Transcript Intersection Control Delay

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:
CL
g 2
 (1 
)
2
CL
d1 
V
g
(1  (min(1, ) 
)
C CL

Incremental Delay:

Initial Delay:
d3 
1800Qb (1  u )t
CT




Qb


t  minT ,

 C 1  min(1, V ) 


C  


V
V
V
C ]
d 2  900 CL  [(  1)  (  1) 2 
C
C
C  CL
8kl
Developed Algorithms--Intersection Control Delay
-Observed Vehicle Group Identification
Loop detector
Initial
queue
Observed vehicles group
d3
TD
LTD
Assumtion
t
Observed veh
Group 3
Observed veh
Group 2
Observed veh
Group 1
Link i+1
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
V
1
C
k
i
A
B
a
t0
t2
t1
t3
Red
Green time
Red
k
1
V
C
b
i
A
C
B
c
a
t0
t2
t1
t3
Green time
Red
t4
Red
t5
Green time
Intersection Control Delay
-Case 2 an initial queue exists and it is smaller than one cycle
length( 0<d3<CL)
Q size in
veh
Queue of the observed
vehicle group
m+i'
Queue at the intersection
k+i'
h3
Cycle length for observed group
m
Area D
i
# of vehicle in
the initial queue
i'
h
2
Area of A
t0
t1
Red time
g1=d3-r
situation
t2
t3
Area of B
Area
of C
t4
t5
g1
g2
d3
Cycle Length=r+g1+g2=100 sec
Red time
t6
g1
t7
Intersection Control Delay
-Case 3 -Initial Queue clearance time d3 is greater than one cycle
length (d3>CL)
Cycle length
N
h2
k
i
Area D
A
B
h2
C
t1
t0
t2
t3
Red time
Red time
t4
g1
t5
g2
t7
t6
r
g1
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: 10.85sec
MAE for HCM2000 algorithm result with real control delay:14.28sec
Validation of Intersection Control Delay Algorithms
ANOVA Table for Actual Delay vs HCM2000 results
Source
DF
Regression
SS
MS
F
1
472.2
472.2
Residual Error
26
6733.4
259.0
Total
27
7205.7
P
1.82
0.182
ANOVA Table for Actual Delay vs Developed Algorithm results
Source
Regression
DF
SS
MS
F
1
4267.4
4267.4
Residual Error
26
2938.3
113
Total
27
7205.7
P
37.76
0.01
Total Travel Time Computation

Travel Time Without initial Queue:
Travel  time 

Travel time with an initial queue but without blackout:
Travel  time 

L
 Intersection delay
speed _ by _ det ector
LTD  QL
L  LTD

 Intersection delay
speed _ by _ det ector speed _ lim it
Travel time with blackout (i.e. QL> LTD) :
Travel  time 
L  QL
 Intersection delay
speed _ lim it / 2
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 determine travel time on link i
Main flow chart
Obtain flow and occupancy from detectors
*
Is blackout occurring
on the detector of
link i?
Yes
Algorithm 3
No
Use algorithm 1 to
estimate travel time on
link i
No
Yes
Use algorithm 2 to
estimate travel time
on link i
Is blackout on link
i+1?
update queue length
and check whether it
is crossing link i
no
Consider link i-1
yes
is link i-1 the
last link?
Consider link i-1 and
use algorithm 4 to
estimate the travel
time of this last link
Sum the travel times
on each link
Repeat process for
tn+1
Send travel time
updates to traffic
control center
* blackout condition exists if a car stays over the loop detector for an extended period of time
Algorithm 1(No blackout)
Is departing rate from link i smaller
than downstream link’s capacity?
Yes
Use intersection capacity of link i
No
Use downstream lane capacity as
the intersection capacity of link i
Algorithm 2(Determining the intersection capacity of
link i when blackout is on the downstream link i+1)
TD
LTD
Is Li+1 -QLi+1<100ft?
(High congestion downstream?)
Yes
No
Link i+1
Use the detected flow rate from
downstream detector as
the intersection capacity of link i
Algorithm 1
Algorithm 3(Determining incoming
volume when blackout is on link i)
TD
LTD
Is Li –Qli>100ft
High congestion on link i?)
Yes
Use the dissipated volume from link i-1
as the incoming volume to link i
No
Link i-1
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
Link i+1
Algorithm 4 (Where no detectors are
available beyond this link)
Algorithm 4
Where no detectors are available beyond this link
Obtain flow and occupancy from loop detectors
The change of major flow chart
The same as major flow chart
*
Yes
Is blackout occurring on
the detector of link i?
Assume maximum queue
on link i
No
Use algorithm 1 to
estimate travel time on
link i
No
Yes
Is blackout on link i+1?
Use algorithm 2 to
estimate travel time on link
i
A Simulation from CORSIM
Results
250
Travel Time
200
150
Travel time by CORSIM(sec)
Travel time by Algorithm(sec)
100
50
0
1
2
3
4
5
6
7
8
9
10
Conclusion and future study
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
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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?