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Didi Tech

Jan 27, 2021 · Artificial Intelligence

Addressing Uncertainty in Autonomous Driving: Data‑Driven Control Module Strategies

The article proposes a three‑layer, data‑driven framework—problem analysis using massive fleet data, iterative deep‑learning algorithm development with fallback and explainable‑AI safeguards, and systematic validation via simulation and real‑world tests—to mitigate perception, prediction, and control uncertainties and advance trustworthy autonomous‑driving control systems.

autonomous drivingcontroldata-driven

0 likes · 12 min read

Addressing Uncertainty in Autonomous Driving: Data‑Driven Control Module Strategies

DataFunTalk

Feb 27, 2020 · Artificial Intelligence

Technical Challenges in Planning and Control for Autonomous Heavy Trucks

The article reviews the complex system model of autonomous heavy trucks, outlines traditional and modern planning and control methods—including rule‑based FSM, POMDP, learning‑based and optimization techniques—highlights safety, efficiency, fuel‑economy, and dynamic modeling challenges specific to heavy‑truck and trailer configurations, and shares practical attempts such as lane‑changing, merging, and trailer‑aware trajectory planning.

POMDPautonomous drivingbehavioral planning

0 likes · 13 min read

Technical Challenges in Planning and Control for Autonomous Heavy Trucks

DataFunTalk

Nov 8, 2019 · Artificial Intelligence

Balancing Safety and Comfort in Autonomous Driving: Planning and Control Optimization

This article explores how autonomous driving systems can simultaneously ensure safety and passenger comfort by optimizing planning and control modules, defining safety and comfort metrics, formulating constraints and cost functions, and employing models such as the bicycle model for lateral and longitudinal control.

Safetyautonomous drivingbicycle model

0 likes · 12 min read

Balancing Safety and Comfort in Autonomous Driving: Planning and Control Optimization