Title: Traffic Flow Characteristics. Dr. Attaullah Shah
1Transportation Engineering - I
Traffic Flow Characteristics. Dr. Attaullah Shah
2Traffic Flow
- Traffic flow No of vehicle passing per unit time
at a road section - q n/t n No of vehicles t duration of
time, usually an hour - Time head way The time between passing of
successive vehicles i.e. bumpers - t S hi t duration of time interval hi
time head way of ith vehicle. - q n/ S hi Average mean time headway
- The average speed is defined in two ways
- Arithmetic mean of total speeds at a particular
point also called time mean speed Mean Ut
Sui/n - Space Mean Speed Assumed that the average speed
for all vehicles is measured at the same length
of roadway. - Space mean speed in unit distance per unit time
length of strip/mean time
3Example
- The speed of five vehicles is measured with radar
at the midpoint of 0.8Km strip (0.5 mi) The
speeds are measured as 44,42,51,49 and 46 mi/h.
Assuming the vehicles were travelling constant
speed, determine the time mean speed. - Tim Mean speed Ut Sui/n (4442514946)/5
46.4 mi/h - The space mean
5/ 1/441/421/511/491/46 -
- 46.17 mi/h
- Space mean speed is always smaller than time mean
speed.
4Traffic density
- K n/l The No of vehicles per unit length.
- The density is also related to individual
spacing of the vehicles - The total length of roadway l S si
- k 1/( Mean space)
- Traffic flow q uk
- q flow of traffic No of vehicles/hour
- Speed ( Space mean speed)
- k density units of vehicle/mile.
- Example 5.2
5Traffic Flow
- Complex between vehicles and drivers, among
vehicles - Stochastic variability in outcome, cannot
predict with certainty - Theories and models
- Macroscopic aggregate, steady state
- Microscopic disaggregate, dynamics
- Human factor driver behavior
6Speed (v)
- Rate of motion
- Individual speed
- Average speed
- Time mean speed
- Arithmetic mean
- Space mean speed
- Harmonic mean
7Individual Speed
(1)
Spot Speed
8Time Mean Speed
Mile post
Observation Period
9Space Mean Speed
Observation Distance
Observation Period
10Volume (q)
- Number of vehicles passing a point during a given
time interval - Typically quantified by Rate of Flow (vehicles
per hour)
11Volume (q)
12Density (k)
- Number of vehicles occupying a given length of
roadway - Typically measured as vehicles per mile (vpm),
- or vehicles per mile per lane (vpmpl)
13Density (k)
14Density (k)
15Spacing (s)
- Front bumper to front bumper distance between
successive vehicles
S1-2
S2-3
16Headway (h)
- Time between successive vehicles passing a fixed
point
T3sec
T0 sec
h1-23sec
17Spacing and Headway
spacing
headway
18Spacing and Headway
What are the individual headways and the average
headway measured at location A during the 25 sec
period?
A
19Spacing and Headway
What are the individual headways and the average
headway measured at location A during the 25 sec
period?
A
h1-2
h2-3
20Lane Occupancy
- Ratio of roadway occupied by vehicles
L1
L2
L3
D
21Clearance (c) and Gap (g)
- Front bumper to back bumper distance and time
Clearance (ft) or Gap (sec)
Spacing (ft) or headway (sec)
22Basic Traffic Stream models
- 1. Speed density Model Relationship between
speed and density - Initially when there is only one vehicle, the
density is very low and driver will move freely
at the speed closely to the design speed of the
highway. This is called free flow speed. - When more and more vehicles would come, the
density of the road will increase and the speed
of vehicles would reduce. The speed of the
vehicle may ultimately reduce to u0 - This high traffic density is referred as Jam
Density - This model can be expressed as U Uf ( 1- k/kj)
- U Space mean speed in mi/h (km/h)
- Uf Free flow speed in mi/h
- k density in veh/mi ( veh/km)
- This gives relationship between traffic flow
speed and density - The speed density relationship tends to be non
linear at low density and very high density. - Non linear relationship at low densities that has
speed slowly declining from free flow to value - Linear relationship over the medium density
region ( speed declining linearly with the
density). - Non linear relationship near the traffic jam
density relationship
23Speed vs. Density
ufFree Flow Speed
Speed (mph)
kj Jam Density
Density (veh/mile)
24Basic Traffic Stream models
- Flow Density Model
- As we know that q uk and U Uf ( 1- k/kj)
- Parabolic density model q Uf ( k k2/Kj )
- The max flow rate qcap The highest flow rate
- The traffic density that corresponds to this
capacity flow rate is kcap and the corresponding
values qcap ,Kcap ,Ucap - dq/dk Uf (1-2k/kf ) 0 Since the free flow
speed cannot be zero. - Kcap Kj / 2
- Substituting the value Ucap ( k Kj /2kj )
Uf /2
25Flow vs. Density
Congested Flow
Optimal flow, capacity, qm
FLow (veh/hr)
kj Jam Density
kmOptimal density
Uncongested Flow
Density (veh/mile)
26Speed Flow Model
- This is parabolic relationship
- Two speeds are possible as it is quadratic
equation, up to the highway capacity - Similarly two densities are possible for given
flow
27Speed vs. Flow
ufFree Flow Speed
Uncongested Flow
um
Speed (mph)
Optimal flow, capacity, qm
Congested Flow
Flow (veh/hr)
28Example
At a section of highway in Islamabad the free
flow speed is 90km/h and capacity of 5000 veh/h.
During traffic census at a particular section
2500 vehicles were counted. Determine the space
mean speed of the vehicle. Solution The
traffic flow is related to the space mean speed
and jam density as The jam To determine the
jam density From above equation of traffic flow
we can rearrange the equation as
Both the speeds are feasible as
shown on previous slide
29Traffic Flow Models-Poisson Model
- The Poisson distribution
- Is a discrete (as opposed to continuous)
distribution - Is commonly referred to as a counting
distribution - Represents the count distribution of random events
30Poisson Distribution
P(n) probability of having n vehicles arrive in
time t ? average vehicle arrival rate in
vehicles per unit time t duration of time
interval over which vehicles are counted e base
of the natural logarithm (e2.718)
31Example
- An observer counts 360veh/h at a specific highway
location. Assuming the arrival of vehicles at
this point follows Poissons distribution.
Estimate the probabilities of 0,1,2,3,4 and 5
vehicles arriving in 20 sec time interval. - Solution
- The average arrival rate ? 360 veh/h
360/60x600.1 veh/sec - t20 sec
- For probability of no vehicle
- P(1) 0.271 P(2) 0.271 P(3) 0.180 P(4)
0.090 - For 5 or more vehicles
- P(ngt 5) 1-P(nlt5) 1-(0.1350.2710.2710.180.090
0.053 - Draw the histogram of the distribution
32Poisson Example
- Example
- Consider a 1-hour traffic volume of 120 vehicles,
during which the analyst is interested in
obtaining the distribution of 1-minute volume
counts
33Poisson Example
- What is the probability of more than 6 cars
arriving (in 1-min interval)?
34Poisson Example
- What is the probability of between 1 and 3 cars
arriving (in 1-min interval)?
35Poisson distribution
- The assumption of Poisson distributed vehicle
arrivals also implies a distribution of the time
intervals between the arrivals of successive
vehicles (i.e., time headway)
36Negative Exponential
- To demonstrate this, let the average arrival
rate, ?, be in units of vehicles per second, so
that
- Substituting into Poisson equation yields
(Eq. 5.25)
37Negative Exponential
- Note that the probability of having no vehicles
arrive in a time interval of length t i.e., P
(0) is equivalent to the probability of a
vehicle headway, h, being greater than or equal
to the time interval t.
38Negative Exponential
(Eq. 5.26)
Note
This distribution of vehicle headways is known as
the negative exponential distribution.
39Negative Exponential Example
- Assume vehicle arrivals are Poisson distributed
with an hourly traffic flow of 360
veh/h.Determine the probability that the
headway between successive vehicles will be less
than 8 seconds.Determine the probability that
the headway between successive vehicles will be
between 8 and 11 seconds.
40Negative Exponential Example
41Negative Exponential Example
42Negative Exponential
For q 360 veh/hr
43Negative Exponential