Supplemental Material: Geographical Cellular Traffic (GCT) dataset

This is the original data repository of Geographical Cellular Traffic.

The dataset materials are provided in the following.

Acknowledge

This work was supported in part by National Science and Technology Council, Taiwan, under Grant NSTC 111-2634- F-002-022 and by Qualcomm through a Taiwan University Research Collaboration Project.

This prototypical dataset cooperated with Chunghwa Telecom laboratories

DEMO Playground

https://cylin-cmlab.github.io/GCT-flow-demo

Overview

The experimental code will be public in ./Model

GCT

GCT is cellular traffic with estimated GPS coordinates obtained from triangulation, indicating where the traffic was generated. Each GCT is classified\footnote{The algorithm is the telecom company's confidential trade secret.} into three categories: vehicle, pedestrian, and stationary.

Here are the partial examples of GCT records (*IMEI numbers were hashed to protect privacy):

IMEI	Latitude	Longitude	Time	Type
...	...	...	...	...
gn...mE	24.78585	120.98825	09/25 17:59:58	vehicle
gn...GI	24.78601	120.98838	09/25 18:00:00	pedestrian
gn...mU	24.78608	120.98829	09/25 18:00:05	stationary
...	...	...	...	...

Road segment

The road segments are defined as 20m x 20m areas, which is based on the average road size in our proof-of-concept (POC) area in Hsinchu, Taiwan. All the GCTs listed in the above table are located within the predefined road segments, nearby various regional functionality.

Here are the distribution examples of selected road segments:

GCT Flow

We define GCT flow as the total quantity of GCT within a fixed interval (e.g., 5 minutes) using public traffic flow datasets.

Below are partial examples of GCT flows for different road segments:

With multi-type GCT (as shown in the "Type" data field in the table above), there are various GCT flows, including vehicle (V-GCT), pedestrian (P-GCT), and stationary (S-GCT) flows.

Here is an example of the multi-type GCT flows for one road segment:

Experimental Materials Providing

I. Graph Structure of Road Segments Network

We provide instructions on how to construct a road segment network in the Hsinchu POC area:

1. GPS coordinates for each road segment ID: We provide the ID and corresponding GPS coordinates for each road segment, available at: Google Drive

2. Distance between connected road segments (in meters): We provide a file containing the distances between each pair of road segments, available at: Google Drive

3. Graph structure construction: To generate the graph structure based on the distances.txt file provided above, please follow the script.

We also provide a road network structure file for use in the experiments, available at: Google Drive

II. Muti-type GCT flows dataset for training

There are three types GCT flows, which are based on Type in GCT table to calculate seperately.

1. V-GCT flow: The original CSV file for V-GCT flow is available on: Google Drive

Here are the partital examples of V-GCT flow:

	Road Segment 1	Road Segment 6	Road Segment 11	...
2022/08/28 00:05:00	8.0	3.0	12.0	...
...	...	...	...	...
2022/08/28 19:05:00	55.0	12.0	46.0	...
2022/08/28 20:05:00	77.0	12.0	41.0	...
2022/08/28 20:10:00	60.0	20.0	20.0	...
...	...	...	...	...

2. P-GCT flow: The original CSV file for P-GCT flow is available on: Google Drive

3. S-GCT flow: The original CSV file for S-GCT flow is available on: Google Drive

To generate the train/val/test datasets for each type of GCT flow as {train,val,test}.npz, please follow the script, using the CSV files provided above.

The processed train/val/test data structures are available on: Google Drive

Examples of Potential for Intelligent Tranportation System

I. Real-time monitoring:

GCT flow can be used to monitor crowd density and mobility on each road segment. During peak hours or festivals, it can monitor crowd activities to ensure public safety.

II. Emerging traffic indicator:

GCT flow can be regarded as a traffic performance indicator. When the number of GCT flows exceeds a predefined threshold at a certain time, it can alert the transportation authority to respond and ensure efficient allocation of traffic resources, reducing road congestion, and so on.

We provide these initial potential applications, hoping to pave the way for the application of GCT in transportation management!