Traffic simulation models provide an effective way to study complex traffic flow phenomena without costly and time-consuming real-world data collection and experimentation. Simulation models allow researchers to reproduce dynamic traffic conditions over time through micro, meso, or macroscopic representations. The development of accurate traffic simulation involves defining the problem, collecting field input data, establishing logical relationships between modeled elements, programming the simulation, calibrating and validating the model against real data.

1. Traffic Simulation
Prepared By:
Mr.Praful Shinkar
Assistant Professor and PG In-Charge

2. Introduction
• Traffic flow phenomenon consists of a wide range of complex activities,
embracing vehicle arrivals, speed of travel, lane discipline, overtaking and
crossing logic, gap acceptance, acceleration and deceleration etc..
• Different road characteristics will be govern by vehicle performance,
characteristics and behaviour of road user
• The understanding of traffic flow can be attain by observing how the vehicles
move into the traffic stream by mathematical models, or analytical methods
• The science of this study has been developed with this approach

4. Cont..
• The analytical approach requires that field data be collected on a large scale. i.e
if a proper understanding of a complex heterogeneous traffic on Indian Road is
to be achieved, real life observations need to be collected
• Like pavement widths, roughness, curvature, vertical profile etc. so it is tedious
• Time consuming and expensive
• At last if still it has been done but the results are uncertain

5. Traffic Models
Traffic Flow
Models
Level of Details
Micro Meso Macro
Operationalisation
Analytical Simulation

6. Cont..
• The analytical models are, where the solution to a set of differential equations
describing the traffic system is obtained analytically (using calculus)
• Analytical models can be static and dynamic
• Numerical methods are used for solutions
• But analytical models require large amount of field data such as, road width,
lane width, roughness, complete information on geometric design, vehicle
composition, type, traffic volumes, speeds & density etc.
• Extremely costly & tedious
• Often uncertainties are involved in the data

7. Cont…
• The simulation models are, where the successive changes of the traffic system
over time (space-time dynamics) are reproduced (approximated) in the model.
• Simulation models are dynamic
• Macroscopic, mesoscopic and microscopic

8. Development of Simulation
• New technique to solve the traffic problems
• It is a working analogy of real life problems into a computer based model
• It is a technique where some part of a real world is represented dynamically by
building a computer model, running the model through time to solve problems
having any given constraints and inputs

9. Advantages
• It is cheaper than any other on field methods
• It is a powerful tool for comparing the consequences of a number of alternative
strategies and improvement plan
• Better involvement of competent authority
• In real life situations . It will be difficult to obtain conditions in the field which
are needed for building a better analytical formulation
• These techniques can be employed to check uncertain analytical solution
• These techniques provide opportunity for controlled experimentation, altering
one variable at a time or specific variables simultaneously

10. Cont..
• Some of the solutions are doughtful in nature, simulation can overcome with
such deficiencies
• Simulation models are transparent

11. Main factors of traffic simulation
1. Advanced research in traffic theory
2. Advancement in computer hardware technology
3. Advancement in computer software technology
4. Development in information, communication infrastructure
5. Increased importance of traffic and transportation in the society

12. Road Traffic as a Simulation Object
1. Transport networks cover wide physical areas
2. Large number of active participants or users and interaction among them
3. Objectives of the participants can be individualistic or social
4. Presence of independent variables outside the control of the operator and the
participants (the weather conditions, the number of users, etc.)
5. The road & highway traffic variables can be stochastic (inherent randomness)
and time varying in nature
6. Transportation systems involve both human interaction and vehicle
interaction with surroundings

13. Steps
Definition of problem
Field studies to determine inputs
Development of logic
Development of Computer
Simulation Programme
Calibration of model
Simulation runs covering actual
conditions
Validation of model

14. Development of Logic
• Certain activities in the models are inter related through some logic which has
to be established by the modeller
• For example for a given “T” intersection problem, the vehicle arriving at the side
road have to wait for suitable gaps in the traffic stream in the main road. Drivers
accept gaps which are safe, some are taking risks
• So, a logic in the modeller needed to be established