LTC, Annual Forum, The Direction of Technology in Transportation, 05/13/2011, Matthew Barth

Communicating with Infrastructure: Using Intelligent Transportation System Technologies

Matthew BarthYeager Families Professor of Engineering

Director: Center for Environmental Research and TechnologyUniversity of California-Riverside

Acknowledgements:

• Kanok Boriboonsomsin, George Scora, Alex Vu, Sindhura Mandava, Qichi Yang

• University of California Transportation Center (UCTC), California Department of Transportation, Federal Highway Administration, EPA, VW/Audi, Nissan, BMW, others

UCR CE-CERTLaboratories:

Emissions and Fuels ResearchEmissions measurement/analysis, fuel effects, new

instrumentation/methods, after-treatment

Atmospheric Processes Researchsecondary pollutant formation, mitigation methods

Transportation Systems Research ITS, vehicle activity, energy/emissions modeling

Sustainable Energy Researchcellulosic ethanol, synthetic diesel fuel, solar energy

Environmental Modelingmodels to predict long-term regional effects; micro dispersion

www.cert.ucr.edu

Intelligent Transportation SystemsTargeted Benefits:

• Improving Safety• reducing accidents• making accidents more survivable

• Improving Transportation Efficiency:• increasing throughput• reducing congestion• maximizing economics

• Energy/Environment:• in-direct benefits of lower emissions and fuel savings• directed benefits to target lower emissions/fuel

Communications is key for Advanced ITS Applications:• V2V (adhoc networks, VANET)• V2I• I2V

Many ITS applications require real-time link-level information: speed, density, flow, energy, emissions, etc.

Vehicle Activity: Real-Time Traffic Data

• real-time traffic density, speed, and flow is become more readily available

• Example: California Traffic Performance Measurement System (PeMS)

• Real-Time data can be used measure congestion

PROBE VEHICLES:

using GPS dataloggers

0

10

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7:00 7:03 7:06 7:09 7:12 7:14 7:17 7:20

Time [hr:min]

Vel

oci

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km/h

r]

Highway Arterial Residential

• when and where trips start and end

• measurement of position, speed, and acceleration

• which roadway route (post map match)

Traffic Surveillance• Proliferation of Video Cameras:

• off-board• on-board• better algorithms

Arterial Roadway Testbed Chula Vista, California

re-identification

Simulation coverage

Minimum probe or other data coverage(overlaps with thesimulation network are not marked)

Simulation coverage

Minimum probe or other data coverage(overlaps with thesimulation network are not marked)

Google Earth or Google Maps Interface

Traffic simulation result for arterials

PeMS data for freeways

Probe Vehicle network (arterials and freeways)

NAVTEQ underlying network data

Dynamic Network Information: Data Integration

Traffic signal/detector info

INRIX traffic data

Broadcasting

Mobile communications network

Base station (Antenna)

On-board network (ITS Data Bus), sensors, collision avoidance radar, ...

Roadside network（Ex. Optical fiber)

Pedestrian

Cell phone, Satellite portable phone, MCA, Radio pager, ...

Existing network

ITS information communications platform

ＩＴＳ information

Truck(Transport company)

Bus, Taxi(Public transportation)

Passenger vehicle

GPS

ITS information

ITS information

Roadside network（Ex. Optical fiber)

ITS info

Broadcasting (FM multiplex, Terrestrial digital, Satellite digital, …)

Road-vehicle communications

DSRC

Base station (Antenna)

Vehicle-vehicle communications

ITS Communication

UCR Testbed Vehicle

GPS-based location system and wireless communication capability

Programmable navigation system with touch-screen capability available to driver and passengers

On-board computer interfaces with the vehicle CAN bus, navigation system, and

wireless communications system

“Dynamic Eco-Driving”ECO-Driving Advice with Dynamic Feedback• Static ECO-Driving:

• shift up as soon as possible• maintain a steady speed• anticipate traffic flow• accelerate smoothly• decelerate softly• check the tire pressure frequently

• Dynamic ECO-Driving: providing real-time advice/feedback:• speed management, intelligent speed adaptation• Instantaneous fuel economy readings• Cumulative real-time travel cost display

Dynamic ECO-Driving

DestinationCurrentLocation

Dynamic ECO-Driving

Destination

Current Speed ECO-Speed

40 35MPHMPH

11+ mi. over ECO-Speed

6-10 mi. over ECO-Speed


At or under ECO-Speed

Dynamic ECO-Driving

Destination


21 25MPHMPH





Dynamic ECO-Driving

Destination


29 35MPHMPH





Dynamic ECO-Driving

Destination


61 45MPHMPH





Dynamic ECO-Driving

Destination


52 45MPHMPH





Dynamic ECO-Driving

Destination


45 40MPHMPH





Dynamic ECO-Driving

Destination


33 35MPHMPH





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Distance Traveled, km

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/h

Non-ISA ISA ISA Maximum Recommended Speed

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Distance Traveled, km

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Dynamic Eco-Driving Field Experiments: Example Results

same travel time results:

reference:

M. Barth and K. Boriboonsomsin (2008) “Energy and Emissions Impacts of a Freeway-Based Dynamic Eco-Driving System”, in press, Transportation Research Part D: Environment, Elsevier Press, August, 2008.

. -13%15341766Fuel (g)

-37%3.976.28NOx (g)

-41%1.903.20HC (g)

-48%50.4797.01CO (g)

-12%47815439CO2 (g)

DifferenceECONon-ECOEnergy/Emissions

-13%15341766Fuel (g)

-37%3.976.28NOx (g)

-41%1.903.20HC (g)

-48%50.4797.01CO (g)

-12%47815439CO2 (g)

DifferenceNon-Energy/Emissions

Dynamic ECO-Driving for Arterial Roads: Signalized Corridor Speed Management

• Much fuel is wasted and CO2 is emitted by vehicles waiting at signalized intersections

• vehicle speed trajectory can be planned based on knowledge of signal timing

• concept: broadcast signal timing information to vehicle to plan vehicle trajectories

• potential target demonstration: California VII corridor where DSRC equipment is already in place with signal information

Signalized Corridor Time-Distance Diagram

time

distance

signal 1

signal 2

signal 3

signal 4

signal n

vehicle trajectories

Simple Signalized Corridor Planning (freeflow)

time

distance

signal 1

signal 2

signal 3

signal 4

signal n

simple heuristic: adjust vehicle speed to catch the green time

Velocity Algorithm• Target velocity is set to get through the green phase of the next

signal (time-distance calculation)• Initial velocity may be above or below target velocity• objective is to:

limit10

1

1102110

(v)

(iv)

(iii)

(ii)

))(()2

1( (i) : subject to

minimize

vatv

PPP

ttt

tt

Dttatvattv

a

enginesaccessorietf

tractive

rg

v0 = velocity of the vehicle at the instant it enters the DSRC ranget = total time taken to reach the intersectiont1 = the portion of time spent accelerating or decelerating with an acceleration rate a(t-t1) = portion of time spent traveling at uniform velocity before reaching the intersection

accelerate with respect to vh

],0[],[ maxvvvV hlpossible intrg dtt ,,

maxv

possiblec Vv

if

YES

NO

NO

YES

lc vv

if

decelerate with respect to vh

fuel or emissions

speed

TARGET

Signalized Corridor Planning Simulation Results

0 50 100 150 200 250 300 350 400 4500

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6000

Time in sec

Dis

tanc

e in

met

ers

0 50 100 150 200 250 300 350 400 4500

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Time in sec

spee

d in

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per

sec

0 50 100 150 200 250 300 350 400 450-3

-2

-1

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1

Time in sec

acce

lera

tion

in m

eter

s pe

r se

c2

0 50 100 150 200 250 300 350 400 450 5000

2000

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6000

Time in sec

Dis

tanc

e in

met

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0 50 100 150 200 250 300 350 400 450 5000

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Time in sec

spee

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met

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per

sec

0 50 100 150 200 250 300 350 400 450 500-3

-2

-1

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Time in sec

acce

lera

tion

in m

eter

s pe

r se

c2

without advanced information with advanced information

LDV24 Without With % Diff.

in Avg. p-value of

t-test Avg. S.D. Avg. S.D. Fuel (g/mi) 118.3 13.2 103.8 9.3 -12.3 8.7E-06 CO2 (g/mi) 371.0 41.2 318.8 25.3 -14.1 3.2E-07

TT (sec) 456.7 60.7 451.9 56.9 -1.06 0.635

Navigation Techniques:• route finding uses famous minimum path algorithms

(Dijkstra, etc.)• shortest

distance

• shortest duration (requires traffic info)

• lowest energy, lowest emissions (requires traffic info, road grade, energy & emissions models)

New Navigation Tool: ECO-Routing:

• shortest-distance or shortest-duration path will oftenbe the path that minimizes energy use or emissions

• roadway congestion and other factors (e.g. grade) create scenarios where minimum-energy and minimum-emissions path may be different than shortest duration or distance

WAN

LAN

Management Interface

Wireless Infrastructure(Cellular, 802.11)

802.11 a/b/g/p - CMDA - GPRS

WAN

MCU

CMEMOBD-II

GPS

Data MiningPost Processing Web Interface XML-RPC Cluster

Database Cluster

ProxyComm Cluster

Universal Mobile Emissions Telematics System (UMETS)

LTC, Annual Forum, The Direction of Technology in Transportation, 05/13/2011, Matthew Barth

Technology

Transcript of LTC, Annual Forum, The Direction of Technology in Transportation, 05/13/2011, Matthew Barth