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code

my own implement of classical CNN architecture

didi-competition-solution

ROS nodes for visualization, calibration, car and passenger detection for Didi autonomous driving competition.

largescale-gps-trajectories-analysis-

This repository contains all the code used for processing large scale trajectory data as part of the research subject: Infrastructure Engineering Research Project CVEN900064 (Master of Engineering (Spatial) - Melbourne University)

pattern-mining-in-didi-trajectory-data

Trajectory period: 01/05/15- 05/05/15

predicting-transportation-modes-of-gps-trajectories

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features generation; (iii) trajectory features extraction; (iv) noise removal; (v) normalization. We show that the extraction of the new point features: bearing rate, the rate of rate of change of the bearing rate and the global and local trajectory features, like medians and percentiles enables many classifiers to achieve high accuracy (96.5%) and f1 (96.3%) scores. We also show that the noise removal task affects the performance of all the models tested. Finally, the empirical tests where we compare this work against state-of-art transportation mode prediction strategies show that our framework is competitive and outperforms most of them.

spatial-statistics

The repository contains methods and applications of spatial-statistics, like Fast and Adaptive Kernel Density Estimation for Hundreds of Millions of points

uctb

vehiclerecognition

zhaoguanwei.github.io