# US 2021/0176597 A1 · Trajectory Analysis With Mode Of Transportation Analysis

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- Number: US 2021/0176597 A1
- Document ID: US20210176597A1
- Status: Published application
- Kind: A1
- Application number: 16/470,235
- Filed: 2017-09-27
- Published: 2021-06-10
- Earliest claimed: 2017-02-17
- Assignees: DataSpark, Pte. Ltd.
- Applicants: Dataspark Pte Ltd
- Inventors: Ying LI; The Anh DANG
- Web page: https://patentgrep.com/patent/US20210176597A1

## CPC

- G08G 1/012: {from other sources than vehicle or roadside beacons, e.g. mobile networks}
- H04W 4/027: {using movement velocity, acceleration information}
- G01C 21/343: {Calculating itineraries (travelling salesman problem G06Q10/04; optimisation of routes G06Q10/047)}
- G01C 21/3815: {Road data}
- G06F 18/2148: {characterised by the process organisation or structure, e.g. boosting cascade}
- G08G 1/0129: {for creating historical data or processing based on historical data}
- G08G 1/0133: {for classifying traffic situation}
- G08G 1/0145: {for active traffic flow control}
- H04W 4/029: Location-based management or tracking services
- H04W 4/42: for mass transport vehicles, e.g. buses, trains or aircraft
- G01C 21/3407: {specially adapted for specific applications}
- G01C 21/3841: {Data obtained from two or more sources, e.g. probe vehicles}
- G08G 1/123: indicating the position of vehicles, e.g. scheduled vehicles; {Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams}(transmission of navigation instructions to vehicles G08G1/0968)
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)
- G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

Machine learning techniques may be applied to determining a mode of transportation for a trajectory of a sequence of user locations. The mode of transportation, such as walking, bicycling, riding in a car or bus, riding in a train, or other mode, may be determined by creating a training set of data, then using classification mechanisms to classify trajectories by mode of transport. The training set may be generated by tracking then verifying a user's transportation mode. In some cases, a user may manually input or verify their transportation mode, while in other cases, a user's transportation mode may be determined through other data sources.

## Claims

### Claim 1

A method performed on at least one computer processor, said method comprising:
building a training set comprising:
determining a trajectory segment for a user, said trajectory segment comprising a sequence of timestamped locations;
determining a transport mode for said user;
storing said trajectory segment and transport mode in said training set;
determining a transport mode for a new trajectory by a method comprising:
receiving said new trajectory, said new trajectory having an unknown transport mode;
comparing said new trajectory to said training set to determine a first transport mode for said new trajectory.

### Claim 2 (depends on 1)

The method of claim 1 further comprising:
receiving said sequence of timestamped locations for said user;
determining a plurality of segments of said sequence, each of said plurality of segments representing a different transportation mode.

### Claim 3 (depends on 2)

The method of claim 2 further comprising:
determining a first transportation mode for a first trajectory segment of said sequence.

### Claim 4 (depends on 3)

The method of claim 3 further comprising:
transmitting a first segment descriptor to said user for a first trajectory segment; and
receiving a first transportation mode for said first trajectory segment.

### Claim 5 (depends on 3)

The method of claim 3 further comprising:
determining a first transportation mode for said first trajectory segment by identifying mode-specific locations within said sequence of timestamped locations.

### Claim 6 (depends on 5)

The method of claim 5, said mode-specific locations comprising locations accessible through a single transportation mode.

### Claim 7 (depends on 6)

The method of claim 6, said mode-specific locations comprising one of a group of:
a location accessible from a bus;
a location accessible from a taxi; and
a location accessible from a train.

### Claim 8 (depends on 2)

The method of claim 2 further comprising:
identifying a first trajectory segment within said plurality of segments by identifying a first transportation mode change point and a second transportation mode change point.

### Claim 9 (depends on 8)

The method of claim 8, said first transportation mode change point being one of a group composed of:
a bus stop;
a train station;
a parking lot; or
a taxi drop off point.

### Claim 10 (depends on 1)

The method of claim 1, said transportation mode comprising one of a group composed of:
walking;
riding a bus;
riding a car;
riding a taxi;
riding a train;
rising a ferry; and
bicycling.

### Claim 11

A system comprising:
a first computer processor;
a training set creator operating on said first computer processor, said training set creator configured to perform a method comprising:
determining a trajectory segment for a user, said trajectory segment comprising a sequence of timestamped locations;
determining a transport mode for said user;
storing said trajectory segment and transport mode in said training set;

### Claim 12 (depends on 11)

The system of claim 11, said method further comprising:
receiving said sequence of timestamped locations for said user;
determining a plurality of segments of said sequence, each of said plurality of segments representing a different transportation mode.

### Claim 13 (depends on 12)

The system of claim 12 said method further comprising:
determining a first transportation mode for a first trajectory segment of said sequence.

### Claim 14 (depends on 13)

The system of claim 13 said method further comprising:
transmitting a first segment descriptor to said user for a first trajectory segment; and
receiving a first transportation mode for said first trajectory segment.

### Claim 15 (depends on 13)

The system of claim 13 said method further comprising:
determining a first transportation mode for said first trajectory segment by identifying mode-specific locations within said sequence of timestamped locations.

### Claim 16 (depends on 15)

The system of claim 15, said mode-specific locations comprising locations accessible through a single transportation mode.

### Claim 17 (depends on 16)

The system of claim 16, said mode-specific locations comprising one of a group of:
a location accessible from a bus;
a location accessible from a taxi; and
a location accessible from a train.

### Claim 18 (depends on 12)

The system of claim 12 said method further comprising:
identifying a first trajectory segment within said plurality of segments by identifying a first transportation mode change point and a second transportation mode change point.

### Claim 19 (depends on 18)

The system of claim 18, said first transportation mode change point being one of a group composed of:
a bus stop;
a train station;
a parking lot; or
a taxi drop off point.

### Claim 20 (depends on 11)

The system of claim 11, said transportation mode comprising one of a group composed of:
walking;
riding a bus;
riding a car;
riding a taxi;
riding a train;
rising a ferry; and
bicycling.