This document provides a review of optimal speed traffic models. It begins with introductions to traffic modeling approaches including microscopic and macroscopic models. Microscopic models describe individual vehicle dynamics while macroscopic models use aggregated quantities like density and flow. The optimal velocity model is then defined as a car-following model where vehicles accelerate/decelerate to match an optimal speed based on headway. Properties, applications, and limitations of the optimal velocity model are discussed. Research on extensions like the full velocity difference model is also summarized. The document concludes with recommendations for further studying simulation problems to improve understanding of jam formation and congestion dynamics.
Being an Assignment, submitted to the Department of Civil Engineering Bayero University Kano Master of Engineering May, 2017
Guided by Professor Hashim M. Alhassan
Exploring Queuing Theory to Minimize Traffic Congestion Problem in Calabar-Hi...Premier Publishers
Traffic congestion has been a serious problem that drivers are facing especially in Calabar – highway by IBB road intersection. In this paper, emphasis is placed on model formation and derivation of some parameters that will help to facilitate the flow of vehicles in this intersection to reduce traffic congestion. The channel considered in this research is multiple queue single servers. We derived variance waiting time of vehicles in the queue and in the system, expected number of vehicles in the queue and in the system waiting for service, expected waiting time of vehicles in the queue and in the system. We also determine the time each vehicle spends in the queue waiting for service and the mean queue length for all the channels in each section. The result shows fair traffic congestion in Calabar – highway by IBB road intersection especially in the morning and evening hours for all the locations.
A Review on Road Traffic Models for Intelligent Transportation System (ITS)IJSRD
Traffic flow models seek to describe the interaction of vehicles with their drivers and the infrastructure. Almost all the models directly or indirectly characterize the relationship among the traffic variables: the position, the speed, the flow, and the density of vehicles. These relationships can be based on either the behavior of individual vehicles in a traffic network in relation to the dynamics of other vehicles, the overall characteristics of the flow of vehicles in a traffic network, or a combination of the behavior of individual vehicles in a traffic network and the overall traffic flow characteristics. This paper describes the different models for automatic Traffic control system.
Being an Assignment, submitted to the Department of Civil Engineering Bayero University Kano Master of Engineering May, 2017
Guided by Professor Hashim M. Alhassan
Exploring Queuing Theory to Minimize Traffic Congestion Problem in Calabar-Hi...Premier Publishers
Traffic congestion has been a serious problem that drivers are facing especially in Calabar – highway by IBB road intersection. In this paper, emphasis is placed on model formation and derivation of some parameters that will help to facilitate the flow of vehicles in this intersection to reduce traffic congestion. The channel considered in this research is multiple queue single servers. We derived variance waiting time of vehicles in the queue and in the system, expected number of vehicles in the queue and in the system waiting for service, expected waiting time of vehicles in the queue and in the system. We also determine the time each vehicle spends in the queue waiting for service and the mean queue length for all the channels in each section. The result shows fair traffic congestion in Calabar – highway by IBB road intersection especially in the morning and evening hours for all the locations.
A Review on Road Traffic Models for Intelligent Transportation System (ITS)IJSRD
Traffic flow models seek to describe the interaction of vehicles with their drivers and the infrastructure. Almost all the models directly or indirectly characterize the relationship among the traffic variables: the position, the speed, the flow, and the density of vehicles. These relationships can be based on either the behavior of individual vehicles in a traffic network in relation to the dynamics of other vehicles, the overall characteristics of the flow of vehicles in a traffic network, or a combination of the behavior of individual vehicles in a traffic network and the overall traffic flow characteristics. This paper describes the different models for automatic Traffic control system.
Application of a Markov chain traffic model to the Greater Philadelphia RegionJoseph Reiter
A macroscopic traffic model based on the Markov chain process is developed for urban traffic networks. The method utilizes existing census data rather than measurements of traffic to create parameters for the model. Four versions of the model are applied to the Philadelphia regional highway network and evaluated based on their ability to predict segments of highway that possess heavy traffic.
Car-Following Parameters by Means of Cellular Automata in the Case of EvacuationCSCJournals
This study is attention to the car-following model, an important part in the micro traffic flow. Different from Nagel–Schreckenberg’s studies in which car-following model without agent drivers and diligent ones, agent drivers and diligent ones are proposed in the car-following part in this work and lane-changing is also presented in the model. The impact of agent drivers and diligent ones under certain circumstances such as in the case of evacuation is considered. Based on simulation results, the relations between evacuation time and diligent drivers are obtained by using different amounts of agent drivers; comparison between previous (Nagel–Schreckenberg) and proposed model is also found in order to find the evacuation time. Besides, the effectiveness of reduction the evacuation time is presented for various agent drivers and diligent ones.
Macroscopic Traffic Flow model for nepalese roadsHemant Tiwari
This research deals with the calibration of various conventional macroscopic traffic flow models of Nepalese Roads and recommend the best suitable model after undergoing calibration and validation process.
Application of a Markov chain traffic model to the Greater Philadelphia RegionJoseph Reiter
A macroscopic traffic model based on the Markov chain process is developed for urban traffic networks. The method utilizes existing census data rather than measurements of traffic to create parameters for the model. Four versions of the model are applied to the Philadelphia regional highway network and evaluated based on their ability to predict segments of highway that possess heavy traffic.
Car-Following Parameters by Means of Cellular Automata in the Case of EvacuationCSCJournals
This study is attention to the car-following model, an important part in the micro traffic flow. Different from Nagel–Schreckenberg’s studies in which car-following model without agent drivers and diligent ones, agent drivers and diligent ones are proposed in the car-following part in this work and lane-changing is also presented in the model. The impact of agent drivers and diligent ones under certain circumstances such as in the case of evacuation is considered. Based on simulation results, the relations between evacuation time and diligent drivers are obtained by using different amounts of agent drivers; comparison between previous (Nagel–Schreckenberg) and proposed model is also found in order to find the evacuation time. Besides, the effectiveness of reduction the evacuation time is presented for various agent drivers and diligent ones.
Macroscopic Traffic Flow model for nepalese roadsHemant Tiwari
This research deals with the calibration of various conventional macroscopic traffic flow models of Nepalese Roads and recommend the best suitable model after undergoing calibration and validation process.
1
Intermodal Autonomous Mobility-on-Demand
Mauro Salazar1,2, Nicolas Lanzetti1,2, Federico Rossi2, Maximilian Schiffer2,3, and Marco Pavone2
Abstract—In this paper we study models and coordination poli-
cies for intermodal Autonomous Mobility-on-Demand (AMoD),
wherein a fleet of self-driving vehicles provides on-demand
mobility jointly with public transit. Specifically, we first present
a network flow model for intermodal AMoD, where we capture
the coupling between AMoD and public transit and the goal is
to maximize social welfare. Second, leveraging such a model,
we design a pricing and tolling scheme that allows the system
to recover a social optimum under the assumption of a perfect
market with selfish agents. Third, we present real-world case
studies for the transportation networks of New York City and
Berlin, which allow us to quantify the general benefits of
intermodal AMoD, as well as the societal impact of different
vehicles. In particular, we show that vehicle size and powertrain
type heavily affect intermodal routing decisions and, thus, system
efficiency. Our studies reveal that the cooperation between AMoD
fleets and public transit can yield significant benefits compared
to an AMoD system operating in isolation, whilst our proposed
tolling policies appear to be in line with recent discussions for
the case of New York City.
I. INTRODUCTION
TRAFFIC congestion is soaring all around the world. Besidesmere discomfort for passengers, congestion causes severe
economic and environmental harm, e.g., due to the loss of
working hours and pollutant emissions such as CO2, partic-
ulate matter, and NOx [1]. In 2013, traffic congestion cost
U.S. citizens 124 Billion USD [2]. Notably, transportation
remains one of a few sectors in which emissions are still
increasing [3]. Governments and municipalities are struggling
to find sustainable ways of transportation that can match
mobility needs and reduce environmental harm as well as
congestion.
To achieve sustainable modes of transportation, new mobil-
ity concepts and technology changes are necessary. However,
the potential to realize such concepts in urban environments is
limited, since upgrades to available infrastructures (e.g., roads
and subway lines) and their capacity are often extremely costly
and require decades-long planning timelines. Thus, mobility
concepts that use existing infrastructure in a more efficient way
are especially attractive. In this course, mobility-on-demand
services appear to be particularly promising. Herein, two main
concepts exist. On the one hand, free floating car sharing
systems strive to reduce the total number of private vehicles
in city centers. However, these systems offer limited flexibility
and are generally characterized by low adoption rates that
result from low vehicle availabilities due to the difficulty of
1Institute for Dynamic Systems and Control ETH Zürich, Zurich (ZH),
Switzerland {samauro,lnicolas}@ethz.ch
2Department of Aeronautics and Astro.
A New Paradigm in User Equilibrium-Application in Managed Lane PricingCSCJournals
Ineffective use of the High-Occupancy-Vehicle (HOV) lanes has the potential to decrease the overall roadway throughput during peak periods. Excess capacity in HOV lanes during peak periods can be made available to other types of vehicles, including single occupancy vehicles (SOV) for a price (toll). Such dual use lanes are known as “Managed Lanes.” The main purpose of this research is to propose a new paradigm in user equilibrium to predict the travel demand for determining the optimal fare policy for managed lane facilities. Depending on their value of time, motorists may choose to travel on Managed Lanes (ML) or General Purpose Lanes (GPL). In this study, the features in the software called Toll Pricing Modeler version 4.3 (TPM-4.3) are described. TPM-4.3 is developed based on this new user equilibrium concept and utilizes it to examine various operating scenarios. The software has two built-in operating objective options: 1) what would the ML operating speed be for a specified SOV toll, or 2) what should the SOV toll be for a desired minimum ML operating speed. A number of pricing policy scenarios are developed and examined on the proposed managed lane segment on Interstate 30 (I-30) in Grand Prairie, Texas. The software provides quantitative estimates of various factors including toll revenue, emissions and system performance such as person movement and traffic speed on managed and general purpose lanes. Overall, among the scenarios examined, higher toll rates tend to generate higher toll revenues, reduce overall CO and NOx emissions, and shift demand to general purpose lanes. On the other hand, HOV preferential treatments at any given toll level tend to reduce toll revenue, have no impact on or reduce system performance on managed lanes, and increase CO and NOx emissions.
Modeling business management systems transportationSherin El-Rashied
Introduction
How IT &Business Process Fit Together
What is modeling?
What is Simulation?
Modeling & Simulation in Business Process Management
The Seven-Step Model-Building Process
Transportation
An overview on transportation modeling
Transport model scope & structure
Car Traffic Jam Problem
Aim of Transportation Model
Types of Traffic Models
Microscopic Traffic model & Simulation
Cellular Automaton model
Conclusion
Solving Transportation Problem by Software Application
Class Example
Traffic State Estimation and Prediction under Heterogeneous Traffic ConditionsIDES Editor
The recent economic growth in developing countries
like India has resulted in an intense increase of vehicle
ownership and use, as witnessed by severe traffic congestion
and bottlenecks during peak hours in most of the metropolitan
cities. Intelligent Transportation Systems (ITS) aim to reduce
traffic congestion by adopting various strategies such as
providing pre-trip and en-route traffic information thereby
reducing demand, adaptive signal control for area wide
optimization of traffic flow, etc. The successful deployment
and the reliability of these systems largely depend on the
accurate estimation of the current traffic state and quick and
reliable prediction to future time steps. At a macroscopic level,
this involves the prediction of fundamental traffic stream
parameters which include speed, density and flow in spacetime
domain. The complexity of prediction is enhanced by
heterogeneous traffic conditions as prevailing in India due to
less lane discipline and complex interactions among different
vehicle types. Also, there is no exclusive traffic flow model for
heterogeneous traffic conditions which can characterize the
traffic stream at a macroscopic level. Hence, the present study
tries to explore the applicability of an existing macroscopic
model, namely the Lighthill-Whitham-Richards (LWR) model,
for short term prediction of traffic flow in a busy arterial in
the city of Chennai, India, under heterogeneous traffic
conditions. Both linear and exponential speed-density
relations were considered and incorporated into the
macroscopic model. The resulting partial differential
equations are solved numerically and the results are found to
be encouraging. This model can ultimately be helpful for the
implementation of ATIS/ATMS applications under
heterogeneous traffic environment.
Presentation on advance traffic engineering.pptxEtahEneji1
This presentation was done to fulfil the course requirement for the pursuit of my M. ENG on the course title: Advanced traffic engineering Course code : (CIV 8331).
Course Lecturer : ENGR. PROF H. M. AlHASSAN
Motorcycle Movement Model Based on Markov Chain Process in Mixed TrafficIJECEIAES
Mixed traffic systems are dynamically complex since there are many parameters and variables that influence the interactions between the different kinds of vehicles. Modeling the behavior of vehicles, especially motorcycle which has erratic behavior is still being developed continuously, especially in developing countries which have heterogeneous traffic. To get a better understanding of motorcycle behavior, one can look at maneuvers performed by drivers. In this research, we tried to build a model of motorcycle movement which only focused on maneuver action to avoid the obstacle along with the trajectories using a Markov Chain approach. In Markov Chain, the maneuver of motorcycle will described by state transition. The state transition model is depend on probability function which will use for determine what action will be executed next. The maneuver of motorcycle using Markov Chain model was validated by comparing the analytical result with the naturalistic data, with similarity is calculated using MSE. In order to know how good our proposed method can describe the maneuver of motorcycle, we try to compare the MSE of the trajectory based on Markov Chain model with those using polynomial approach. The MSE results showed the performance of Markov Chain Model give the smallest MSE which 0.7666 about 0.24 better than 4 order polynomial.
IMPORTANCE OF REALISTIC MOBILITY MODELS FOR VANET NETWORK SIMULATIONIJCNCJournal
In the performance evaluation of a protocol for a vehicular ad hoc network, the protocol should be tested under a realistic conditions including, representative data traffic models, and realistic movements of the mobile nodes which are the vehicles (i.e., a mobility model). This work is a comparative study between two mobility models that are used in the simulations of vehicular networks, i.e., MOVE (MObility model generator for VEhicular networks) and CityMob, a mobility pattern generator for VANET. We describe several mobility models for VANET simulations.
In this paper we aim to show that the mobility models can significantly affect the simulation results in VANET networks. The results presented in this article prove the importance of choosing a suitable real world scenario for performances studies of routing protocols in this kind of network.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
1. PRESENTATION
R E V IE W O F O P T IM A L S P E E D T R A F F IC
M O D E L
Y U N U S A H A M I S U G A B A S AWA
( S P S / 1 6 / M E C / 0 0 0 6 6 )
M . E N G I N C I V I L E N G I N E E R I N G A S S I G N M E N T,
S U B M I T T E D
T O
P R O F, H . M . A L H A S S A N
C IV IL E N G IN E E R IG D E PA RT M E N T
B AY E R O U N IV E R S IT Y K A N O ,
N IG E R IA
2. GENERAL INTRODUCTION.
Recently, traffic problems have attracted
considerable attention, due to the fact that
traffic behavior is important in our lives.
When car density increases, traffic jams
appear. A variety of approaches have been
applied to describe the collective properties
of traffic flow: car-following models,
cellular automaton models, gas kinetic
models, and hydrodynamic models.
3. GENERAL INTRODUCTION CONT.
The traffic flow models are classified into the
deterministic and stochastic models. Nagel and
Schreckenberg have introduced a stochastic
cellular automaton model. It has been shown
that the start-stop waves (traffic jams) appear
in the congested traffic region as observed in
real freeway traffic. Bando et al. have proposed
the deterministic optimal velocity model in
which a car accelerates or decelerates according
to the dynamic equation of car motion with the
optimal velocity function.
4. INTRODUCTION AND HISTORY OF MODELS
MICROSCOPIC TRAFFIC MODELS
Microscopic traffic flow models describe
dynamics of traffic flow at the level of each
individual vehicle. They have existed since the
1960s with the typical car-following models.
• Car-following models describe the processes
in which drivers follow each other in the traffic
stream. The car-following process is of the
main processes in all microscopic models as
well as in modern traffic flow.
5. MICROSCOPIC TRAFFIC MODELS
• Microscopic traffic flow models describe
dynamics of traffic flow at the level of each
individual vehicle. They have existed since the
1960s with the typical car-following models.
• Car-following models describe the processes
in which drivers follow each other in the
traffic stream. The car-following process is of
the main processes in all microscopic models
as well as in modern traffic flow.
6. CAR FOLLOWING MODELS,
Is one of the most useful tools for
traffic dynamics, have been developed
more than six decades. There are two
main objectives in the car process:
(ⅰ) Reducing the speed difference and
(ⅱ) Maintain an appropriate spacing
between the following vehicle and the
leading vehicle.
8. DEFINATION OF OPTIMAL SPEED MODEL
Optimal speed limit can be defined as process or
situation where by a moving vehicle attain and
maintain maximum legally permitted design pavement
speed limit on a freeway or maintain a maximum
legally permitted speed limit of a moving vehicle over
a period of time on an free way (Flow stream) without
accelerating further of the permitted speed limit.
Optimum speed limit varies across the globe because
each country base on their nature of their road set an
optimum speed limit by their legislative also enforced
by either police or road related agencies. Example
10mph in 1861 by UK, Switzerland 120km/hr in 1994,
Australia 100km/hr in 1996 etc.
9. OPTIMAL VELOCITY MODEL
The Optimal Velocity Model (OVM) is a time-
continuous model whose acceleration function is of
the form am ic (s,v), i.e., the speed difference
exogenous variable is missing. The acceleration
equation is given by
=
𝑣𝑜𝑝𝑡 𝑠 − 𝑣
𝑡
𝑜𝑝𝑡𝑖𝑚𝑎𝑙 𝑣𝑒𝑙𝑜𝑐𝑡𝑦 𝑀𝑜𝑑𝑒𝑙 (1)
This equation describes the adaption of the actual
speed v=v α to the optimal velocity v opt(s)on a time
scale given by the adaptation time τ. Comparing the
acceleration equation with the steady-state condition
it becomes evident that the optimal velocity (OV)
function 14vopt(s)is equivalent to the microscopic
fundamental diagram ve(s). It should obey the
plausibility conditions.
10. PROPERTIES OF OPTIMAL SPEED
MODEL.
1•On a quantitative level, the OVM results are
unrealistic.
2• On a qualitative level, the simulation outcome has a
strong dependency on the fine tuning of the model
parameters, i.e., the OVM is not robust.
3 • These deficiencies are mainly due to the fact that
the OVM acceleration function does not contain
the speed difference as exogenous variable.
4 • the simulated driver reaction depends only on the
gap but is the same whether the leading vehicle is
slower or faster than the subject vehicle. This
corresponds to an extremely shortsighted
driving style.
11. FULL VELOCITY DIFFERENCE MODEL
in 2006, Zhi peng and yui- cai conducted a detailed
analysis of FVDM As in the OVM, the steady-state
equilibrium is directly given by the optimal velocity
Function v opt. When assuming suitable values for the
speed difference sensitivity γ of the order of, the
FVDM remains accident-free for speed adaptation
times of the order of several seconds. It turns out that
model is able to realistically simulate the cruising
phase, in contrast to the original model , and produces
realistic accelerations, in contrast to the OVM.
12. MICROSCOPIC TRAFFIC MODEL
Microscopic models typically refer to
simulation models that include
randomized characteristics and
behaviors of an array of drivers and
vehicles as they traverse a network.
The performance of these models is
typically averaged over several “runs”
to account for the randomized driver
and vehicle characteristics.
13. (Bando et al., 1995). The optimal velocity
model has not the ability to explain only
individual behavior of a vehicle, but also
its connectivity to some mac-roscopic
values such as traffic flow and density
(Nugrahani, 2013). As mentioned, there
are two major approaches to describe
the traffic flow problem.
14. MACROSCOPIC TRAFFIC FLOW
Macroscopic Traffic models make use of
the picture of traffic flow as a physical
flow of a fluid. They describe the traffic
dynamics in terms of aggre-gated
macroscopic quantities such as the
traffic density, traffic flow or the average
velocity as a function of space and time
cor-responding to partial differential
equations. By way of contrast,
microscopic traffic models describe the
motion of each indi-vidual vehicle. They
model the action, such as accelerations,
decelerations and lane changes of each
driver as a response to the surrounding
traffic.
15. MACROSCOPIC TRAFFIC FLOW FIG
(Kesting et al., 2008) (Fig. 1).
Fig. 1Illustration of different traffic modeling
approaches
16. GREENSHIELD’S MODEL
The Greenshield’s model represents how
the behavior of one parameter of traffic
flow changes with respect to another.
The most simple relation between speed
and density is proposed by green shield
and scalled the fundamental relation or
fundamen-tal diagram later (van
Wageningen, 2014; Jabeena, 2013).
17. MICROSCOPIC TRAFFIC MODEL
CON’T
Unlike macroscopic models, traffic demand
values are generally inputs and typically do not
result from path choice within the model,
therefore, there may not be a predetermined
throughput. As a result, assigned traffic
volumes at specific locations such as midblock
or a turn movement may not match the input
demand due to constraints on the network
metering flow. For example, queues will build in
a microscopic model and only vehicles that can
make it through a bottleneck in a given time
period will be observed.
18. ADVANTAGE OF OPTIMAL SPEED MODEL.
It reduce fuel consumption
It reduce accident rate
It makes driving safer
It helps in maintaining the design life span of the
pavement.
It reduces pollution.
It increase traffic flow speed and its stability
It prevent over speeding
19. DISADVANTAGE OF OPTIMUM SPEED MODEL
* It wastes time for commercial drivers that
are used to
* travel with high speed.
* It cause s over speeding
* It increase accident
* It causes road dilapidation .
20. LIMITATION AND CHARACTERISTIC OF
OPTIMUM SPEED LIMIT
LIMITATION OF OPTIMUM SPEED MODEL
The OVM does not have a time delay in its model
expression, which makes it convenient for theoretical
analysis.
The optimal speed function assumes that there is a one-
to-one correspondence between the spatial headway
and the optimal driving speed in steady traffic state.
21. CHARACTERISTIC OF OPTIMUM SPEED LIMIT
1. Synthesize existing knowledge about speed and factors that
either influence speed or are an outcome of speed such as Safety,
Environmental Impacts, Road User Costs
2. To analyze speed data to determine the vehicle operating speed
impacts from different vehicle classifications, temporal factors,
environmental factors, and road factors. Such as Road
Engineering, Regulatory and Enforcement Environment, Driver
Attitude and Behaviour, Weather Factors, Temporal Factors,
Vehicle Classification,
22. APPLICATION
Optimal velocity models are also used to:
Describe many properties of traffic flows
Evolution of traffic congestion
Formation of stop and go waves
Analysis of rear end collision
Application to intelligent, especially how to
suppress the emergence of traffic congestion.
23. RESEARCH ON OPTIMAL SPEED MODELS
Some of the researches on the optimal speed models are
as follows;
Optimal speed advisory for connecting vehicles in arterial
road and the impact on mixed traffic by Nianfeng Wan,
ArdalanVahidi, Andre Luckow.
Effect of optimal estimation of flux difference information
on the lattice traffic flow model by Shu-hongYang,Chun-
guiLi∗,Xin-laiTang,ChuanTian.
Traffic simulation models calibration using speed–density
relationship: An automated procedure based on genetic
algorithm by SandroChiapponea, OrazioGiuffrèa, Anna
Granàa,∗, RaffaeleMauroc, Antonino SferlazzabQ1.
Speed management in rural two-way roads: speed limit
definition through expert-based system. Nuno Gregórioa,*,
Ana BastosSilvaa, Alvaro Secoa.
Evidence for speed flow relationships Nicholas Taylor (TRL,
ntaylor@trl.co.uk) Nathan Bourne (TRL) Simon Notley (TRL)
George Skrobanski (English Highways Agency).
24. CONCLUTION
It can be concluded that, it is
difficult to accurately predict
the behavior of drivers during
jam formation and congestion.
And also it is very difficult to
predict optimal speed function
such situation,
25. RECOMMENDATIONS
Based on the above observation, it is
recommended that study should continue
to be carried out so as to cover simulation
problem with intension to have result that
will show in future. It is also
recommended to African Countries’s
researchers to go deep in to the world of
optimal speed traffic model research with
intention to come up with a lot of
solutions to traffic problems.
26. REFERENCES.
M. Bando, K(1995). Hasebe, A. Nakayama, A. Shibata, and Y.
Sugiyama, “Dynamical Modelof Traffic Congestion and
Numerical Simulation”, Phys. Rev. E 51, 1035-1042 (1995).[2] M.
Bando, K. Hasebe, A. Nakayama, A. Shibata, and Y. Sugiyama,
“Structure Stability of Congestion in Traffic Dynamics”, Japan
Journal of Industrial and Applied Mathemat-ics 11, 203-223
(1994).[3] M. Bando, K. Hasebe, K. Nakanishi, A. Nakayama, A.
Shibata, and Y. Sugiyama,Aghabayk, K., Sarvi, M., Young, W.
(2015) A State-of the-Art Review of Car-Following Models with
Particular Considerations of Heavy Vehicles. Transport Reviews.
35(1), pp. 82-105.