Development of a New Intelligent Algorithm to Improve Autonomous Car Operation
Autonomous Driving Systems (ADS) are transforming modern transportation by enabling safer, more efficient vehicle operation.
Engineering 5.5 · Research 8.0 · Business 5.5
Path planning and motion planning for autonomous vehicles — route planning, trajectory optimization, decision-making and planning in complex urban traffic.
Autonomous Driving Systems (ADS) are transforming modern transportation by enabling safer, more efficient vehicle operation.
Engineering 5.5 · Research 8.0 · Business 5.5
This paper presents a radial basis function network (RBFN)-informed motion planning framework for safe and efficient urban autonomous driving.
Engineering 5.0 · Research 7.0 · Business 5.0
Current research indicates that collaborative decision-making and control across several vehicles can markedly enhance traffic efficiency and driving safety.
Engineering 5.0 · Research 7.0 · Business 5.0
An autonomous driving research paper: IntelliFly: Multi-UAV Cooperative Path Optimization for IoT-enabled Energy-efficient Smart Agriculture.
Engineering 5.0 · Research 7.0 · Business 5.0
To address this issue, A Search-Resampling-Enhanced Iterative Optimization (SREIO) framework is proposed in this paper.
Engineering 5.0 · Research 8.0 · Business 5.0
Introduction Autonomous navigation of crawler tractors is essential for precision agriculture; however, existing systems often face a trade-off between path-tracking accuracy and steering stability, particularly under complex field conditions.
Engineering 5.0 · Research 7.0 · Business 5.0
To tackle this problem, we propose HGeo-TopoMap, which leverages an explicit prior map and implicit spatial relations to hierarchically boost topological mapping.
Engineering 7.0 · Research 7.0 · Business 5.5
An autonomous driving research paper: DVFA-RRT*: A Progress-Driven Hybrid Sampling Approach for 3D Trajectory Planning and Obstacle Avoidance.
Engineering 5.0 · Research 7.0 · Business 5.0
Autonomous driving has become a transformative technology poised to reshape modern transportation systems.
Engineering 5.5 · Research 7.0 · Business 5.0
Diffusion-based trajectory planners achieve strong nominal performance in autonomous driving, but sparse safety intervention remains difficult to evaluate and realize effectively.
Engineering 5.0 · Research 7.0 · Business 5.0
In this work, we propose GeoWorldAD, a geometry world action model that grounds trajectory planning in ego-aligned 3D space and anticipates short-horizon scene evolution with latent future geometry tokens.
Engineering 5.0 · Research 8.0 · Business 5.0
This paper presents TSC-VP-STO, a task-space-constrained extension of VP-STO that replaces the strict terminal joint-space constraint with a task-space constraint, jointly optimizing the trajectory and the redundant degrees of freedom of the terminal configuration.
Engineering 5.5 · Research 7.0 · Business 6.5
We present DRIFT, a fixed-depth planner that combines one-step drifting in a compact trajectory latent space with scene-aware proposal aggregation.
Engineering 5.5 · Research 7.0 · Business 5.0
To address this limitation, we propose the S-squared-VLA, which explicitly decouples the semantic and spatial streams in Vision-Language-Action models.
Engineering 5.0 · Research 8.0 · Business 5.0
This paper proposes a hybrid architecture that integrates game-theoretic reasoning into a sampling-based motion planner, combining strategic interactions with robust trajectory generation.
Engineering 5.0 · Research 7.0 · Business 5.0
In this paper, we present BucketKD, a bucket-based knowledge distillation framework that yields compact and safety-aware end-to-end planners.
Engineering 6.0 · Research 8.0 · Business 6.0
An autonomous driving research paper: Path Planning Algorithm for Self-Driving Cars Based on High-Precision Maps and Improved A*.
Engineering 5.0 · Research 7.0 · Business 5.0
Agriculture 5.0 represents a breakthrough transformation from Agriculture 4.0, addressing the needs for safety, sustainability, and resilience in human–robot collaboration in agriculture.
Engineering 5.0 · Research 7.0 · Business 6.0
We present a Reliable Context-Aware and Temporal Planning framework for Autonomous Driving (RCT-AD) that explicitly models feature quality and temporal consistency to support safer, more consistent planning.
Engineering 6.5 · Research 7.0 · Business 6.0
This work presents an efficient motion planning framework for four-wheel steering (4WS) autonomous vehicles operating in complex and unknown environments.
Engineering 5.0 · Research 7.0 · Business 5.0