Microscopic Sim
ulation: A Tool for Evaluation of Traffic Schem
es
Ricardo Sigua, Ph.D
. Professor, Institute of C
ivil Engineering C
ollege of Engineering, UP D
iliman
Fellow, National C
enter for Transportation Studies rdsigua@
up.edu.ph
Professorial Chair Colloquium
10 August 2012
Prof. Emeritus Norbert S. Vila Professorial Chair
asked David.
Flight Simulation
Approaches to studying traffic problem
s 1)A
nalytical: W
riting mathem
atical expressions to represent the traffic process and then m
anipulating it to determine values to be used in changing
to better traffic conditions. ;0t k
x q
continuity equation:
.0)'
(x k
kuu
t k
x kk c
dt du2
equation of motion:
2/)1
(nck
dk du
2) Trial (and Error): Involves a change in the real traffic situation and then apply subsequent correction if it turns out badly. 3) Sim
ulation: Technique of setting up a stochastic m
odel of real system
which neither over sim
plifies (the system) to the point
where the m
odel becomes trivial, nor incorporates so m
any features of the real system
that the model becom
es untractable or prohibitively clum
sy.
- Harling (O
RSA
, 1958)
CR
ITE
RIO
N
AN
ALY
TIC
AL
SIMU
LA
TIO
N
TR
IAL
Cost
Least M
edium
Most
Time
Least M
edium
Most
Reproducibility
Most
Medium
Least
Realism
Least
Medium
M
ost
Generality of
results M
ost M
edium
Least
Merits of Study Approaches
Early simulation efforts
Writing Program
s in FORTR
AN
, BA
SIC or other languages
Running program
(3x real time !)
Tabulating, analyzing results
0 50
100
150
200
250
300
0500
10001500
Minor road capacity, vph.
Main
road
traffic, vph.
Some Traf Sim
Efforts of ICE faculty m
embers
Analysis of D
elay Caused by M
idblock Jeepney Stops U
sing Simulation, PA
LMIA
NO
, HS, U
EDA
, S, YAI, T
and FUK
UD
A, D
, 2004. M
icro-Scale Analysis of the Transportation Environm
ent in M
etro Manila, V
ERG
EL, YAI, T, IW
AK
UR
A, S, 2001.
Developm
ent of a Simulation Program
for the Evaluation of Jeepney Stop C
onfigurations with Focus on Single
Lane Roadw
ays, REG
IDO
R, JR
F, 1995. A
Study on Control of Left Turn Traffic at Signalized
Intersection, SIGU
A, R
D, 1984.
Some Popular Traffic
Analysis and Simulation
Softwares
Synchro: a macroscopic analysis and optim
ization software application
SIDR
A IN
TERSEC
TION
: an advanced micro-analytical traffic
evaluation tool that employs lane-by-lane and vehicle drive cycle
models.
Paramics: can m
odel transit operations, bus or light rail, with user
defined scheduling and bus stop loading. It can also manage m
ultiple m
odel runs and a sophisticated data analysis tool to aggregate and com
pare scheme options.
TSIS-CO
RSIM
: a microscopic traffic sim
ulation software package for
signal systems, freew
ay systems, or com
bined signal and freeway
systems
VISSIM
: a microscopic sim
ulation program m
odeling for urban and highw
ay traffic, including pedestrians, cyclists and motorized vehicles.
Basic Components of
Traffic Simulation
Road netw
ork: links no. of lanes, lane w
idths, gradient, etc., and nodes nature of conflicts ( diverging, m
erging, crossing/weaving)
traffic volum
e and composition
speed
distribution, lane changing behaviour, gap acceptance, car following, etc.)
Y
IELD or STO
P, signals, roundabout, U-turn, etc.)
Performance evaluation
Comm
on evaluation param
eters Vehicle D
elay Travel tim
e Q
ueue length Fuel consum
ption Em
issions Person delay
Case Study 1 M
ac-Arthur H
ighway
Roxas Ave.
1st St. (C
lark)
Mac A
rthur Highw
ay
Case 1:
Do N
othing C
ase 2:
C
ase 3:
Case Study 1 Sim Results
Mac-A
rthur Highw
ay R
oxas Ave. (Clark)
Parameter
Present
Round
Square
Average delay time per vehicle [s], A
ll Vehicle Types 14.948
19.298 1.095
Average number of stops per vehicles, A
ll Vehicle Types
0.56 0.701
0.03
Average speed [km/h], A
ll Vehicle Types 31.855
27.728 50.422
Average stopped delay per vehicle [s], All Vehicle
Types 5.277
7.061 0.046
Total delay time [h], A
ll Vehicle Types 14.857
27.516 0.925
Total travel time [h], A
ll Vehicle Types 37.721
58.297 22.075
Case Study 2 N
LEX- M
indanao Ave. Intersection
NLEX
Case Study 2 Sim Results
NLEX
- Mindanao Ave.
Parameter
w/Pedestrian
Signal w
/Pedestrian O
verpass
Average delay time per vehicle [s], A
ll Vehicle Types 45.627
9.641
Average number of stops per vehicles, A
ll Vehicle Types 0.912
0.385
Average speed [km/h], A
ll Vehicle Types 25.718
44.300
Average stopped delay per vehicle [s], All Vehicle Types
36.831 5.129
Total delay time [h], A
ll Vehicle Types 47.757
8.580
Total travel time [h], A
ll Vehicle Types 98.882
54.780
Case Study 3 C
omm
onwealth Ave.
University Ave. Intersection and its
vicinity
a) Large area of conflict
b)
Weaving problem
before reaching the U
-turn lane slot c) Long travel distances
ISSUES
a) Current condition
b)
Signal control for 1 left turn m
ovement
c) Signal control for 2 left turn m
ovements
Case Studies
Measure of perform
ance
Current
condition, no signal
Option 1:
1 Left turn signal
Option 2:
2 left turn signals
Average delay tim
e per vehicle [s] 4.86
6.45
15.19
Average speed [km
/h] 50.84
50.27
47.42
Average stopped delay per vehicle [s]
0.70
1.48 7.87
Total delay time [h]
10.58
14.04 33.07
Total Distance Traveled [km
], 17138.92
16705.26
16298.01
Total stopped delay [h], 1.51
3.23
17.13
Total travel time [h],
337.14
332.86 343.67
Case Study 3 Sim Results
Com
monw
ealth Ave. U
niversity Ave. Intersection and its vicinity
Conclusions Very effective for evaluating alternative solutions C
urrent comm
ercially available simulation program
s C
ostly N
eed to localize inputs vehicle types; driver behaviour, etc.
M
ust we develop our ow
n? Safety, difficult to assess.
areas for research
A good traffic m
odeller can create a good traffic m
odel out of most m
odelling systems,
and a bad traffic modeller w
ill always create
a bad traffic model out of the best system
- Param
ics microsim
ulation
Thank you!