2014 ite intermountain section annual meeting center for advanced transportation education and...

2014 ITE Intermountain Section Annual MeetingCenter for Advanced Transportation

Education and ResearchUniversity of Nevada, Reno

Using Detector Information to Determine Turning Movement Proportions at Signalized

Intersections with Shared Lanes

Ali Gholami

Center for Advanced Transportation Education and Research (CATER)

Department of Civil & Environmental Engineering

University of Nevada, Reno

1

Center for Advanced Transportation Education and ResearchUniversity of Nevada, Reno

Project Panel MeetingMarch 27, 1012



Outline

Volume application

Problem statement

Proposed methods

Case study intersections

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Intersection operational analyses Traffic safety studies Travel demand modeling Identifying critical flow time periods …

Turning Movement Volume Applications

3





Loop Detector4





Loop Detector5





What is the current practice?6





Loop Detector Data , Aggregated

7

9 10 11 12 5 6 7 8

46

29 33 45 41 0 0 0 0

26 36 39 37 0 0 0 0

33 32 57 53 0 0 0 0

46 67 89 87 0 0 0 0

. . . . . . . . . .

. . . . . . . . . .

; ; ; ; ; ; ; ; ; ;

6/12/2013 6:15:00AM

6/12/2013 6:30:00AM

6/12/2013 6:45:00AM

Volume Report

Detectors

Date/ Time

KIETZKE & MOANA

6/12/2013 6:00:00AM





Loop Detector Data, High Resolution

8

Sample data collected from the data communication adaptor

Data Communication Adaptor





•Expensive

•Time assuming

•Not continuous

•Manual

•Not possible in shared lanes

•Automatic using loops

Collecting intersection Volume in Nevada

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• Only high resolution data

• Both stop bar and departure detectors are necessary

• Departure detector

• Aggregated or high resolution data• Network

Equilibrium (NE)

• 1 min aggregated data or high resolution data

• Volume and Queue Length of Shared Lanes

(VQ)

• Only high resolution data• Flow Characteristics of Shared Lanes (FC)

• Aggregated or high resolution data •Observed proportions

in the field (OP)

Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes

10





Network Equilibrium (NE)11

𝑊𝑇 𝑖𝑡=−𝑁𝐿𝑖

𝑡−𝑆𝑅𝑖𝑡+𝑊𝑅 𝑗

𝑡+∆𝑡+𝑊𝑇 𝑗𝑡+∆𝑡+𝑊𝐿 𝑗

𝑡+∆𝑡−𝛿𝑖𝑗𝑡

Intersection iIntersection j









Equilibrium (NE)



(VQ)



in the field (OP)


12





Volume and Queue Length of Shared Lanes (VQ)

13

𝑟 𝑠 ,𝑎𝑡 =

𝑣𝑠𝑡

𝑣𝑎𝑡

𝑟𝑟 ,𝑡𝑡 (𝑜𝑟 𝑟 𝑙 , 𝑡

𝑡 )=¿¿

¿









Equilibrium (NE)



(VQ)



in the field (OP)


14





Flow Characteristics of Shared Lanes (FC)

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¿









Equilibrium (NE)



(VQ)



in the field (OP)


16





• Not applicable in Nevada• Departure

detector

• Significant trip generator between intersections

• Network Equilibrium (NE)

• Downstream intersection• Volume and Queue Length of Shared Lanes

(VQ)• Not applicable if left turn is not protected

• Pedestrian

• Turning radius

• Flow Characteristics of Shared Lanes (FC)

• High variances in different hours, days, weeks, or seasons

•Observed proportions in the field (OP)

Considerations

17





Making the Models20

•User must specify the structure of the model

•Regression

•GP automatically evolves both the structure and the parameters

• Genetic Programmi

ng





What does GP do?21





What does GP do?22

x y z3 5 5.8309528 14 16.12452

18 2 18.1107732 11 33.8378512 10 15.620521 6 21.840337 4 8.062258

16 24 28.844412 9 9.219545...

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GP is based on evolution process, (cross over, mutation, and elitism)

We can use ready applications

How GP Works?23





GPTIPS24





R25





MAPE: Mean Absolute Percentage Error

Di: the detector data value

Bi: the reference (base) data value

n: the total number of intervals

Accuracy26





Case Study Intersections27

9th St. and Sierra St.

N McCarran Blvd and Clear Acre Ln

8th Street and Center Street





1 6 25 0.24 3 0.50

2 7 18 0.39 5 0.71

3 6 13 0.46 4 0.67

4 18 21 0.86 18 1.00

5 7 16 0.44 5 0.71

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Sample of data collected for VQ method

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1 0 0 1 c c T

1 2.24 2.24 2 c c R

1 2.31 4.55 3 t c T

1 3.01 5.32 4 c t T

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Sample of data collected for FC method

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MODELLING METHOD

N MCCARRAN BLVD/CLEAR ACRE LN

9TH ST/ SIERRA ST 8TH ST/ CENTER ST

NE

Regression Not applicable Not applicable Not applicableGP Not applicable Not applicable Not applicable

Analytical Calculation

Not applicable due to un-controlled south bound

right turn

Not applicable due to downstream un-

signalized intersection

VQ

RegressionNot applicable because

the adjoining lane is also shared lane

Not applicable due to no existing same-direction adjoining lane

GPNot applicable due to no existing same-direction

adjoining lane

Not applicable due to no existing same-direction adjoining lane


Not applicable Not applicable Not applicable

FC

Regression * * *

GP * * *


Not applicable Not applicable Not applicable

Models30





MODELLING METHOD

INTERSECTION

TURNING RADIUS (FT)

TIME INTERVAL

MAPE (%)

Regression GPAnalytical

Calculation

FLOW CHARACTERISTI

CS (FC)

8th St and Center St

16

Vehicle by Vehicle

20 14 -

Hourly Average 8 7 -

9th St and Sierra St

35

Vehicle by Vehicle

21 20 -


McCarran Blvd and Clear Acre

Ln100

Vehicle by Vehicle

28 25 -


VOLUME AND QUEUE (VQ)

8th St and Center St

Vehicle by

Vehicle17 15 -


NETWORK EQUILIBRIUM

(NE)

9th St and Sierra St

Vehicle by

Vehicle- - -

Hourly Average - - 1

Results31





Results32

Vehicle by Vehicle

Hourly Average

Vehicle by Vehicle

Hourly Average

Vehicle by Vehicle

Hourly Average

Vehicle by Vehicle

Hourly Average

Vehicle by Vehicle

Hourly Average

8th St and Center St 9th St and Sierra St McCarran Blvd and Clear Acre Ln

8th St and Center St 9th St and Sierra St

Flow Characteristics (FC) Volume and Queue (VQ) Network Equilibrium (NE)

0%

5%

10%

15%

20%

25%

30%

Mean Absolute Percentage Error (MAPE) percent

Regression MAPE

GP MAPE

Analytical MAPE





33

Errors using inadequate data are much less than those using no data at

all.

Charles Babbage in 1860

Considered “father of the computer”





34

Thank you

Any comments or questions?

If we have data, let’s look at data. If all we have are opinions, let’s go with mine!

Jim Barksdale, former Netscape CEO

2014 ite intermountain section annual meeting center for advanced transportation education and...

Documents

research university

reno project panel meeting

reno loop detector data

sample data

detector information

intersection volume

shared lanes automatic

shared lanesnot possible