big telematics data - iapsccase studies big telematics data 7 1. leeds clean air zone study one...

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 vehicular

emissions 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 Floow Ltd.

Routes to Clean Air Conference, Bristol, October 2016 https://www.slideshare.net/secret/km7kcqE8oHtrn9

BENEFITSBIG telematics data

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Emission assessments account for local, real-driving conditions:

Network-wide: No boundaries

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 by hour

BACKGROUND WORKModelling vehicle movements & emissions

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0 100 200 300 400 500

020

40

60

80

Sp

ee

d (

km

.h1)

0 100 200 300 400 500

01

23

45

67

CO

2(g

.se

c1)

0 100 200 300 400 500

0.0

00.0

20.0

40.0

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Time (seconds)

NO

X(g

.se

c1)

UNDER-PINNING EMISSION MODELInstantaneous Emission Model PHEM*Passenger car and Heavy-duty Emission Model (Euro 0 – 6 / VI)

FIGURES | Sample time series, TfL London

Drive Cycle, Euro 5 diesel MPV

Modelled_NOx

Ob

se

rve

d_

NO

x

0.00

0.01

0.02

0.03

0.00 0.01 0.02 0.03

Counts

112357

111623345175111165244361535

Modelled_CO2

Ob

se

rve

d_

CO

2

0

2

4

6

8

0 2 4 6 8

Counts

1123468

11162231436186121171241

Zallinger, M., Tate, J., Hausberger, S. 2008. An instantaneous emission model for the passenger

car fleet. Transport & Air Pollution conference, Graz 2008

Moody, A., Tate, J. 2017. In Service CO2 and NOX Emissions of Euro 6/VI Cars, Light- and

Heavy- 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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1. 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)

2. 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 (aerodynamic drag,

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 in positive

VSP with RAINFALL

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

FIGURE | Variation in positive

VSP with TEMPERATURE

LEEDS CLEAN AIR ZONE STUDY 2017

METHOD

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METHODBIG telematics data ▶ vehicle emissions process (START)

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METHODBIG telematics data ▶ vehicle emissions process (END)

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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 Emission Factors (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 – 08:30 hrs Direction South Bound

Passenger car (a) speed & (b) Euro 5 diesel car NOX Emission Factors


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FIGURE | Autumn term-time (first half) 08:00 – 08:30 hrs Direction North Bound



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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

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

big telematics data - iapsccase studies big telematics data 7 1. leeds clean air zone study one...

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