This document presents an overview of microscopic traffic flow modeling. It discusses the objectives of traffic flow modeling like reducing congestion and optimizing traffic. It classifies models as macroscopic, mesoscopic, and microscopic. Microscopic models attempt to analyze traffic by modeling driver-driver and driver-road interactions. Various car following models are described, including the Pipes, Forbes, General Motors, Optimal Velocity, and Wiedemann models. Microscopic models help analyze small changes in traffic over time and space to better understand traffic behavior.

1. MICROSCOPIC TRAFFIC STREAM MODEL
PRESENTED BY:
PEAKA RAKESH (2021423)
SAURABH KUMAR (2021424)
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2. Contents:
 Introduction
 Objectives of traffic flow modelling
 Classification of traffic flow models
 Microscopic models
 Conclusion
 Reference
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3. Introduction:
 TRAFFIC FLOW: It is the flow of the
vehicles on the road or highways etc.
 By the effective study of traffic
facilities such as freeways , signalized
and un-signalized intersections gives
the better designing of traffic
facilities.
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4. Objectives of traffic flow modelling:
 To reduce the traffic congestion.
 Understanding the reasons for traffic jam.
 To optimize the traffic flow.
 It is used to stimulate traffic.
 These models can be used to improve road safety.
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5. Classification of traffic models:
 Macroscopic traffic flow model
 Mesoscopic traffic flow model
 Microscopic traffic flow
 Sub-microscopic traffic model
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6. Microscopic traffic flow modelling:
 Microscopic model of traffic flow attempt to analyze the flow of a
traffic by modelling driver-driver, and driver-road interactions
within a traffic stream.
 Driver-Driver interactions means how a driver reacts to the actions
of a another driver and driver-road interactions means how a driver
reacts to various features of roads such as narrow width, curves etc.
 So, basically microscopic traffic flow model is a driver behaviour
model.
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7. Fundamental variables:
 Distance headway is defined as the distance from a
selected point (usually front bumper) on the lead
vehicle to the corresponding point on the following
vehicles.
 Time headway is defined as the time difference
between any two successive vehicles when they
cross a given point.
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8.  Over the years various models of driver behaviour in
different driving situations have been developed.
Some are based on the presence of static obstacles and
some are based on driver behaviour in car following
situations.
The car following models are as follows:
1) Pipes model
2) Forbes model
3) General motors model
4) Optimal velocity model
5) Wiedemann model
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9. 1) Pipes model: The first car-following models were prepared by pipes
(1953).
* The basic assumption of this model is “A good rule for following another
vehicle at a safe distance is to allow yourself at least the length of a car between
your vehicle and the vehicle ahead at which you are traveling”.
* A disadvantage of this model is that at low speeds, the minimum
headways proposed by the theory are considerably less than the corresponding
field measurements.
2) Forbe’s model: A similar approach was proposed by Forbe’s at (1956).
* In this model, the reaction time needed for the following vehicle to
aware of the need to decelerate and apply the brakes is considered.
* A disadvantage of this model is that, similar to Pipe’s model, there is a
wide difference in the minimum distance headway at low and high speeds.
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10. 3) General motor’s model : The General Motors’ model is the most
popular of the car-following theories because of the following reasons:
1. This models shows good correlation to the field data.
2.Greenberg’s logarithmic model for speed-density relationship can
be derived from General motors car following model.
Major problem with this model is
it only considers the relative speed
i.e The Rate of change of distance
headway.
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11. 4) Optimal velocity model: Whereas the previous car-following
models mostly describe the behaviour of a vehicle that is following a
leader, the OVMs modify the acceleration mechanism, such that a vehicle’s
desired speed is selected on the basis of its space headway, instead of only
considering the speed of the leading vehicle.
The formulation is based on the assumption of desired speed based on the
distance headway of nth vehicle.
Where 1/T is called sensitive coefficient.
Where nth vehicle tries to maintain the safe speed.
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12. 5)Wiedeman’s model :The Wiedemann model uses random
numbers in order to create heterogeneous traffic stream behavior
* These random numbers are meant to simulate behaviour of
different drivers.
* The naturalistic data is a perfect match for this situation
because the data is collected by individual drivers. Data for three
different drivers was selected and processed in order to calibrate
the Wiedemann car-following model.
* Future research is recommended in the development and
implementation of driver’s aggression profile in this model.
* More no.of profiles needed to gain more accurate
stimulation of traffic flow.
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13. Conclusion:
 Microscopic traffic flow modeling focuses on the minute aspects of
traffic stream like vehicle to vehicle interaction and individual
vehicle behavior.
 They help to analyze very small changes in the traffic stream over
time and space.
 Car following model is one such model where in the stimulus-
response concept is employed.
 The traffic stream models attempt to establish a better relationship
between the traffic parameters.
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14. Reference:
 Principles of Transportation engineering by Partha Chakroborty and
Animesh Das.
 NEPTEL Traffic Engineering and Management
 Analysis of the Wiedemann Car Following Model over Different
Speeds by Bryan Higgs
 Transportation Planning and Traffic Flow Models by Sven
Maerivoet and Bart De Moor.
 Google images.
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15. THANK YOU
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