has partnered with self-driving vehicle technology startup Aurora. The buzzy startup, led some of the best minds in self-driving cars, will work on bringing Level 4 autonomous vehicle capabilities into Byton vehicles. The two companies will conduct a pilot deployment of Aurora's L4 autonomous driving systems on Byton vehicles in the "next two years." The pilot will be in California, Aurora CEO Chris Urmson said.

The annual Consumer Electronics Show, in Las Vegas has become the best place to learn about what's coming to cars. This year, however, the wild new capabilities rolling through CES, and into the auto industry, went from an open secret to headline grabbing news. As a result, it was an incredible week for us. Since we unveiled our AI computing platform for autonomous vehicles at CES last year, DRIVE PX 2 has become the core of the AI revolution sweeping the auto industry. That became clear with the show's opening keynote Wednesday from NVIDIA Co-Founder and CEO Jen-Hsun Huang, who announced our new AI Co-Pilot for the car built on DRIVE PX 2, as well as our ever expanding AI Car ecosystem of partners.

Just two days ahead of the official start to the 2017 Consumer Electronics Show, CES Unveiled gave a sneak peek at some of the technology set to make a splash this year. With robots designed as companions for the elderly, a smart glove for stroke rehabilitation, and even a helmet said to combat baldness, many of the products focused on medical care and personal wellbeing. But, virtual reality dominated the show floor on Tuesday night as well, with everything from immersive exoskeletons to VR slippers. Pictured, an attendee wears the iGrow hair growth system from Apira Science. Exhibitors from Yumii showed off the adorable robot named'Cutii,' which acts as a platform to keep older people connected with the world around them.

Faraday Future, the mysterious Chinese electric car poised to take on Tesla, unveiled its first production vehicle at CES yesterday. Dubbed the FF91, the self-driving car was described by the firm as representing an entirely'new species' of vehicle. But the company was left red-faced when it tried to demo the car's self-parking feature at its unveiling in Las Vegas. Before the car malfunctioned, the crowd at CES had watched a camouflaged prototype parking itself outside of the venue. It wasn't until the car had to perform the same manoeuvre on stage that events started taking a turn for the worse.

Just two days ahead of the official start to the 2017 Consumer Electronics Show, CES Unveiled gave a sneak peek at some of the technology set to make a splash this year. With robots designed as companions for the elderly, a smart glove for stroke rehabilitation, and even a helmet said to combat baldness, many of the products focused on medical care and personal wellbeing. But, virtual reality dominated the show floor on Tuesday night as well, with everything from immersive exoskeletons to VR slippers. Pictured, an attendee wears the iGrow hair growth system from Apira Science. Exhibitors from Yumii showed off the adorable robot named'Cutii,' which acts as a platform to keep older people connected with the world around them.