Fast map matching, an open source framework in C++
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Updated
Jul 9, 2024 - C++
Fast map matching, an open source framework in C++
Interface to OpenStreetMap (load maps, extract road connectivity, plot road network & find shortest path)
The source of the IJCAI2017 paper "Modeling Trajectory with Recurrent Neural Networks"
Easy-to-build realistic roads in Unity. Foundation of any simcity game.
Fast shortest path calculations for Rust
Source code for Spatio-Temporal Trajectory Similarity Learning in Road Networks. KDD 2022.
Pure-python package for map matching
General Modeling Network Specification
QuadTree Model for generating random road network
Convert Shapefile to the Network and find number of shortest paths
Road Network Enhanced Trajectory Recovery with Spatial-Temporal Transformer (ICDE'23)
OSM XML file to road graph converter
This project consists of implementations of several kNN algorithms for road networks (aka finding nearest points of interest) and the experimental framework to compare them from a research paper published in PVLDB 2016. You can use it to add new methods and/or queries or reproduce our experimental results.
[CVPR 2023] Repository for the UrbanLaneGraph Dataset & Benchmark and the LaneGNN approach
Summary of Spatio-Temporal Representation Learning Models.
Tackle the problem of traffic congestion by monitoring the traffic flow and congestion and providing useful traffic congestion related information
Package with functions to pull sensor data, sensor IDs, and sensor configuration for MnDOT metro district
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