map matching | BestHub

JD Tech

Jun 17, 2021 · Artificial Intelligence

MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi‑Task Learning

The paper introduces MTrajRec, a Seq2Seq multi‑task learning framework that simultaneously restores low‑sampling‑rate GPS trajectories to high‑sampling‑rate and aligns them to the road network, achieving more accurate and efficient trajectory recovery for downstream applications such as navigation and travel‑time estimation.

Deep LearningKDD 2021map matching

0 likes · 9 min read

MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi‑Task Learning

Didi Tech

Sep 29, 2020 · Artificial Intelligence

Technical Overview of Didi’s MJO 3D Panoramic Navigation, Main/Sub‑Road Yaw Detection, and Deep‑Learning‑Based Navigation Engine

Didi’s Navigation system combines a novel MJO 3D panoramic map with advanced data‑compression and octree rendering, precise main/sub‑road yaw detection using LSTM‑based models trained on GPS and image data, and a lightweight deep‑learning engine optimized for mobile CPUs/GPUs, delivering accurate, real‑time guidance for ride‑hailing and autonomous driving.

3D renderingDeep LearningGPS trajectory

0 likes · 21 min read

Technical Overview of Didi’s MJO 3D Panoramic Navigation, Main/Sub‑Road Yaw Detection, and Deep‑Learning‑Based Navigation Engine

Zhengtong Technical Team

Dec 20, 2019 · Big Data

Optimizing Trajectory Visualization: From Data Collection to Rendering

This article examines the challenges of mobile‑based trajectory tracking in city management and presents a comprehensive set of optimizations—including adaptive GPS sampling, keep‑alive strategies, accuracy enhancements, algorithmic fitting, and cinematic animation effects—to produce smooth, accurate, and visually appealing trajectory displays at scale.

Data OptimizationGPSKalman filter

0 likes · 11 min read

Optimizing Trajectory Visualization: From Data Collection to Rendering

Amap Tech

Aug 13, 2019 · Artificial Intelligence

Multi‑Sensor Fusion Positioning for Vehicle Navigation: GPS/IMU/Map‑Matching Solution

Gaode's solution combines GPS, IMU, odometer, visual sensors with map‑matching using a Kalman filter, addressing yaw drift, loss of fix, and road‑capture errors in vehicle navigation, especially in urban canyons, achieving over 90% road identification and significant error reductions while keeping hardware costs low.

GNSSIMUKalman filter

0 likes · 16 min read

Multi‑Sensor Fusion Positioning for Vehicle Navigation: GPS/IMU/Map‑Matching Solution

Amap Tech

Jun 28, 2019 · Fundamentals

Road Matching: Definitions, Applications, and Key Algorithms

Road matching, a core subset of map‑matching theory, aligns GPS points to the correct road segments using algorithms such as distance‑based measures, Fréchet‑distance global optimization, and Hidden Markov Models, enabling accurate navigation, heterogeneous data fusion, traffic analysis, and urban planning, as validated by ACM SIGSPATIAL competitions.

Fréchet distanceGISHMM

0 likes · 11 min read

Road Matching: Definitions, Applications, and Key Algorithms