AGILE 2013 – Leuven, May 14-17, 2013

Reconstructing movement traces through a hybrid map-matching

algorithm

Understanding Urban Cycling: A Data Challenge

Kevin Baker

AGILE 2013 – Leuven, May 14-17, 2013

Research Framework

• Branding slogan: “Plan your nicest route”

– Specific information about the road infrastructure and surroundings focused on his application

AGILE 2013 – Leuven, May 14-17, 2013

Research Framework

• PhD research:

– “Mapping Linear Landscapes - Geosemantic methods for information extraction, validation and enrichment using dynamic geodata”

– intelligent aggregation and combination of novel geographic information from a dynamic community

AGILE 2013 – Leuven, May 14-17, 2013

Algorithm

AGILE 2013 – Leuven, May 14-17, 2013

Algorithm

AGILE 2013 – Leuven, May 14-17, 2013

Algorithm

AGILE 2013 – Leuven, May 14-17, 2013

Algorithm

• Software: FME / Python/OSRM Routing Engine

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Hybrid map-matching algorithm • Geographical: Point Search Algorithm

• Semantic: Attribute matching

• Topological: Shortest Path Routing Engine

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Vector Database:

– TomTom

• Preprocessing steps twofold: Routable dataset Point cloud

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Raw dataset

– Create plausible trips per PERSONID

• Time between registrations < 5 minutes

• Remove outliers/error: – HDOP < 5

– Distance between

registrations (<2500 m)

– outliers/error in Lat/Lon

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Raw dataset

– Analyse and filter trips on time passed and meanspeed

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Raw dataset

– Resulting trips (3302)

• PersonID

• TripID

• Starttime

• Endtime

• Meanspeed

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Point Search Algorithm

– Detect unambigious points along a trace:

• Dual carriage way

• Parallel roads

• Bearing difference

• Analyse closest

candidates

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Point Search Algorithm

– Variable parameters in function of quality:

• Dynamic search distance (B)

• Search interval (ΔA)

• Allowed bearing difference

• Number of closest candidates to analyse

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Similarity measure

– A is routed segment

– B is original segment of trace

A

B

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Similarity measures (Quality dependend threshold)

– Frèchet distance

– Relative/Absolute length difference

– Area between segments

– Turning function

AGILE 2013 – Leuven, May 14-17, 2013

Workflow

• Hybrid map-matching algorithm

AGILE 2013 – Leuven, May 14-17, 2013

Result: overview

Good similarity

Bad similarity

AGILE 2013 – Leuven, May 14-17, 2013

Result: overview

Good similarity Bad similarity

AGILE 2013 – Leuven, May 14-17, 2013

Result: comparison

• Individual trips

Created Trip TRIPID: 3034 Meanspeed: 4.88 Person : 207 Traveltime: 0:36:36

Additional trail TRIPID: 207-961 Person : 207 Traveltime: 0:16:00

AGILE 2013 – Leuven, May 14-17, 2013

Result: comparison

• Individual trips

Created Trip TRIPID: 1328 Meanspeed: 6.9955 Person : 146 Traveltime: 0:49:25

Additional trail TRIPID: 146-964 Person : 146 Traveltime: 0:15:00

AGILE 2013 – Leuven, May 14-17, 2013

Result: comparison

• Heatmap of ‘additional cycle trips’ (Raster) Max

Min

Remark: Pixelsize of 4m

AGILE 2013 – Leuven, May 14-17, 2013

Result: comparison

• Vector dataset with continuous color on count Max

Min

AGILE 2013 – Leuven, May 14-17, 2013

Result: comparison

AGILE 2013 – Leuven, May 14-17, 2013

Discussion and Research Outlook

• Customize routable data to specific activity – Exclude specific highwayclasses?

– Resistance on edges (fix vs variable)?

• Extensive post processing of delta (red lines) – How far can the automatic integration go?

– Crowdsourcing/Outsourcing?

• Fine-tuning the Point Search Algorithm

• Extend similarity measure and thresholds

• Resulting trip parameters

AGILE 2013 – Leuven, May 14-17, 2013

Q&A