7/31/2019 Tracking and mapping cyclists behaviours - what GNSS can do

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PRELIMINARYRESULTS

Spatial analysis of cyclewaycorridor space characteristics vis-

-vis route choices of participants

35.1% of cycle trips: off the officialnetwork.

55.1% of cycle trips: on the official

network.

9.8% of cycle trips: close to official

network.

907 detected cycle trips from 76 utility

cyclists (304 trips by females; 603 made

by males).

Total computed distances of all the

identified cycle tracks is 4,466km.

INTRODUCTION

GNSS infrastructure offers an

indispensable means to collect spatial

temporal data at different scales and in

different settings adding new layers of

knowledge to urban studies (Van derSpek et al., 2009); which may help in

understanding urban transportation with

very low impact on the environment.

The obstacles to everyday cycling [utility

cycling] are primarily related to the

environment in which it takes place.

(Docherty & Shaw, 2008, p. 125).

Bottom-up approach to understanding

cycling can help strategic investment in

cycle infrastructure; but, more empirical

evidence is needed.

More scientific empirical evidence isneeded about cyclists perception and

experiences on route/destination choices;

to support urban designers as well as

cycling policy interventions and

transportation engineers and thereby

increase cycling uptake (Skinner & Rose,

2007; Forsyth & Krizek, 2011).

STUDYAREA

Fieldwork planning

Five major planning phases (see Fig. 2)

Preparation: designed and testedmaterials with 7 participants. Four GPS

devices were evaluated and one chosen

(see Fig. 3) for the main survey

Invitation: 350 emails were collated and

used for the field campaign (including

bicycle user group lists of Northumbria

and Newcastle Universities)

Screening and recruitment: Utility cyclists

were screened and invited for face-to-face

meeting.

Data collection: one week data collection

Data cleaning by visual inspection

All logged points time on 02:00:00

(HH:MM:SS) UTC time is corrected

backwards to 01:00:00 (HH:MM:SS) UTC

time the same day to reflect local time.

In order to get clean data which is not that

messy to enable data analysis, visual

inspection method for data cleaning was

introduced (see example in Fig. 5)

Visual inspection approach: Raw data

from GNSS device is imported into Space-

Time-Cube (STC) in GeoTime software.

The GPS tracks are inspected using filled

travel diaries and secondary data such asopenstreetmap.

Godwin Yeboah, Northumbria University at Newcastle upon Tyne.

AIMOF RESEARCH

The aim of the study is to understand how

the built environment constrains or

supports the movement behaviour of

cyclists in urban environments.

FURTHERWORK Exploratory analysis of collected data

Analysis and visualisation of revealed

movement patterns (i.e., actual route and

destination choices) using Space-Time

Cube

Reconstruction of travel behaviour of

cyclists using agent based modelling and

simulation (ABMS) techniques Cycle

Track Modelling (CTM)

Tracking cyclists travel behaviour

81 Participants (i.e., Utility Cyclists) carried /

use the GNSS device while filling self-

administered questionnaire forms (see Fig.

4).

Data collection wave: October November

2011. Participation: 81 out of 118 cyclists

The portable GNSS device used is an

assisted GPS, A-GPS, capable; meaning it

can use available network resources to

identify and use satellites under low/poor

signal situations

Comment from a participant with ID 148: No

problem into day 2 cycled in

today despite the weather

FORFURTHERINFORMATION

Supervisors: Dr. Seraphim Alvanides and Dr. Emine M. Thompson,School of Built and Natural Environment, Northumbria University.

PhD Student: godwin.yeboah@northumbria.ac.uk

PhD Research Blog: http://godwinyeboah.blogspot.com

GNSS BASED TRACKINGAND DATACLEANING METHODS

OFF/

NAV/OFF

optionsBattery

status LED

(Red/Green)

GPS status LED

Power jack (mini USB)

Charging GPS

with mini USB

cable to the

PC/laptop/etc.

Cleaned DATANot MESSY!RAW DATAMESSY!

TO

30th Oct. 2011

(Time Change !!!)

Fig. 5:An example of visual inspection showing GPS raw data (left)

and processed data (left) in space time cube in GeoTime Software

Fig. 6: Corridor space

definitions using a map:

Blue for cycle trips on

network (10m buffer

around network), green for

cycle trips close to network(10-20m buffer) and red is

for cycle trips off the

network (outside buffers).

GNSS device placed at

top compartment of bag

GNSS device placed in the

pocket

GNSS device placed on

key ring

Fig. 3:

GNSS

device

used

Fig. 4: How

GNSS

device was

carried by

Participants

SELECTEDREFERENCESForsyth, A. & Krizek, K. (2011) 'Urban Design: Is there a Distinctive View

from the Bicycle?', Journal of Urban Design, 16 (4), pp. 531-549.

Van der Spek, S., Van Schaick, J., De Bois, P., & De Haan, R. (2009).Sensing Human Activity: GPS Tracking. Sensors, 9(4), 3033-3055.

ACKNOWLEDGMENTSpecial thanks to Northumbria University for funding this project. To all thosewho participated in the survey, special thanks for your support. Thanks toOculus Info, Inc for providing GeoTime Software under special license for thisresearch. Many thanks to Gfg2 team for printing this poster and sponsoring mefor the summer school.

Fig. 2: Fieldwork planning architecture

Backgroundmap: GoogleMaps 2012

HOME

WORK/SCHOOL

STUDY AREA

LEGEND

Overview

Fig. 1: The study area of the research covers the city centre of

Newcastle upon Tyne and part of Gateshead; the centre of

Tyneside conurbation.

Visual

inspection

of GNSS

raw data

Processed

/ refined

data

Screening

Processing

&

Analysis

Stepwise flow

(main survey)

Stepwise flow

(during testing)

Recruitment

Data

collection

Planning

&Preparation

Invitation

Extensive piloting ofsurvey instruments

with 7 participants

Evaluated 4 GPS

devices: i-gotU GT-600;Atmel BTT08; Canmore

GT-750 (L); and Qstarz

BT-Q1000XT (selected)

mailto:godwin.yeboah@northumbria.ac.ukhttp://godwinyeboah.blogspot.com/http://godwinyeboah.blogspot.com/http://godwinyeboah.blogspot.com/mailto:godwin.yeboah@northumbria.ac.uk