autonomous driving

Cognitive Technology Team

Apr 1, 2025 · Artificial Intelligence

Four‑Second Bloodshed: How Autonomous Driving Algorithms Turned a Fatal Accident

A March 2025 crash involving a Xiaomi‑branded autonomous vehicle illustrates how a four‑second algorithmic decision loop, inadequate night‑vision sensors, flawed handover timing, and poor emergency‑exit design combined to create a lethal scenario that exposes the deadly risks of over‑relying on L2 driver‑assist systems.

AI safetyHuman-Machine InteractionL2 driver assistance

0 likes · 4 min read

Four‑Second Bloodshed: How Autonomous Driving Algorithms Turned a Fatal Accident

ByteDance Cloud Native

Mar 27, 2025 · Operations

Taming High Cardinality in AI & Autonomous Driving with Prometheus

This article shares practical experience from Volcengine's managed Prometheus service and its deep integration with large‑model and autonomous‑driving platforms, explaining what high cardinality is, its impact on monitoring systems, root causes, and a range of design, collection, and analysis techniques to mitigate it.

AIObservabilityPrometheus

0 likes · 12 min read

Taming High Cardinality in AI & Autonomous Driving with Prometheus

Amap Tech

Mar 19, 2025 · Artificial Intelligence

Driving by the Rules: Integrating Lane-Level Traffic Regulations into Online HD Maps

Gaode Map and Xi'an Jiaotong University introduce the “Driving by the Rules” task, releasing the MapDR benchmark that integrates lane‑level traffic‑sign regulations into online‑constructed HD maps, and provide modular (VLE‑MEE) and end‑to‑end (RuleVLM) baselines to evaluate rule extraction and lane association.

AIHD mapsautonomous driving

0 likes · 8 min read

Driving by the Rules: Integrating Lane-Level Traffic Regulations into Online HD Maps

IT Architects Alliance

Dec 19, 2024 · Artificial Intelligence

From Traditional IT Architecture Limitations to the Rise of Adaptive Intelligent Architecture

Traditional IT architectures suffer from manual, passive operations and limited scalability, prompting a shift toward adaptive intelligent architectures that leverage neural architecture search, elastic networks, and meta‑learning to dynamically adjust models across domains such as autonomous driving, mobile devices, robotics, and personalized recommendation, while addressing efficiency, generalization, and real‑time challenges.

Artificial IntelligenceNeural Architecture Searchadaptive architecture

0 likes · 18 min read

From Traditional IT Architecture Limitations to the Rise of Adaptive Intelligent Architecture

Python Programming Learning Circle

Nov 4, 2024 · Artificial Intelligence

Reinforcement Learning with highway‑env and Gym: DQN for Autonomous Driving

This tutorial explains how to install the gym and highway‑env packages, configure a highway simulation environment, process observations and actions, build a DQN network in PyTorch, train the agent, and analyze training results for autonomous driving scenarios.

DQNPythonautonomous driving

0 likes · 11 min read

Reinforcement Learning with highway‑env and Gym: DQN for Autonomous Driving

IT Services Circle

Jul 18, 2024 · Artificial Intelligence

Insights on Baidu’s “Robo Fast Run” Autonomous Driving Initiative and Related Career Opportunities

The article discusses Baidu’s new autonomous‑driving service “Robo Fast Run,” its potential impact on ride‑hailing jobs, the technical challenges involved, and provides detailed guidance on the qualifications and learning paths for engineers seeking positions in Baidu’s intelligent‑driving divisions.

AIBaiduCareer Advice

0 likes · 5 min read

Insights on Baidu’s “Robo Fast Run” Autonomous Driving Initiative and Related Career Opportunities

DataFunTalk

May 21, 2024 · Big Data

Applying Alluxio to Autonomous Driving Model Training: Deployment, Performance, and Operational Insights

This article details how Alluxio was adopted to replace NAS in autonomous driving model training, describing the data closed‑loop workflow, the challenges of the previous system, Alluxio's architectural benefits, deployment strategies across single and multiple data centers, functional and performance testing, operational tuning, and the resulting cost and efficiency gains.

AlluxioDistributed Storageautonomous driving

0 likes · 15 min read

Applying Alluxio to Autonomous Driving Model Training: Deployment, Performance, and Operational Insights

ZhongAn Tech Team

Apr 29, 2024 · Artificial Intelligence

Weekly Technology Overview: AI, Autonomous Driving, Cloud Models, Spatial Computing, and Industry Updates

This weekly technology roundup highlights major developments such as Momenta and Qualcomm's new autonomous driving solution, OpenAI's expansion in Asia, Tencent's integration of large AI models, rising interest in spatial computing, Nvidia's vision for affordable humanoid robots, breakthrough brain‑computer interface research, and notable industry and policy news.

AIIndustry newsRobotics

0 likes · 9 min read

Weekly Technology Overview: AI, Autonomous Driving, Cloud Models, Spatial Computing, and Industry Updates

Python Programming Learning Circle

Mar 28, 2024 · Artificial Intelligence

Tutorial: Setting Up highway‑env with OpenAI Gym and Training a DQN for Autonomous Driving

This article explains how to install the gym and highway‑env packages, configure the environment for various driving scenarios, define observations, actions and rewards, build a DQN network in PyTorch, run the training loop, and analyze the resulting performance metrics.

DQNautonomous drivinggym

0 likes · 9 min read

Tutorial: Setting Up highway‑env with OpenAI Gym and Training a DQN for Autonomous Driving

DataFunSummit

Mar 5, 2024 · Artificial Intelligence

Application and Practice of Large Models in Intelligent Electric Vehicles

The presentation by NIO senior technology planning expert Chen Jiong explores the development trends of intelligent electric vehicles, showcases how large AI models empower various automotive scenarios, and shares NIO's practical implementations, offering insights on industry-focused solutions, problem‑driven application, and unified architecture design.

Artificial IntelligenceLarge ModelsNIO

0 likes · 3 min read

Application and Practice of Large Models in Intelligent Electric Vehicles

Baidu Tech Salon

Dec 25, 2023 · Artificial Intelligence

Apollo Open Platform 9.0: New Features and Public Course Schedule

Baidu unveiled Apollo Open Platform 9.0 on December 19, delivering Package Management 2.0, new perception models with 4D millimeter‑wave radar support, incremental training, and a revamped Dreamview+ UI, and will host two live‑stream courses on December 27‑28 to explain the PnC and perception upgrades, with gifts for registrants.

AIApolloPlatform Upgrade

0 likes · 3 min read

Apollo Open Platform 9.0: New Features and Public Course Schedule

Amap Tech

Dec 21, 2023 · Artificial Intelligence

Creating a High-Quality Live Map for Intelligent Driving

At the fifth 2023 Mapping Technology Forum, Amap’s General Manager Xiang Zhe presented his report on creating a high‑quality ‘Live’ map, describing how the company’s HQ Live Map combines advanced perception with continuously refreshed map data to support intelligent driving and ADAS applications.

AIGeospatial DataHigh‑Definition Mapping

0 likes · 3 min read

Creating a High-Quality Live Map for Intelligent Driving

Amap Tech

Dec 4, 2023 · Artificial Intelligence

End-to-End BEV+Transformer Perception and Modeling for High-Definition Map Production

By fusing LiDAR point clouds and camera images into a unified bird‑eye‑view space and applying Transformer‑based perception, multi‑sensor fusion, and graph‑diffusion modeling, the proposed BEV+Transformer framework automatically detects and smooths ground‑level line features and signs for high‑definition maps with centimeter‑level accuracy, boosting production efficiency and reducing cost.

BEVHD mapTransformer

0 likes · 20 min read

End-to-End BEV+Transformer Perception and Modeling for High-Definition Map Production

Amap Tech

Nov 15, 2023 · Artificial Intelligence

Vision‑Based Bird’s‑Eye‑View (BEV) Representation and Solutions for Autonomous Driving

Vision‑based Bird’s‑Eye‑View (BEV) transforms camera data into a scale‑invariant, geometry‑friendly top‑down map using perspective‑transformation modules such as Lift‑Splat‑Shoot and Pseudo‑LiDAR, incorporates deformable convolutions and attention, and underpins modern autonomous‑driving detectors like BEVDet, BEVDepth, Detr3D, BEVFormer and PETR, while future research targets depth‑estimation bottlenecks, multimodal transformer fusion, and foundation‑model generalization.

3D PerceptionBEVautonomous driving

0 likes · 19 min read

Vision‑Based Bird’s‑Eye‑View (BEV) Representation and Solutions for Autonomous Driving

Zhengtong Technical Team

Sep 25, 2023 · Artificial Intelligence

Compliance Test Report of the "Qi Ji" Autonomous Driving Vehicle A2 According to Standard T/CSAE 285‑2022

On September 22, the self‑designed "Qi Ji" A2 autonomous vehicle for smart‑city data production was inspected by China Merchants Group Vehicle Technology Research Institute, passed all 11 major test items of the T/CSAE 285‑2022 functional‑type unmanned vehicle field test standard, and the detailed results are presented in this report.

AIStandardsautonomous driving

0 likes · 29 min read

Compliance Test Report of the "Qi Ji" Autonomous Driving Vehicle A2 According to Standard T/CSAE 285‑2022

Python Programming Learning Circle

Aug 5, 2023 · Artificial Intelligence

Building and Training a DQN Agent with highway‑env for Autonomous Driving Simulation

This article explains how to install gym and highway‑env, configure the environment, process state, action and reward data, build a DQN model in PyTorch, run training loops, and analyze results for autonomous driving simulations using reinforcement learning.

DQNPythonautonomous driving

0 likes · 10 min read

Building and Training a DQN Agent with highway‑env for Autonomous Driving Simulation

Didi Tech

Jun 27, 2023 · Artificial Intelligence

Highlights of the First Didi Industry-Academia Collaboration Forum and Gaia Lighthouse Project Awards (June 2023)

At a June 2023 forum in Beijing, Didi partnered with leading Chinese universities to showcase award‑winning projects that applied deep‑learning positioning, long‑term pricing models, high‑precision two‑wheel navigation, in‑vehicle voice separation, and data‑driven autonomous‑driving, illustrating how academia‑industry collaboration turns cutting‑edge research into commercial value.

Artificial IntelligenceDidiIndustry-Academia Collaboration

0 likes · 9 min read

Highlights of the First Didi Industry-Academia Collaboration Forum and Gaia Lighthouse Project Awards (June 2023)

DataFunSummit

Oct 19, 2022 · Artificial Intelligence

Series Six of the Integer Intelligence Autonomous Driving Dataset Collection – Overview and Highlights

This article presents a comprehensive overview of several publicly available autonomous driving datasets, focusing on Series Six of the Integer Intelligence collection, which includes StreetLearn, UTBM RoboCar, Multi‑Vehicle Stereo Event Camera, comma2k19, the Annotated Laser Dataset, Ford, and Oxford RobotCar, detailing their sources, download links, publication years, key features, and research relevance.

Roboticsautonomous drivingcomputer vision

0 likes · 10 min read

Series Six of the Integer Intelligence Autonomous Driving Dataset Collection – Overview and Highlights

Python Programming Learning Circle

Apr 6, 2022 · Artificial Intelligence

Building a DQN‑based Autonomous Driving Agent with highway‑env in Python

This tutorial explains how to install the gym and highway‑env packages, configure the simulation environment, process state and action representations, implement a DQN network in PyTorch, and train the model while visualizing performance metrics for autonomous driving tasks.

DQNPythonautonomous driving

0 likes · 11 min read

Building a DQN‑based Autonomous Driving Agent with highway‑env in Python

Tencent Cloud Developer

Mar 31, 2022 · Cloud Computing

Understanding Cloud Computing, Service Models, and Edge Computing Solutions

Cloud computing delivers on‑demand, pay‑as‑you‑go resources through IaaS, PaaS, and SaaS layers, while edge computing extends these services toward devices to meet latency, bandwidth, and privacy demands, using lightweight K3s‑based clusters that address management, connectivity, and resource constraints for applications such as autonomous driving.

5GAIEdge Computing

0 likes · 16 min read

Understanding Cloud Computing, Service Models, and Edge Computing Solutions