Travel Time Estimation on Arterial Streets

By

Heng Wang, Transportation Analyst Houston-Galveston Area Council

Dr. Antoine G Hobeika, Professor Virginia Tech

Outline

Objective and background Focusing methodology development Methodology validation Conclusion and future study Q & A

Objective

Methodologies were prepared for the proposal for real-time travel time estimation on major arterial streets.

Requirements:

1)Short time interval update for real-time estimation

2)Simple-computation time

3)Make good use of real time detected traffic information

4)Well behaved

About the Methodology

The developed methodology is presented into two sections:

1. Travel time estimation on an isolated arterial link;

2. Travel time estimation on a signalized arterial link that also considers the traffic situation on the upstream and downstream links(Network Algorithms).

Section 1- Travel time estimation on an isolated arterial link --Travel Time Components

Travel time(HCM)=link travel time + intersection control delay

Components of intersection control delay:

1) Uniform delay

2) Incremental delay (over-saturation delay)

3) Initial delay

Intersection Control Delay (HCM2000) and its weakness in short time period update situation

Uniform Delay:

Incremental Delay:

Initial Delay:

)),1(min(1(

)1(21

2

CL

g

C

VCL

gCL

d

]8

)1()1[(9002 2

CLCC

Vkl

C

V

C

VCLd

CT

tuQd b )1(1800

3

),1min(1

,min

C

VC

QTt b

Developed Algorithms--Intersection Control Delay -Observed Vehicle Group Identification

Loop detector I ni t i alqueue

Observed vehi cl es group

d3

Li nk i +1

LTDTD

Observed vehGroup 1

Observed vehGroup 2

Observed vehGroup 3

Assumti on

t

Developed Intersection Control Delay Algorithms

Case 1-where there is no initial queue for the observed vehicle group;

Case 2-there is an initial queue for the observed vehicle group and its clearance time is less than a cycle length;

Case 3- where initial queue clearance time (d3) is greater than a cycle length.

Intersection Control Delay- Case 1 no initial queue

Red

Green time Red

at0 t1 t2 t3

k

i

AB

1V

C

Red

Green time Red

a

b

c

t0 t1 t2 t3 t4 t5

k

i

AB C

1V

C

Green time

Intersection Control Delay-Case 2 an initial queue exists and it is smaller than one cycle length( 0<d3<CL)

Red timeg1 g2 Red time

g1

d3

k+i'

Cycle Length=r+g1+g2=100 sec

h2

Cycle length for observed group

Q size in veh

t2

Area of A Area of B

t3 t4 t6

t7

i'

t1

Queue at the intersectionh3

t5

Area of Ct0

m+i'Queue of the observed

vehicle group

Area D

i

m

# of

veh

icle

in

the

init

ial q

ueue

g1=d3-r

situation

Intersection Control Delay-Case 3 -Initial Queue clearance time d3 is greater than one cycle length (d3>CL)

Red t i meRed t i me g1 g2 r g1

Cycl e l ength

N

h2

i

A B

C

h2

k

t0

t1 t4 t5 t6 t7

Area D

t3t2

Validation of Intersection Control Delay Algorithms

An intersection at N Franklin St/Peppers Ferry RD in Christiansburg, Virginia was selected to initially conduct control delay analyses based on traffic volume and the arrival of vehicles in the observed group.

Validation of Intersection Control Delay Algorithms

MAE for developed algorithm result with real control delay: 10.85secMAE for HCM2000 algorithm result with real control delay:14.28sec

Validation of Intersection Control Delay Algorithms

Source DF SS MS F P

Regression 1 472.2 472.2 1.82 0.182

Residual Error 26 6733.4 259.0

Total 27 7205.7

Source DF SS MS F P

Regression 1 4267.4 4267.4 37.76 0.01

Residual Error 26 2938.3 113

Total 27 7205.7

ANOVA Table for Actual Delay vs HCM2000 results

ANOVA Table for Actual Delay vs Developed Algorithm results

Total Travel Time Computation

Travel Time Without initial Queue:

Travel time with an initial queue but without blackout:

Travel time with blackout (i.e. QL> LTD) :

Intersection delay_ _ det

LTravel time

speed by ector

Intersection delay_ _ det _ limTD TDL QL L L

Travel timespeed by ector speed it

Intersection delay_ lim / 2

L QLTravel time

speed it

Section 2- Network Algorithms

Network conditions that influence input parameters:

Bottleneck on the downstream link: Change intersection capacity; Blackout Situation: Change the identification of the

observed vehicle group.

to determi ne travel t i me on l i nk i

Obtai n fl ow and occupancy f rom detectors

I s bl ackout on l i nki +1?

Use al gori thm 2 toesti mate travel t i me

on l i nk i

Use al gori thm 1 toesti mate travel t i me on

l i nk i

i s l i nk i -1 thel ast l i nk?

Consi der l i nk i -1

Consi der l i nk i -1 anduse al gori thm 4 toesti mate the travel

t i me of thi s l ast l i nk

Sum the travel t i meson each l i nk

Send travel t i meupdates to traffi c

control center

Repeat process fortn+1

Yes

yesno

I s bl ackout occurri ngon the detector of

l i nk i ?

Al gori thm 3Yes

* bl ackout condi ti on exi sts i f a car stays over the l oop detector for an extended peri od of ti me

*

Mai n fl ow chart

update queue l engthand check whether i ti s crossi ng l i nk i

No

No

Algorithm 1(No blackout)

Is departing rate from link i smaller than downstream link’s capacity?

Use downstream lane capacity as the intersection capacity of link i

Use intersection capacity of link i

Yes No

Algorithm 2(Determining the intersection capacity of link i when blackout is on the downstream link i+1)

Li nk i +1

LTDTD

Is Li+1 -QLi+1<100ft?(High congestion downstream?)

Use the detected flow rate from downstream detector as

the intersection capacity of link iAlgorithm 1

Yes No

Algorithm 3(Determining incoming volume when blackout is on link i)

Link i+1

LTDTD

Link i-1 Link i

Is Li –Qli>100ftHigh congestion on link i?)

Use the dissipated volume from link i-1 as the incoming volume to link i

Use the smaller of the following two values:a) the dissipating rate from link i-1

b) the intersection capacity of link i which is the maximum dissipating rate of link i

Yes No

Algorithm 4 (Where no detectors are available beyond this link)

Where no detectors are available beyond this link

Obtain flow and occupancy from loop detectors

Is blackout on link i+1?

Use algorithm 2 to estimate travel time on link

i

Use al gori thm 1 to esti mate travel t i me on

l i nk i

Yes

Is blackout occurring on the detector of link i?

Assume maxi mum queue on l i nk i

Yes*

Algorithm 4

No

No

The same as major flow chartThe change of major flow chart

A Simulation from CORSIM

Results

Conclusion and future study

Algorithms in section 1 provide accurate results when compared with HCM2000 by using real world data;

Algorithms in section 2 are robust when compared with CORSIM simulation results;

Real world data would be collected to validate the section 2 of the developed methodology.

Questions?