Silicon Valley startup Tensor plans to sell the world's first personal robocar, allowing consumers to own self-driving cars by 2026.

This paper introduces RoboCar, an open-source research platform for autonomous driving developed at the University of Luxembourg. RoboCar provides a modular, cost-effective framework for the development of experimental Autonomous Driving Systems (ADS), utilizing the 2018 KIA Soul EV. The platform integrates a robust hardware and software architecture that aligns with the vehicle's existing systems, minimizing the need for extensive modifications. It supports various autonomous driving functions and has undergone real-world testing on public roads in Luxembourg City. This paper outlines the platform's architecture, integration challenges, and initial test results, offering insights into its application in advancing autonomous driving research. RoboCar is available to anyone at https://github.com/sntubix/robocar and is released under an open-source MIT license.

Collaborative logistics has been widely recognised as an effective avenue to reduce carbon emissions by enhanced truck utilisation and reduced travel distance. However, stakeholders' participation in collaborations is hindered by information-sharing barriers and the absence of integrated systems. We, thus, in this paper addresses these barriers by investigating an integrated platform that foster collaboration through the integration of agents with digital twins. Specifically, we employ a multi-agent system approach to integrate stakeholders and physical mobile assets in collaborative logistics, representing them as agents. We introduce a loosely-coupled system architecture that facilitates the connection between physical and digital systems, enabling the integration of agents with digital twins. Using this architecture, we implement the platform (or testbed). The resulting testbed, comprising a physical environment and a digital replica, is a digital twin that integrates distributed entities involved in collaborative logistics. The effectiveness of the testbed is demonstrated through a carrier collaboration scenario. This paper is among the earliest few efforts to investigate the integration of agents and digital twin concepts and goes beyond the conceptual discussion of existing studies to the technical implementation of such integration. Transportation is the largest contributor to greenhouse gas (GHG) emissions [1]. Among all transportation modes, trucks are the second-largest source of emissions after cars and taxis. However, they are currently utilised inefficiently, operating at around 60% of their weight capacity, and approximately 30% of the distance they travel carries no freight [2]. Collaborative logistics has been widely recognised as an effective pathway to enhance truck utilisation [3] [4] [5]. This approach involves carriers collaborating through coalition to collectively fulfil delivery requests, achieving reduced total cost and travel distance through economies of scale. Two key barriers, among others [5], contribute to this challenge: 1) Lack of Trusted Platforms: Concerns business secrecy may deter carriers from sharing data with centralised platforms, despite the environmental and economic benefits. These barriers hinder stakeholders' participation in collaboration.

How AutonomousVehicles will change our lives forever? An autonomous car (driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Self-driving vehicles can detect surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision. It's been suggested that 57% of roadway accidents are due to human error. However, with driverless vehicles, its suggested that this number could dramatically decrease as unlike humans, the computer technology in cars can't be'distracted'.

Once an industry with long development cycles, the automotive space is being upended by China's tech giants. One can hardly keep up with all the new electric vehicle brands that come out of the country nowadays. Jidu, an electric carmaking company founded by Baidu and its Chinese auto partner Geely only a year ago, said Wednesday it has banked nearly $400 million in a Series A funding round. The new injection, bankrolled by Baidu and Geely, which owns Volvo, is a boost to the $300 million initiation capital that Jidu closed last March. The proceeds will speed up Jidu's R&D and mass production process and allow it to showcase its first concept "robocar" -- which it classifies as an automotive robot rather than a car -- at the Beijing auto show in April.

More Chinese automakers collaborating on EVs -- The automotive industry has entered into an intense era of collaboration among carmakers, technology giants, and even software start-ups, among others. This trend comes as countries, including China, accelerate into increased usage of EVs and AVs. Numerous partnerships have sprouted up in the past year, adding density and life to this ecosystem. Among Chinese automakers themselves, a handful of significant partnerships were made to accelerate the developments of EVs and AVs within the country. In fact, China is shaping up to be the first real test of Big Tech's ambitions in the world of car making.

The potential of reinforcement learning (RL) to deliver aligned and performant agents is partially bottlenecked by the reward engineering problem. One alternative to heuristic trial-and-error is preference-based RL (PbRL), where a reward function is inferred from sparse human feedback. However, prior PbRL methods lack interpretability of the learned reward structure, which hampers the ability to assess robustness and alignment. We propose an online, active preference learning algorithm that constructs reward functions with the intrinsically interpretable, compositional structure of a tree. Using both synthetic and human-provided feedback, we demonstrate sample-efficient learning of tree-structured reward functions in several environments, then harness the enhanced interpretability to explore and debug for alignment.

Baidu also took the wraps off a "robocar," an autonomous vehicle with doors that open up like wings and a big screen inside for entertainment. It is a prototype and the company gave no word on whether it would be mass-produced. But the concept car highlights Baidu's ambitions in autonomous driving, which analysts predict could be a multibillion dollar business for the Chinese tech giant. Baidu has also been running so-called robotaxi services in some cities including Guangzhou and Beijing where users can hail an autonomous taxi via the company's Apollo Go app in a limited area. On Wednesday, Baidu rebranded that app to "Luobo Kuaipao" as it looks to roll out robotaxis on a mass scale.

LAS VEGAS, NEVADA - JANUARY 07: Mobileye CEO and Intel Senior Vice President Amon Shashua speaks ... [ ] during an Intel press event for CES 2019 at the Mandalay Bay Convention Center on January 7, 2019 in Las Vegas, Nevada. CES, the world's largest annual consumer technology trade show, runs from January 8-11 and features about 4,500 exhibitors showing off their latest products and services to more than 180,000 attendees. At the EcoMotion self-driving conference held (in cyberspace) from Israel this week, Amnon Shashua, founder and CEO of MobilEye, now a unit of Intel INTC, declared their intention to offer robotaxi service, with no safety drivers, in early 2022. They will begin in their headquarters town of Jerusalem, then move to Tel Aviv, then France, Korea and China. He makes this statement while many other companies, particularly car OEMs, are scaling back their plans and timelines on full robocar service.

Robot-maker ZMP Inc. is aiming to launch the first commercial level 3 automated bus operation in Japan at an airport in 2020. The Tokyo-based startup, which bills itself as the "robot of everything," has built a variety of contraptions ranging from delivery robots to autonomous forklifts. It plans to start marketing Japan's first fully autonomous single-seat electric vehicle, the Robocar Walk, in May, founder and CEO Hisashi Taniguchi said. Taniguchi expanded on his plans during a recent interview. Is it true ZMP is targeting a level 4 automated driving business by the Olympics? Yes, we are aiming for commercial operation of an unmanned level 4 autonomous vehicle.