ENHANCING MOVES FOR

CONNECTED AND AUTOMATED VEHICLE ANALYSIS

Matthew Barth Yeager Families Professor, CE-CERT Director

barth@cert.ucr.edu

ENHANCING MOVES FOR CONNECTED AND AUTOMATED VEHICLE ANALYSIS

David Oswald CE-CERT Graduate Student Researcher

TRANSPORTATION IS UNDERGOING FOUR MAJOR REVOLUTIONS

Shared Mobility:

Electrification: • electric drivetrains are becoming more common • Drivers: advances in motors, controls, and batteries

Connectivity: • Vehicles are increasingly “connected” • Drivers: cellular communications, dedicated short range communications

• carsharing, ride hailing companies (e.g., Uber, Lyft), and advanced transit • Drivers: Internet connectivity, convenience, and transportation costs

Automation: • Vehicle automation is emerging in many forms • Automation comes with many social implications

General Components of a Transportation-basedEmissions/Energy Inventory:

• emissions/energy factors environmental • vehicle activity inventory

• fleet composition

Shared Mobility

RouteE

BEAM

CAV+ Traffic Flow

CAV+Mode Choice

FUTURE TRANSPORTATION: MODELING ENERGY & EMISSIONS

Shared Mobility: • Vehicle Activity: Travel Demand Models need to change • Vehicle Operation should remain the same

Electrification: • Vehicle category is simply changed within MOVES • Indirect Emissions: need to know energy sources that produce electricity

Connectivity: • Vehicle types will likely be newer, energy efficient, and low emissions • Vehicle Operation/Activity will likely be smoother

Automation: • Vehicle types will likely be newer, energy efficient, and low emissions • Vehicle Operation/Activity will likely be smoother

or

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Project-Level Emission Modeling 70

Travel time = 10 minutes

Veh

icle

Spe

ed, m

ph

60 Travel distance = 3.7 miles 50 Travel speed = 21.9 mph 40

30

20

vehicle activity (velocity trajectory and grade if available) 10

0

3 0

or:

vehicle calibration Emissions parameters and Modeling

emissions factors

traffic simulation

0.018 3.0 NOx emission = 1.5 g

Fuel consumption = 464 g = 0.17 gallons 0.015 (NOx emission fee = X dollars/g)2.5

Fuel

Con

sum

ptio

n, g

Fuel price = $2.7/gallon Travel fuel cost = 0.5 dollars2.0

(Travel NOx emission cost = 1.5X dollars)0.012

0.009 1.5

0.006 1.0

0.0030.5

0.000 1 101 301 501201 401

fuel consumption emissions

0.0 601

--

Three regimes on how Connected & Automated Vehicles can reduce on-road energy and emissions

CO2

(g/m

i) 1000

900

800

700

600

500

400

300

200

100

0

Increases capacity of roadways through congestion reduction

Reduction of stop and go driving

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Average Speed (mph)

Real-world driving Smooth driving

Congestion Reduction

Traffic flow smoothing

Platooning reduces aerodynamic drag

Aerodynamic Drag Reduction

Source: Barth, M. and Boriboonsomsin, K. (2008). Real-world carbon dioxide impacts of traffic congestion. Transportation Research Record, 2058, 163-171.

-

0

3

6

9

5 12 -~ .:.:: - 18 Q. Cl)

> 24

30

30+

0

11 12 13 14 15

>

16

Speed (mph) 25 50 50+

21 22 33 23 24 35 25

27 37

28 38

29 39

30 40

Motor Vehicle Emission Simulator (MOVES) • Data-Driven Emission Model • Uses a Binning Approach for Vehicle Operation Mode (OpMode) and Emission Factors

Vehicle Equipped with the

Eco-Approach and Departure at Signalized

Intersections Application (CACC capabilities

optional)

Source: Noblis . November 2013 Traffic Signal Head

Traffic Signal

1controller with

I ,,., '"""""

MOVES Sensitivity Analysis • In our real-world connected and automated vehicle experiments, we noticed

that MOVES was under predicting the energy and emissions benefits • We initiated a study to compare real-world fuel consumption, MOVES, and

CMEM

Speed (mph) 0 50 50+

0 00 0

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0 .. 0 30+ '------------___.L_ ____ ____:_ ..:::__ ___ _l__ __ ....:.._ ___ __:._ __ _J

Calibrating MOVES: Training Data Set

• Second-by-second data were collected from numerous driving trips and experiments • Data are used to calibrate MOVES fuel consumption factors and activity in the various

OpModes

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4.5

4

3.5

3

2.5

2

1.5

0.5

0

Fuel Consumption mapped to MOVES bins

• Second-by-second fuel consumption (grams/s) • Max value: 5.41 grams/s

• 15

20

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>

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30

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Speed (mph) 16

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• • •

• 0.5

Fuel Consumption map of MOVES Bin 16

• Wide range of values with lower VSP values dominated by lower fuel values • Range: [0.38, 4.59]

MOVES Bin Statistics 11 # of Values: 6057

Range: [0.199, 3.01] Mean = 0.324 S.D. = 0.177 21 # of Values: 2923

Range: [0.23, 3.6266] Mean = 0.195 S.D. = 0.323

33 # of Values: 108 Range: [0.327, 3.99]

Mean = 0.511 S.D. = 0.869 12 # of Values: 2335

Range: [0.21,2.967] Mean = 0.624 S.D. = 0.357 22 # of Values: 1631

Range: [0.238,2.73] Mean = 0.465 S.D. = 0.403

13 # of Values: 1288 Range: [0.24, 2.856]

Mean = 0.953 S.D. = 0.429 23 # of Values: 1931

Range: [0.24, 3.566] Mean = 0.714 S.D. = 0.412

14 # of Values: 1229 Range: [0.27, 3.5]

Mean = 1.22 S.D. = 0.437 24 # of Values: 1470

Range: [0.26, 3.744] Mean = 0.939 S.D. = 0.417

35 # of Values: 56 Range: [0.35, 3.51]

Mean = 1.2 S.D. = 1.139

15 # of Values: 914 Range: [0.34, 3.586]

Mean = 1.501 S.D. = 0.451 25 # of Values: 1002

Range: [0.247, 3.59] Mean = 1.18 S.D. = 0.507

27 # of Values: 842 Range: [0.31, 4.11]

Mean = 1.64 S.D. = 0.651 37 # of Values: 42

Range: [0.368, 3.75] Mean = 1.908 S.D. = 1.1454

16 # of Values: 600 Range: [0.38, 4.59]

Mean = 2.07 S.D. = 0.699

28 # of Values: 188 Range: [0.43, 4.37]

Mean = 2.39 S.D. = 0.831 38 # of Values: 28

Range: [0.4, 4.1159] Mean = 2.14 S.D. = 1.282

29 # of Values: 62 Range: [0.36, 5.1]

Mean = 3.17 S.D. = 0.892 39 # of Values: 30

Range: [0.4566, 4.745] Mean = 3.23 S.D. = 1.435

30 # of Values: 30 Range: [2.44, 5.22]

Mean = 3.745 S.D. = 0.856 40 # of Values: 30

Range: [0.67, 5.41] Mean = 3.83 S.D. = 1.54

0

3

6

9

~ 12 -~ .=.:: - 18 Q. Cl)

> 24

30

30+

0

11 12 13 14 15

16

Speed (mph) 25 50 50+

21 22 33 23 24 --25 ~~

-- --.... vi

-- --,._ V ~u

-- --,~ ~~

30 40

Improving Resolution Using Sub-Binning

• Green lines show new bin borders

C 0

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.., 15

~ ~ 18 en > 21

24

27

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0

111

121

131

141

151

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166

167

Speed (mph) 25 50 50+

211 331

221 332

231 333

241 351

251 352

271 371

272 372

281 381

282 382

291 391

292 392

301 401

New Bin Definitions

• New Bin Numbering System

0

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C 0 - 15 ~ .:a::

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- 18 c.. "' > 21

<9 0 -.r>

163° 0 =i 0o 0

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164 0

24 165

27 166

30

167

0 0

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O 00 0 331°

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371

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381 ° 0

0 0 0 Oo O 'lC,2

~ oO

0 0 0 00 391 0

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0 391 0

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0 401 0

50+

0

0

0 0

0

0 oO 0 30+ L::::::==============i_ ________ _:_ _____ ...L. ___ _:_ __________ ...J

0

New Bin Definitions

• Training data plotted in new bins • Green boxes highlight what was changed

50+

--'2 12

-0 120 ~ 15

24

~ 18 0.. Ul 21 >

I 24

?7

27

30

30+

122 ° 121 . , 0 i O ' • ., 220

222 c o V "'

& •

l

Emissions & Fuel Factors

3.64208

3.41281

3.54149

3.67345

High Resolution Bins

3.41281 + 3.54149 + 3.67345 + 3.64208 = 3.5674575 ≅ 3.5675 4

Emission factor for bin 120 is 3.5675 Do the same process for each bin of High Res. MOVES

D

D

D

Calibration of Emissions & Fuel Factors

0 0.2533 1 0.2908 111 0.3746 112 0.6262 113 0.9336 114 1.2210 115 1.4943

0 0.2533 1 0.2908 11 0.3746 12 0.6262 13 0.9336 14 1.2210 15 1.4943 16 3.0875

211 0.2908 212 0.4712 Calibrated 213 0.7115 214 0.9475 MOVES 215 1.2142

Avg.

Avg. 116 1.8635 117 2.3965 118 2.7907 119 2.9698 120 3.5675 121 3.7988 122 4.2254

21 0.2908 22 0.4712 23 0.7115 24 0.9475 25 1.2142 High Res.

311 0.1432 312 0.7473 313 0.7243 314 0.7131 315 1.8969 316 1.8942 317 1.9222 318 1.0207 319 2.7613 320 2.8209 321 4.1931

30 3.9454

0.5383 33 1.3050 35 1.9082 37 1.8910 38 3.5070 39

Calibrated MOVES

216 1.5973 217 2.0022 218 2.3361 219 2.8737 220 2.9989 221 3.8236 222 3.9454

High Res.

40 3.8337

Calibrated 322 3.8337 MOVES

High Res.

27 1.7998 28 2.6049 29 3.4113

Avg.

Comparison Results

Fuel Consumption Avg. g/mile

Method Measured MOVES Calibrated MOVES

High Res. MOVES

gram/mile 147.9 170.5 154.69 150.41

% Diff +15.3% +4.59% +1.69%

• Data from typical driving • MOVES: uncalibrated results • Calibrated MOVES: MOVES calibrated based on vehicle fuel consumption data • High Resolution MOVES: uses sub-bins

Extrapolation: Developing a Bin-Pyramid

Decrease Resolution

Increase Resolution

Top Level (Current Bins)

...

Bottom Layer (1 VSP by 12.5 mph)

-

Eco-Approach and Departure at Signalized

Intersections Application (CACC capabilities

optional)

Source: Noblis. November 2013

Roadside

Traffic Signal Head

Traffic Signal Controller with SPaT Interface

Trajectory Smoothing

• There are many applications that attempt to “smooth” trajectories without loss oftravel time: Eco-Pedal, traffic-lightanticipation, etc.

• Example: the Eco-Approach and Departure(EAD) connected vehicle application

• Two cars drove at the same time on the same street, one using EAD techniques and the other driving normally

Increases capacity of roadways through congestion reduction

Reduction of stop

Real-world driving Smooth driving

Congestion Reduction

Traffic flow smoothing

Platooning reduces aerodynamic drag

Aerodynamic Drag Reduction

Speed (mph) Speed (mph) 0 25 50 50+ 0 25 50 50+

0 0 33 33

3 3

6 6

9 35 9 35 S 12 S 12 - -~ 0 37 ~ 37

.:.:: .:.:: - 18 - 18 Q. 0 Q. CJ) 0

~8 38 CJ) 28 38 > 46° > 16 24 24

29 39 29 39 30 30

30 40 30 40 30+ 30+

EAD vs. Non-EAD Driving

Non-EAD EAD

EAD vs. Non-EAD Driving

Fuel Consumption Avg. g/mile

Method Measured MOVES Calibrated MOVES

High Res. MOVES

No EAD 137.63 158.3 144.9 140.63

EAD 128.51 154.6 141.2 136.3

Improvement 6.63% 2.33% 2.55% 3.08%

Speed (mph) Speed (mph) 0 25 50 50+ 0 25 50 50+

0 0 33 33

3 3

6 6

9 35 9 35 S 12 S 12 - -~ O 0 37 ~ 37

.:.:: .:.:: - 18 - 18 Q. 0 Q. CJ) 0

38 CJ) 38 > 60 > 16 24 24

29 39 29 39 30 30

30 40 30 40 30+ 30+

EAD vs. Non-EAD Driving

Non-EAD EAD

Speed (mph) Speed (mph) 0 25 50 50+ 0 25 50 50+

0 0 33 33

3 3

6 6

9 9 C: 12 C: 12 0 0 -~

.:.:: -Q. 18

-~ .:.:: -Q.

18 CJ) CJ)

> > 24 24

30 30

30 40 30 40 30+ 30+

EAD vs. Non-EAD Driving

Non-EAD EAD

Speed (mph) 0 25 50 50+

0 331

3 332

6 ~~~~ 333 9 I--~ ~ 351

- 352 5 12 1---f'--ii~~~~~~ +--..;;...;;;..;;;;;__--i i 15 l---i+--=~~r-~~+--+--3.;:;_7;;_1.:..,.._--i ~ 18 1----+---------f"-"'-~----t---+--3_7_2_ ..... 0..

0163 0 381 "'> 21 . ~ ~ ==:t===~~ ;--,-:;;;-::;--,

~~4 382 24 -------------165 391 27 -------------166 392 30 -------------

167 301 401 30+-----------------

Speed (mph) 0 25 50 50+

0 331

3 332

6 1---.11~ 333 9 ~ ~!.i.. ~ jijlil.Mi~ 351

- I -~~~~ 352 5 12 t- ~ ;..,....--+---..;;...;;;..;;;;;__~ ~ 15 1------/o-l~~~....,,.;.:~;..__-+---3.;:;_7;;_1.:..,.._~ ~ 18 l-------'1------------~...,.o

0

-+-7_2_-+-_3_7_2_--1 o.. 281 381 "'> 21

164 282 382 24 -------------165 291 391 27 -------------166 292 392 30 -------------

167 301 401 30+-----------------

EAD vs. Non-EAD Driving

Non-EAD EAD

\ \

\ \

Conclusions and Recommendations • Traffic Smoothing effects tend to get

washed out in MOVES due to bin size • Recommendation: MOVES can be preserved

and enhanced with a sub-binning approach • MOVES could be used at different

“resolutions” using a Bin-Pyramid approach; original MOVES model is preserved

• New Guidance Documents can be written that suggests what resolution should beused automated resolution determination

Top Level (Current Bins)

...

Alternative Vehicle Emission Modeling Approaches

Array of new modeling techniques developed since the late 1990’s:

• Fuel-Based Emission Inventories • normalizes vehicle emissions to fuel consumption, not VMT • requires estimates of fuel use, e.g., from fuel tax • generates reasonable emission inventories for large databases

• Modal and instantaneous vehicle emission models: • concerned with estimating emissions as a function of vehicle operating

mode, (e.g., idle, acceleration, cruise, deceleration) • predicts emissions second-by-second

• Statistical Models: • Many models exist…

COMP'REHEINSIVE M ,ODAL EMISSIONS IMODEL (CMIEM)

COMPREHENSIVE MODAL EMISSIONS MODEL (CMEM)

• Microscale emission model • Developed at UCR CE-CERT • Initially developed in the 1990’s, lightly maintained

• Sponsorship • National Cooperative Highway Research Program (NCHRP) • U.S. Environmental Protection Agency (EPA)

• Objective • Model vehicle emissions at the project level ( sec-by-sec) • Accurately reflect the impact on emissions from various operating

conditions/parameters • vehicle speed, acceleration, and road grade • starting conditions, temperature (history effects) • secondary engine load, etc.

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40

Vehicle Technolo

2-w ay Cat alyst

3-way Cat alyst, Carburet ed

3-way Cata lyst, Fl, >SOK m iles, low power/weight

3-w ay Cat alyst, Fl, >SOK miles, high pow er/weight

3-w ay Cat alyst, Fl, <SOK miles, low power/weight

3-way Cat alyst, Fl, <SOK miles, high pow er/weight

Tier 1, >SOK miles, low pow er/weight

Tier 1, >SOK mi les, high power/weight

Tier 1, <SOK miles, low power/weight

Tier 1, <SOK mi les, high pow er/weight

Tier 1, >lOOK miles

Ultra l ow Emission Veh icle {ULEV)

Super Ultra l ow Emission Veh icle {SUlEV) / Parti al Zero

Emission Veh icle (PZEV)

Normal Emitting Trucks '=========== Pre-1979 ( <=8500 GVW)

1979 t o 1983 ( <=8500 GVW}

1984 t o 1987 {<=8500 GVW}

1988 t o 1993, <=3750 LVW

1988 t o 199-3, >3750 LVW

Tier 1 LDT2/3 {3751-5750 l VW or A lt. l VW)

Tier 1 LDT4 (6001-8500 GVW, >5750Alt. l VW)

Gasolin e-powered, LDT {> 8500 GVW}

Diese l-powered, LDT {> 8500 GVW}

...... """!!' .................................... .....,H...,igh Em itti ng...,V..,e;.,.h...,i...,.cl..,e.;.,s .................................... ....,1

19

20

21

22

23

45

46

47

Runs lean

Runs ri ch

Misfire

Bad cat alyst

Runs very r ich

19,94 t o 1997, 4-st rok.e, Elec. Fl HOOT

1998, 4-st rn lke, Elec. Fl HOOT

1999 t o WOO, 4-st ro k.e, Elec. Fl HDDT

Veh

icle

Spe

ed, m

ph

Vehicle Activity (velocity trajectory) 70

Travel time = 10 minutes 60 Travel distance = 3.7 miles 50 Travel speed = 21.9 mph 40

30

20

10

0

3 0 Grade (optional) Calibration Vehicle Parameters

General Vehicle Parameters

28 LDV CMEM Emissions

0.018 NOx emission = 1.5 g

0.015 (NOx emission fee = X dollars/g) (Travel NOx emission cost = 1.5X dollars)

0.012

0.009

0.006

0.003

0.000 1 101 201 301 401 501

Fuel Consumption

Fu

el C

onsu

mp

tion

, g

Fuel consumption = 464 g = 0.17 gallons 2.5 Fuel price = $2.7/gallon

Travel fuel cost = 0.5 dollars2.0

1.5

1.0

0.5 3 HDDV 0.0

601

3.0

CMEM EMISSION MODEL STRUCTURE

~ • operating

parameters ~

Engine Power

--------Demand

vehicle parameters ~

--------

Engine Speed

1 Fuel Rate

i Eugiu Contrnl

Engine-Out ------. Emissions

i---------.

i-----------.: Exhaust After­

Treatment

tailpipe emissions,

fuel use

CMEM EMISSION MODEL STRUCTURE

• Fuel is a function of Engine Power Demand and Engine Speed

• Fuel rate is related to emissions through analysis based on measured data

• Model Inputs • Operating parameters - vehicle speed, road grade, accessory power, etc. • Vehicle parameters – weight, gear ratios, calibrated emission parameters, etc.

• Model Outputs • Second–by–second emission data and fuel use

EAD vs. ON-EAD WITH CMEM

31

EAD VS. NON-EAD WITH CMEM

Fuel Consumption Avg. g/mile

Method Measured MOVES Calibrated MOVES

High Res. MOVES CMEM

No EAD 137.63 158.3 144.9 140.63 138.97

EAD 128.51 154.6 141.2 136.3 132.5

Improvement 6.63% 2.33% 2.55% 3.08% 4.65%

CONCLUSIONS AND RECOMMENDATIONS

• MOVES Modeling Approach tends to under-estimate traffic smoothing effects due to connected and automated applications

• Sub-Binning Approach can improve resolution • All Modeling Approaches tends to miss effects of aerodynamic

drag reduction effects • Consider adopting a complementary physical modal or

instantaneous emissions model for connected and automated vehicle scenarios, as well as others that have a strong historyeffect in their emissions generation (SCR, after treatment, etc.)

• Dust off PERE emissions generator model that was previouslyused for MOVES?

THA K vouJ THANK YOU! David Oswald

CE-CERT Graduate Student Researcher