# self-driving

Published articles for self-driving.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## System helps humans predict when self-driving cars will make mistakes

DevFeed: [System helps humans predict when self-driving cars will make mistakes](<https://devfeed.tech/articles/system-helps-humans-predict-when-self-driving-cars-will-make-mistakes-37982.md>)

Original publisher: [Read original article](<https://news.mit.edu/2026/system-helps-humans-predict-when-self-driving-cars-will-make-mistakes-0902>)

Author: Adam Zewe | MIT News

Published: 2026-09-02T15:00:00Z

Content type: news

Language: en

Sources: [MIT AI News](<https://devfeed.tech/sources/mit-ai-news.md>)

Topics: [autonomous vehicles](<https://devfeed.tech/topics/autonomous-vehicles.md>), [Deep learning](<https://devfeed.tech/topics/deep-learning.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Robotics](<https://devfeed.tech/topics/robotics.md>), [Simulation](<https://devfeed.tech/topics/simulation.md>), [Computer science](<https://devfeed.tech/topics/computer-science.md>)

Tags: [aeronautical-and-astronautical-engineering](<https://devfeed.tech/tags/aeronautical-and-astronautical-engineering.md>), [ai](<https://devfeed.tech/tags/ai.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [autonomous-vehicles](<https://devfeed.tech/tags/autonomous-vehicles.md>), [computer-science-and-artificial-intelligence-laboratory-csail](<https://devfeed.tech/tags/computer-science-and-artificial-intelligence-laboratory-csail.md>), [computer-science-and-technology](<https://devfeed.tech/tags/computer-science-and-technology.md>), [concept-wrapper-network](<https://devfeed.tech/tags/concept-wrapper-network.md>), [cw-net](<https://devfeed.tech/tags/cw-net.md>), [deep](<https://devfeed.tech/tags/deep.md>), [electrical-engineering-and-computer-science-eecs](<https://devfeed.tech/tags/electrical-engineering-and-computer-science-eecs.md>), [eoin-kenny](<https://devfeed.tech/tags/eoin-kenny.md>), [human-computer-interaction](<https://devfeed.tech/tags/human-computer-interaction.md>), [julie-shah](<https://devfeed.tech/tags/julie-shah.md>), [laura-major](<https://devfeed.tech/tags/laura-major.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mit-schwarzman-college-of-computing](<https://devfeed.tech/tags/mit-schwarzman-college-of-computing.md>), [momchil-tomov](<https://devfeed.tech/tags/momchil-tomov.md>), [motional](<https://devfeed.tech/tags/motional.md>), [research](<https://devfeed.tech/tags/research.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [safety](<https://devfeed.tech/tags/safety.md>), [school-of-engineering](<https://devfeed.tech/tags/school-of-engineering.md>), [self-driving](<https://devfeed.tech/tags/self-driving.md>), [self-driving-cars](<https://devfeed.tech/tags/self-driving-cars.md>), [simulation](<https://devfeed.tech/tags/simulation.md>), [transparency](<https://devfeed.tech/tags/transparency.md>)

### AI overview

MIT and Motional researchers developed CW-Net, a method that translates an autonomous vehicle's deep-learning decisions into understandable concepts. Tests found that the explanations helped safety drivers and nonexpert users better predict vehicle behavior.

### Source excerpt

A new method, called CW-Net, translates the reasoning process of an autonomous vehicle's AI system into understandable concepts that explain its behavior.

## Using Transformer Architectures for Motion Planning in Autonomous Vehicles

DevFeed: [Using Transformer Architectures for Motion Planning in Autonomous Vehicles](<https://devfeed.tech/articles/article-24863.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/yandex/articles/1052424/>)

Author: msporyshev (Яндекс)

Published: 2026-06-30T07:04:04Z

Content type: article

Language: ru

Sources: [Яндекс - Как мы делаем Яндекс / Статьи](<https://devfeed.tech/sources/source.md>)

Topics: [Machine learning](<https://devfeed.tech/topics/machine-learning.md>)

Tags: [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml](<https://devfeed.tech/tags/ml.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [self-driving](<https://devfeed.tech/tags/self-driving.md>), [tag-4004cf5948d3](<https://devfeed.tech/tags/tag-4004cf5948d3.md>), [transformers](<https://devfeed.tech/tags/transformers.md>)

### AI overview

The article explains how Yandex uses transformer-based architectures for motion planning in autonomous vehicles. It covers the difference between open-loop and closed-loop evaluation, the limits of prediction metrics, and the safety-focused validation process from machine-learning experiments through supervised real-vehicle testing.

### Source excerpt

Трансформеры уже умеют писать код, генерировать тексты и рисовать картины. Но могут ли они управлять автономным автомобилем в реальных городских условиях, среди людей и других машин? Меня зовут Максим, я руковожу службой поведения и предсказания движения в Автономном транспорте Яндекса. Отвечаю за задачу Motion Planning -- ту часть системы, которая решает, как именно должен двигаться автомобиль в следующие секунды. В этой статье я расскажу, как мы используем архитектуры на основе трансформеров в планировании движения и почему это сильно отличается от привычных задач генеративных моделей. Мы пройдём путь от первых ML-экспериментов до регулярных испытаний на реальных машинах. Разберём, чем Open Loop отличается от Closed Loop, почему качество предсказаний не определяет качество вождения и почему безопасность для нас важнее любой архитектуры. Читать далее

## How to SSH into a Self-driving Vehicle

DevFeed: [How to SSH into a Self-driving Vehicle](<https://devfeed.tech/articles/how-to-ssh-into-a-self-driving-vehicle-29678.md>)

Original publisher: [Read original article](<https://goteleport.com/blog/how-ssh-into-a-self-driving-vehicle/>)

Author: ben@goteleport.com (Ben Arent)

Published: 2020-04-30T00:00:00Z

Content type: tutorial

Language: en

Sources: [Teleport](<https://devfeed.tech/sources/teleport.md>)

Topics: [ssh](<https://devfeed.tech/topics/ssh.md>), [OpenSSH](<https://devfeed.tech/topics/openssh.md>), [Internet of things](<https://devfeed.tech/topics/iot.md>), [systems](<https://devfeed.tech/topics/systems.md>), [audit](<https://devfeed.tech/topics/audit.md>)

Tags: [audit](<https://devfeed.tech/tags/audit.md>), [best-practices](<https://devfeed.tech/tags/best-practices.md>), [connectivity](<https://devfeed.tech/tags/connectivity.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [iot](<https://devfeed.tech/tags/iot.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [openssh](<https://devfeed.tech/tags/openssh.md>), [self-driving](<https://devfeed.tech/tags/self-driving.md>), [ssh](<https://devfeed.tech/tags/ssh.md>)

### AI overview

This tutorial explains how to provide system-level SSH access for self-driving vehicles and other mobile IoT devices. It discusses connectivity options, bastion hosts, reverse SSH tunnels, fleet-scale access, OpenSSH, and Teleport, noting that reverse tunnels alone do not scale well.

### Source excerpt

You can SSH into self-driving robots using a reverse SSH tunnel, but this method only scales so far, and it requires more than 50 steps to set up.

## NTSB on Uber (Preliminary)

DevFeed: [NTSB on Uber (Preliminary)](<https://devfeed.tech/articles/ntsb-on-uber-preliminary-36911.md>)

Original publisher: [Read original article](<https://shostack.org/blog/ntsb-on-uber-preliminary/>)

Author: Adam

Published: 2018-05-25T00:00:00Z

Content type: opinion

Language: en

Sources: [Shostack & Friends Blog](<https://devfeed.tech/sources/shostack-friends-blog.md>)

Topics: [systems](<https://devfeed.tech/topics/systems.md>), [Algorithms, Complexity](<https://devfeed.tech/topics/algorithms-complexity.md>)

Tags: [report](<https://devfeed.tech/tags/report.md>), [screen](<https://devfeed.tech/tags/screen.md>), [self-driving](<https://devfeed.tech/tags/self-driving.md>), [system](<https://devfeed.tech/tags/system.md>), [systems](<https://devfeed.tech/tags/systems.md>)

### AI overview

A preliminary NTSB report on Uber's self-driving car fatality found that the vehicle detected the need to brake with enough time to stop automatically, but automatic braking had been disabled. The article also raises questions about preserving relevant computer-system data and algorithms.

### Source excerpt

[no description provided]