Measurement of Traffic Flow Characteristics at mid-block sections -Universal Engineering college.ppt

MEASUREMENT OF TRAFFIC FLOW
CHARACTERISTICS AT MID-BLOCK SECTIONS
Dr. Shriniwas Arkatkar, Associate Professor, CED, SVNIT
P.G. CENTRE IN TRANSPORTATION ENGG. PLANNING
DEPARTMENT OF CIVIL ENGINEERING
SVNIT, SURAT

Outline of the Talk
 Introduction
 Measurement Procedures
 Traffic Flow Characteristics at mid-block
 Time space diagram
 Fundamental diagram of traffic flow
 Traffic flow models
 Summary and Points for Discussion
Measurement of Traffic Flow Characteristics at mid-block sections 17-Feb-23
2

Traffic System Objectives
 Travel Time Reduction (Speed)
 Reduce Congestion (Increase Efficiency)
 Safety
 Economy
 Mobility
 Environmental Effects
 Energy Consumption
 Equity
 Growth
3

Achieving traffic system objectives:
1. To understand, represent and analyze traffic
flow characteristics under various design and
control parameters
2. Select design and control levels to meet
objectives
 Iterative processes….
4

Major Traffic Flow Characteristics
 Traffic flow is a time-space phenomenon
 Highly non-linear system response
 Different Inputs lead to the same output
 Same input may lead to different outputs
 Complex Interactions
 Speed
 Acceleration / Deceleration
 Lateral placement
 Longitudinal position
 Conflicting Objectives
 Speed differential versus safety
 Efficiency versus speed
 LOS versus infrastructure utilization
5

Measurement Procedures
 Advancements in Measurement capabilities
 Influencing interest in traffic flow analysis
Measurement of Traffic Flow Characteristics at mid-block sections
Measurement at a point
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Measurement Procedures..
Measurement over a length of road Example-1
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Measurement over a short section Example-2
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8

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9

Km
5.200
Km
5.500
Km
5.700 Km
5.900
5 % Gradient on National
Highway No. 4 near Pune,
Maharashtra
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10

Observer moving in the traffic stream
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11

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12

Speed – Time profile
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13

Speed – Distance profile
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14

Wide-area samples obtained simultaneously
from a number of vehicles, as part of Intelligent
Transportation Systems (ITS)
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15

Traffic Variables of Interest
 Rates of flow (vehicles per unit time);
 Speeds (distance per unit time);
 Travel time over a known length of road (or sometimes the
inverse of speed, is used);
 Occupancy (percent of time a point on the road is occupied
by vehicles);
 Density (vehicles per unit distance);
 Time headway between vehicles (time per vehicle);
 Spacing, or space headway between vehicles (distance
per vehicle);
 Concentration (measured by density or occupancy).
16

Data Collection Methods
Probe
vehicle
Tfc
Data
Point
Based
Radar
O-D counts
Loop detectors
enoscope
videographic
Area
Based
Video
Aerial Photography
License plate
Stream
Based
Moving
observer
Floating
car
Two fluid
method
17

time
space
t T
L
Time-Space Diagram
Point Measurement
Short Section
Measurement
Measurement
along the road
length
Moving Observer
beyond road length
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18

Microscopic Traffic Variables
 Microscopic:
 Focuses on elemental unit–individual vehicles
 And Interactions with neighbors
 Discrete particle model
 Decisions of interest:
 Overtaking
 Lane-changing
 Vehicle following
 Gap acceptance
 Placement
19

Microscopic Traffic Variables
20
Length considered : 50 m
Width of section : 9.5 m

Plotting of Grid lines
21
• Lateral points are of 1m interval
• Longitudinal points are of 5m interval

Plotting of Grid lines…
22
• Grid lines were plotted in AutoCAD
• Saved as image file
AutoCAD drawing
Image file (.jpg format)

Overlaying of Grid
23
Overlaying the grid image into video file using Ulead Video Converter

Overlaying of Grid
24
Overlaid video file

Extraction of frames using Irfan View
25

Extracted data in excel sheet
26
• Noted the coordinates, frame number etc. in excel sheet.

4. Extracted data in excel sheet
• Noted the coordinates, frame number etc. in excel sheet.
• Raw data file: 2. it corridor2. 1st input(example).xlsx
17-Feb-23
27 Measurement of Traffic Flow Characteristics at mid-block sections

Time-Space Diagram: Analysis
at a Fixed Position
h1
h2 h4
h3
T time
position
0
0
L
x
28

Time-Space Diagram: Analysis
at a Fixed Time
t
s1
s2
L
0
time
position
t0
17-Feb-23
29

Macroscopic Traffic Variables
 Focus on stream characteristics
 Aggregation of individual vehicle properties
 Applied to model overall stream features such
as congestion, delays approximately.
 Computationally easier
30

Terminologies in Traffic Engineering
1. Density(K): Number of vehicles present in a stated
length of road at an instant. Expressed as
vehicles/unit of length(veh/km)
2. Flow(q): Number of vehicles passing a specified point
during a stated period of time. Expressed as
vehicles/unit of time(veh/hr)
3. Time headway (h): Time interval between the passage
of the fronts of successive vehicles at a specified
point. Measured in seconds.
31

4. Space headway(s): Distance between the fronts
of successive vehicles. Measured in meters.
5. Speed(v): Distance travelled per unit time.
6. Spacing(s): The centre to centre distance
between any two consecutive vehicles in motion.
7. Clearance(c) : Distance from end of one vehicle
to the front of other following vehicle.
8. Occupancy : Percentage of time that the
detection zone of the instrument is occupied by a
vehicle.
Terminologies in Traffic Engineering.
17-Feb-23
32

Spacing
Pictorial View of Spacing
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33

Clearance
Pictorial View of Clearance
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34

Density
# vehicles/Distance
Pictorial View of Density
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35

• Speed (v) –m/sec or mph or km/h
• Flow (q) – veh/sec or vph
• Density (k) – veh/ft or vpm or v/km
• Spacing (s) – ft/veh or meter/veh
• Headway (h) – sec/veh
• Clearance (c) – ft/veh or meter/veh
• Gap (g) – sec/veh
Remember Units are Critical!
17-Feb-23
36

Comparison of Micro and Macro
Traffic Flow Characteristics
 Microscopic
 Time headway – (h)
 Spacing –(s)
 Speed – (v)
 Macroscopic
 Volume (Q)
 Density (K)
 Speed (V)
Time Aggregated
Space Aggregated
17-Feb-23
37

Fundamental Relationships
• q = k  v
(veh/hr) = (veh/km)  (km/hr)
• h = 1 / q
(sec/veh) = 1 / (veh/hr)  (3600)
• s = 1 / k
(m/veh) = 1 / (veh/km)  (1000)
What are the assumptions for these relationships?
38

Assumptions: Traffic Relationships
 h and s are constant over entire stretch
 h and s are constant over time
 h and s are identical across drivers
 Under these assumptions v = s/h = Q/K
17-Feb-23
39

Speeds: TMS and SMS
• Time mean speed (TMS): Average of the speed
measurements at one point in space over a
period of time.
40
t
x
1 2
3
4
v4
A x x
x x

Travel Time Averaged Speed (SMS)



i
i
i
i
i
s
t
V
t
V 1
_






i
i
i
i
i
i
i
i
s
V
l
l
V
l
V
V
l
V
/
/
)
/
(
1
_




i
i
i
i
V
n
V
n
)
/
1
(
1
1
/
1
Harmonic Mean of Speeds = Reciprocal of Arithmetic mean of 1/Speeds
However, if you measure at a single point by say radar and take
harmonic mean, the result may not give space mean speed. Why?
17-Feb-23
41

17-Feb-23
42
Travel Time Averaged Speed (SMS)
t
x
1 2
3
4
v4
A x
B
t = T
t = 0
t1
t2
t3
l3
L



i
i
i
i
i
s
t
V
t
V 1
_
3
2
1
3
1
_
t
t
t
l
L
L
V s






Instantaneous Space Mean Speed
 Suppose you can take a snapshot of all vehicles
in a stretch of a highway at some point in time.
 Take the average of speeds of all vehicles in the
snapshot at that instant of time
t
time
of
t
ins
that
at
stretch
that
in
present
vehicles
only
represents
i
Here
n
t
V
V
i
i
s
tan
)
(
2
_ 

17-Feb-23
43

Instantaneous Space Mean Speed
17-Feb-23
44
t
x
1 2
3
4
v4
T0
x
x
x
x

Estimation of volume and travel time
using moving observer method
45
17-Feb-23

Estimation of Travel time on two-lane road
46
17-Feb-23

Problem (Travel Time)
 The following tables give the particulars collected for a
section of road 3.5 km long during the course of a
moving observer study. Calculate the journey speed and
running speed in each direction.
47
Run
No
Journey Time Stopped
Delay
Overtaking
vehicles
Overtaken
vehicles
Opposite
Direction
Flow
min sec min sec
1 8 32 1 40 4 7 268
2 7 50 1 30 5 5 350
3 8 15 1 10 6 6 390
4 9 28 1 50 4 5 260
Table 1: North-South Direction:
17-Feb-23

Traffic Volumes on all routes
48
17-Feb-23

Travel Time Contours
49
17-Feb-23

Travel Time Contours
50
17-Feb-23

17-Feb-23
51
Fundamental Diagrams of
Traffic Flow

Fundamental Traffic Flow Diagram
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52

Fundamental Traffic Flow Diagram
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53

Fundamental diagram of traffic flow
(flow vs. density)
54
Flow
(q)
Density (k)
Optimal flow
or capacity,qmax
Optimal
density, ko
Jam density,
kj
Mean free flow speed, uf
Optimal speed, uo
Speed is the
slope. u = q/k
Congested
flow

Greenshield’s Model
Assume a linear relationship between v and k:
High Density = Low
Speed
Low Density = High
Speed
vf
kj
k
k
v
v
v
j
f
f 









55

K
Q
Max flow
qmax
K0
Kj
vf v0
2
k
k
v
k
v
q
j
f
f 









56

Q
V
Max flow
Qmax
Vf
V0
1/k0=s0
57

Greenshield’s model
k
k
u
u
u
j
f
f
s 

2
k
k
u
k
u
k
u
q
j
f
f
s 


Nice characteristics of the Greenshield’s model:
2
f
o
u
u 
2
j
o
k
k 
4
max
f
ju
k
q 
This model works for all k = 0 to k = kj
58

Combined Fundamental Traffic
Flow Diagram
59

Example-1
Assuming a linear v-k relationship, the mean free speed
is 60 mph near zero density, and the corresponding jam
density is 140 vpm. Assume the average length of
vehicles is 20 ft. Find:
 v(k) and q(k)
 Sketch v-k, v-q, and q-k diagrams
 Compute v and k at q=1000 vph
 Compute the average headway, spacings,
clearances, and gaps when the flow is maximum
60

Example-2
 Given that the relationship between and
density obtained from the actual data is
 Estimate all the macroscopic and microscopic
parameters
k
u 24
.
0
5
.
54 

61

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