Download - Using telematics data to research traffic related air pollution

BIG telematics dataVehicle tracking

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Sources:• Fleet surveillance e.g.

• TfL iBus data• Eddie Stobbart• Taxis*

• Insurance industry• GPS and CAN/OBD link

‘white box’ tracking• Second-by-second (1Hz)• Young driver bias• Data anonymised

* Nyhan, M., Sobolevsky, S., Kang, C., Robinson, P., Corti, A., Szell, M., Streets, D., Lu, L., Britter, R., Barrett, S., Ratti, C. 2016. Predicting vehicularemissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model. Atmospheric Environment 140(2016) 352-363. http://dx.doi.org/10.1016/j.atmosenv.2016.06.018

BIG telematics datawww.thefloow.com| insights from telematics and mass mobility analysis

3 Chapman, S. 2016. Vehicular Air Pollution: Insights from telematics and mass mobility and analysis. The FloowLtd. Routes to Clean Air Conference, Bristol, October 2016https://www.slideshare.net/secret/km7kcqE8oHtrn9

BENEFITSBIG telematics data

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Emission assessmentsaccount for local, real-driving conditions:

• Network-wide: Noboundaries

• Vehicle acceleration,deceleration, cruising &idling

• Variability in traffic flow• Month of year• Day of week• Hour of day• Holidays• Special events• Weather• etc

FIGURE | Sample weekday GPS data byhour

BACKGROUND WORKModelling vehicle movements & emissions

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0 100 200 300 400 500

02

040

6080

Spee

d (k

m. h-1

)

0 100 200 300 400 500

012

34

56

7

CO2(

g.s e

c-1)

0 100 200 300 400 500

0.00

0.02

0.04

0.06

Time (seconds)

NOX(

g.s e

c-1)

UNDER-PINNING ";��-+ ;-."!�� "�� ;�� (6";&

Passengercar and Heavy-duty Emission Model (Euro 0 –6 / VI)FIGURES | Sample time series, TfLLondon Drive Cycle, Euro 5 diesel MPV

Modelled_NOx

Obse

rved

_NO x

0.00

0.01

0.02

0.03

0.00 0.01 0.02 0.03

Counts

112357

111623345175

111165244361535

Modelled_CO2

Obse

rved

_CO

2

0

2

4

6

8

0 2 4 6 8

Counts

1123468

11162231436186

121171241

Zallinger, M., Tate, J., Hausberger, S. 2008. An instantaneous emission model for the passengercar fleet. Transport & Air Pollution conference, Graz 2008

Moody, A., Tate, J. 2017. In Service CO2 and NOX Emissions of Euro 6/VI Cars, Light- andHeavy- duty goods Vehicles in Real London driving: Taking the Road into the Laboratory.Journal of Earth Sciences and Geotechnical Engineering 7(1):51-62 01 Jan 2017.

CASE STUDIESBIG telematics data

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• Leeds Clean Air Zone study• One calendar year (May 2015 – May 2016)• 56,000 kms quality checked telematics data• Supporting data

• Automatic Traffic Count (ATC) data (Leeds CC on A58M)

• Log special events, incidents etc.

• Turning proportions from 2015 traffic model (SATURN)

• Detailed fleet analysis from ANPR study (April 2016)

• Met. (wind speed, direction, temp, RH, rainfall)

• Sheffield City Centre• One calendar year (May 2014 – May 2015)• 15,000 kms quality checked telematics data• Supporting data

• Met. (wind speed, direction, temp, RH, rainfall)

SHEFFIELD RESULTSVariability in driver behaviour by HOUR of day

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FIGURE | Variation in positive VSP with HOUR of the day

NOTE: Vehicle Specific Power (VSP) is the sum of the engine loads (aerodynamicdrag, acceleration, rolling resistance, hill climbing) divided by the mass of the vehicle

SHEFFIELD RESULTSVariability in driver behaviour on HOLIDAYS

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FIGURE | Variation in positive VSP with type of DAY / HOLIDAY

SHEFFIELD RESULTSInfluence WEATHER conditions

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FIGURE | Variation inpositive VSP with

RAINFALL

NOTE: Local, hourly weather data obtained from UK Met Office datasets

FIGURE | Variation inpositive VSP withTEMPERATURE

LEEDS CLEAN AIR ZONE STUDY 2017

METHOD

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'Raw' telematics

data

Temporal & Spatial

variation in VEHICLE

EMISSIONS

DATA CLEANING

Kalman filter > SPEED& ACCELERATION

+ GRADIENT

INSTANTANEOUSEMISSION MODEL

[PHEM]

LINK EMISSION FACTORS (EFs)grams.km-1 all

vehicle sub-types

WEIGHTING& SCALING EFs

by local Fleet Mix & Flowin time slices

Day typeSchool term time:

- AutumnA + B- Spring A + B

- Summer A + BSchool half-terms (all)

Christmas holidayEaster holiday

Summer holidayBank holidays

Special events [X, Y, Z]

DATAFORMAT

PHEM compatible

ANPR dataFleet mix and specification

Traffic Count data

Automatic

TIME SLICE00:00 to 06:00

36 half-hour periods:06:0006:3007:0007:3008:0008:3009:00

etc23:30

FLEET MIXProportions vary by

hour & week / weekend

A58(M) TURNING %Output SATURN

2015

CLASSIFIED LINK FLOWS

all segment IDs

DIGITAL TERRAIN MAP

0.5m gridlink GRADIENTS

METHODBIG telematics data ▶ vehicle emissions process (START)

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'Raw' telematics

data

DATA CLEANING


+ GRADIENT


[PHEM]







DATAFORMAT

PHEM compatible

ANPR dataFleet mix and specificationTIME SLICE

00:00 to 06:0036 half-hour periods:

06:0006:3007:0007:3008:0008:3009:00

etc23:30

DIGITAL TERRAIN MAP


METHODBIG telematics data ▶ vehicle emissions process (END)

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Temporal & Spatial


EMISSIONS


[PHEM]


vehicle sub-types




Traffic Count data

Automatic




2015


all segment IDs

SUPPORTING DATATraffic flow on A58(M): LEEDS CC Automatic Traffic Count (ATC) site

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BIG telematics dataHow good is the data?

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• Pair contrasting North-South journeys (3 of 56,000 kms data)

BIG telematics dataHow good is the data?

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• Pair contrasting North-South journeys (3 of 56,000 kms data)

LEEDS RESULTSPassenger car NOX Emission Factors (EFs)

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FIGURE | Average (all trajectories) passenger car NOX and NO2 EmissionFactors (EFs)

LEEDS RESULTSPassenger car NOX Emission Factors (EFs)

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FIGURE | Passenger car NOX Emission Factors (EFs) all journeys

LEEDS RESULTSVariation in time & space

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FIGURE | Autumn term-time (first half) 08:00 Q >G�B> �� Direction South BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 08:00 Q >G�B> �� Direction North BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 12:00 Q 5��B> �� Direction South BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 12:00 Q 5��B> �� Direction North BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 17:00 Q 5I�B> �� Direction South BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 17:00 Q 5I�B> �� Direction North BoundPassenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors

WORK IN PROGRESSLeeds CAZ study

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• Key tasks:• Sampling “calmer” driving trajectories estimate LGV, HGV & Bus

trajectories• Weighting & scaling time & space varying EFs by classified flow levels• Clean Air Zone scenarios• Primary NO2 fraction sensitivity testing

'Raw' telematics

data

Temporal & Spatial


EMISSIONS

DATA CLEANING


+ GRADIENT


[PHEM]


vehicle sub-types









DATAFORMAT

PHEM compatible


Traffic Count data

Automatic

TIME SLICE00:00 to 06:00

36 half-hour periods:06:0006:3007:0007:3008:0008:3009:00

etc23:30




2015


all segment IDs

DIGITAL TERRAIN MAP


OUTLOOKBIG telematics data

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SHORT-TERM: Target Case Study applications• Traffic management interventions

• Variable Speed Limits (VSL) & ‘Smart’ motorways• Demand management to alleviate congestion• Smoothing traffic flow including ecoDriving

• Complex, unstable, congested networks• Challenging to observe & model traffic flow e.g. Leeds Inner Ring Road

LONG-TERM:• Network wide, system approach• Real-time fusion of telematics, fast IEM & in-situ flow monitoring• All vehicle types: Buses (e.g. iBus London) and HGVs