This document provides a review and analysis of the optimal speed model. It discusses:
1) The theoretical models that support the optimal speed model including microscopic, mesoscopic, and macroscopic traffic flow models.
2) Problems with the original optimal speed model including unrealistic behavior, instability, and stop-and-go waves.
3) A proposed double boundary optimal velocity function model that allows vehicles to operate within a range of speeds and spacings rather than at a single optimal point. This addresses issues with the original model.
Adjusting the flow in crucial areas can maximize the overall throughput of traffic along a stretch of road. This is of particular interest in regions of high traffic density, which may be caused by high volume peak time traffic, accidents or closure of one or more lanes of the road.
Adjusting the flow in crucial areas can maximize the overall throughput of traffic along a stretch of road. This is of particular interest in regions of high traffic density, which may be caused by high volume peak time traffic, accidents or closure of one or more lanes of the road.
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.
Presentation by Professor Toshio YOSHII of Ehime University of Japan, delivered as a guest seminar during a visit to the Institute for Transport Studies, July 2014.
It is well known that traffic accident tends to occur more in congested flow state than in flee flow state. The developing simulation can estimate the traffic accident risk considering these traffic states. The traffic accident risk shows the likelihood of the occurrence of accidents. 3 traffic states are considered in the analysis, which are free flow, congested flow and mixed flow. The simulation can estimate traffic states at each link and using these states the risk estimation model can estimate traffic accident risks. The risk estimation model has been developed by Poisson regression analysis. The results of the Poisson regression analysis is presented.
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.
2019-2020 research findings in Public Transit from the Centre for Transport Studies, University of TWENTE. The presented findings at the Transportation Research board include overcrowding, operational control, electric buses, and train assignment.
Experimental Comparison of Trajectory Planning Algorithms for Wheeled Mobile ...IJRES Journal
In this paper, we present an experimental approach to compare various trajectory planning methods for practical application of wheeled mobile robots. The first method generates a trajectory according to the acceleration limits of the mobile robot and its relationship with the curvature of the planned path. The second method is an improvement of the conventional convolution-based trajectory generation method, on which the heading angles of a curved path is being considered. Due to the limited scope of the considered constraints of the previous approaches, A third approach that conserves the merits of the convolution operator is proposed to consider the high curvature turning points of a sophisticated curve such as a Lemniscate of Gerono,which causes geometrical limitations during robot navigation. All methods are compared experimentally on a two-wheeled mobile robot. The goal of the experiment is to determine which approach meets the criteria of time optimality and sampling time uniformity while considering the physical limits of the mobile robot and the geometrical constraints of the planned path.
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.
Presentation by Professor Toshio YOSHII of Ehime University of Japan, delivered as a guest seminar during a visit to the Institute for Transport Studies, July 2014.
It is well known that traffic accident tends to occur more in congested flow state than in flee flow state. The developing simulation can estimate the traffic accident risk considering these traffic states. The traffic accident risk shows the likelihood of the occurrence of accidents. 3 traffic states are considered in the analysis, which are free flow, congested flow and mixed flow. The simulation can estimate traffic states at each link and using these states the risk estimation model can estimate traffic accident risks. The risk estimation model has been developed by Poisson regression analysis. The results of the Poisson regression analysis is presented.
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.
2019-2020 research findings in Public Transit from the Centre for Transport Studies, University of TWENTE. The presented findings at the Transportation Research board include overcrowding, operational control, electric buses, and train assignment.
Experimental Comparison of Trajectory Planning Algorithms for Wheeled Mobile ...IJRES Journal
In this paper, we present an experimental approach to compare various trajectory planning methods for practical application of wheeled mobile robots. The first method generates a trajectory according to the acceleration limits of the mobile robot and its relationship with the curvature of the planned path. The second method is an improvement of the conventional convolution-based trajectory generation method, on which the heading angles of a curved path is being considered. Due to the limited scope of the considered constraints of the previous approaches, A third approach that conserves the merits of the convolution operator is proposed to consider the high curvature turning points of a sophisticated curve such as a Lemniscate of Gerono,which causes geometrical limitations during robot navigation. All methods are compared experimentally on a two-wheeled mobile robot. The goal of the experiment is to determine which approach meets the criteria of time optimality and sampling time uniformity while considering the physical limits of the mobile robot and the geometrical constraints of the planned path.
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
Vehicle Headway Distribution Models on Two-Lane Two-Way Undivided RoadsAM Publications
The time headway between vehicles is an important flow characteristic that affects the safety, level of service, driver behavior, and capacity of a transportation system. The present study attempted to identify suitable probability distribution models for vehicle headways on 2-lane 2-way undivided (2/2 UD) road sections. Data was collected from three locations in the city of Semarang: Abdulrahman Saleh St. (Loc. 1), Taman Siswa St. (Loc. 2) and Lampersari St. (Loc.3). The vehicle headways were grouped into one-second interval. Three mathematical distributions were proposed: random (negative-exponential), normal, and composite, with vehicle headway as variable. The Kolmogorov-Smirnov test was used for testing the goodness of fit. Traffic flows at the selected locations were considered low, with traffic volume ranged between 400 to 670 vehicles per hour per lane. The traffic volume on Loc.1 was 484 vehicles per hour, that on Loc. 2 was 405 vehicles per hour, and that on Loc. 3 was 666 vehicles per hour. Random distribution showed good fit at all locations under study with 95% confidence level. Normal distribution showed good fit at Loc. 1 and Loc. 2, whereas composite distribution fit only at Loc. 1. It was suggested that random distribution is to be used as an input in generating traffic in traffic analysis at highway sections where traffic volume are under 500 vehicles per hour.
Cooperative Traffic Control based on the Artificial Bee Colony IJERA Editor
This paper studies the traffic control problem in an isolated intersection without traffic lights and phase, because the right-of-way is distributed to each vehicle individually based on connection of the Vehicle-to-Infrastructure (V2I), and the compatible streams are dynamically combined according to the arrival vehicles in each traffic flows. The control objective in the proposed algorithm is to minimize the time delay, which is defined as the difference between the travel time in real state and that in free flow state. In order to realize this target, a cooperative control structure with a two-way communications is proposed. First of all, once the vehicle enters the communication zone, it sends its information to the intersection. Then the passing sequence is optimized in the intersection with the heuristic algorithm of the Artificial Bee Colony, based on the arrival interval of the vehicles. At last, each vehicle plans its speed profile to meet the received passing sequence by V2I. The simulation results show that each vehicle can finish the entire travel trip with a near free flow speed in the proposed method.
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.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
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• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
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• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
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• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
1. REVIEW OF OPTIMAL SPEED
MODEL
MASTERS CLASS ASSIGNMENT
BY
ADAMU MUHAMMAD GYAMBAR
BAYERO UNIVERSITY KANO, NIGERIA.
DEPARTMENT: CIVIL ENGINEERING
COURSE: ADVANCE TRAFFIC
ENGINEERING
SUMMITED TO
PROF. H M ALHASSAN
29 MAY, 2017.
2. INTRODUCTION
Just like normal blood circulation necessitate a healthy body, a well or smooth traffic
flow is necessary for healthy business, works, trips community development in a city .
Traffic congestions haunt, displeased cities and communities from various perspectives.
It inflicts uncertainties, drains resource, reduction in productivity, stress commuters
and harm environment due to it continues deterioration of urban traffic condition.
Speed is one of the most relevant factors that characterize road operation, directly and
decisively influencing its evaluation by all its users, having several effects, either positive
or negative.
3. HISTORY
In describing traffic dynamic, most useful tool is car following model (Gazis–Herman–
Rothery (GHR) model 1958) developed by Chandler et, of microscopic simulation model
base on two objective which comply with the first but failed to describe the second objective
Reducing the speed difference,
maintain an appropriate spacing between the following vehicle and the leading vehicle.
(Newell 1961) proposed a model capture the characteristic of CF behaviors in maintaining an
optimal spacing corresponding but is not suitable in traffic simulation. Linear models (Pipes
1967) were the mainstream models in the beginning of the traffic simulation history
The Gipps CF model (1981), the most successful collision avoidance model,
Fritzsche model 1994 and the Wiedemann model and Reiter 1992) have a two dimension
zone in the “spacing-relative speed” diagram
(Bando et al. 1995 & 1998) developed a new model called Optimal Speed Model (OVM)
Thirty years later
4. THEORETICAL MODEL OF OPTIMUM SPEED MODEL
The theoretical models that support the optimum speed model are as follows
Microscopic model
Mesoscopic model
Macroscopic model
Microscopic traffic flow models: describe the 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 one of the main processes in all microscopic models as well
as in modern traffic flow theory. each vehicle is considered separately and its behavior is
modeled as it reacts and anticipates to vehicles in front by its own dynamic equation having the
following form:
T is the reaction-time, dn is the distance headway with respect to the vehicle in front,
and Vn is the speed of the considered vehicle.
•Different functions of f result in various types of car-following models. These are:
(1)
5. Safe-distance models, stimulus-response models, psycho-spacing models and optimal
speed models. We also have microscopic traffic models based on cellular automata (CA).
Mesoscopics:
There are three types of mesoscopic models: headway distribution models, cluster models
and gas-kinetic models . In gas-kinetic models, vehicles and drivers’ behavior are described
in more aggregate terms than in microscopic models, by means of probability distribution
functions.
Macroscopic (continuum) traffic models: This deal with traffic flow in terms of aggregate
variables as a function of location and time. They describe the dynamics of the traffic
density k (x, t), mean speed v(x, t) and or flow rate q(x, t).
Macroscopic models often require less information input than microscopic models. This
simplifies the calibration and validation process, which make this type of model very
suitable for control applications.
(2)
6. PROBLEMS STATEMENT
Optimal Speed model : Ever since, the development of this model in traffic stream by
Bando et al (1995 and 1998) . The short comings of the model such as:
Unrealistic
instability,
changes in traffic congestion
formation of stop-and-go waves
Due to this factors necessities the frequent review of the model, so as to improved on the
models.
7. Definition of Optimal (optimum) speed limit: can be define as process or situation where
by a moving vehicle attain steady and maintain maximum legally permitted design
pavement speed limit on a free way or maintain a maximum desire 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.
8. According to Green shield :
When the density is zero, the flow is zero because there are no vehicles on the roadway.
As the density increases, the flow also increases to some maximum flow conditions.
When the density reaches a maximum, generally called jam density, the flow must be zero
because the vehicles tend to line up end to end
REVIEW OF OPTIMAL SPEED MODEL
9. According H. Ez-Zahraouy, et al June 2004. considering a one-dimensional road of length
L with open boundary conditions the particles are injected with a rate probability α and β at
one end of the road opposite to each other. car following models with the optimal speed
function with an explicit delay time τ . Base on Newell and Whitham description analysis
on the traffic model, the following equation of motion of car j: V
Where xj(t) is the position of the vehicle j at time t, ∆xj(t)=xj+1(t)-xj(t) is the headway of
vehicle j at time t, and τ is the delay time ( how is allows for the time lag that it takes the car
speed to reach the optimal speed V(∆xj(t)) when the traffic flow is varying. V(∆xj(t)) is the
optimal speed of vehicle j and is given by
Where hc is the safety distance and Vmax is the maximal speed of vehicle j when other
vehicles do not exist.
Ẍj(t)=a{V(Xj+1(t)−Xj(t))−Ẋj(t)} (3)
10. In the original car following models, the optimal speed is the same for all the vehicles.
Thus, the optimal speed function of each vehicle is different from each other. Generally, it
is necessary that the optimal speed function has an upper bound (maximal speed). Also,
it is important that the optimal speed function has the turning point.
The OVM can explain behaviors of traffic flow, for example, the transition from a free flow
to a congested flow, a density-flow relationship, a kind of effective delay of car motion.
Consider a pair of cars, a leader and a follower. Assume the leader changes the velocity
according to vl = v0(t) and the follower duplicates the leader’s velocity but with some
delay time τ , that is, vf = v0(t−T). Under such a situation we can clearly define the delay
time of car motion by T. It is known that the observed delay time τ of car motion is of the
order of 1 sec, but the known physical or mechanical response time τ is of the order of
0.1 sec. it has been confirmed that the equation (2) really produces T of order 1 sec
11. optimal speed function most has an upper bound (maximal speed).
optimal speed function most has the turning point.
The idea of the above car following model is that a driver adjusts the vehicle speed
According to the observed headway ∆xj(t). The delay time τ allows for the time lag that it
takes the speed of each vehicle to reach the optimal speed V (∆xj(t)) of each
vehicle when the traffic flow is varying. By taylor expanding, Eq.(1), one obtains the
differential equation model
(5)
Where a=1/τ is the sensitivity of a driver Furthermore, by transforming the time derivative
to the difference in Eq (1), one can obtain the difference equation model
Xj(t+2τ) = xj(t+τ)+τV(xj(t)) (6)
(4)
12. considering such a case that the dimensionless delay time of vehicle j is uncorrected with other
vehicles and is given by τj=<τ>+∆τ[2rnd(j)-1.0 (7)
Where rnd(j) is the random number between zero and unity, <τ> is the average value of the
dimensionless delay time, and ∆τ is the strength of the variation of the dimensionless delay
time.
Properties of Optimal Speed Model are :
Linear Analysis
Numerical Simulation,
Unrealistic
instability,
changes in traffic congestion
formation of stop-and-go waves
upper boundary (maximum speed)
Turning point
13. According Hao Wang et al August, 2014, by introducing the DBOVF into the original OVM, the
new model allows drivers to reach their steady states within a wide region instead of a specific
optimal solution in a steady state.
(8)
14. Considering the facts that drivers would like to accept a range of spacing instead of an
optimal one, we assume that the steady state occupies a two-dimension area in the
speed-spacing diagram. As shown in Figure 1, there are two boundaries in the steady
state region. Each boundary can be formulated by a certain type of optimal velocity
function. The two boundaries of the steady state divide the speed-spacing diagram into
three regions
15. ASSUMPTIOMS MADE
In region I, the spacing is too small for the driver to accept, and the driver will reduce the
speed towards the optimal speed indicated by the left boundary optimal velocity function.
In region Ⅱ, the driver is satisfied with current conditions, and will not change the speed
until the vehicle moves out of this steady region.
In region Ⅲ, the spacing is too large, and the driver will accelerate towards the optimal
speed indicated by the right boundary optimal velocity function.
Simple Example of DBOVF and types of OVF over the history in traffic flow studies
are:
The three types which were most widely used by researchers in Left boundary and Right
boundary namely,
(Newell 1961), the convex type represented by the exponential function.
(Daganzo 1994), the piecewise linear function represented by triangle fundamental
diagram model.
(Bando et al. 1995), the S shape function In order to make comparison with the original
OVM.
16. The second requirement is from the consideration that the deceleration is usually stronger
than the acceleration at the margin of steady state. Suppose a vehicle moves a small
distance.
(Michaels 1961; Evans and Rothery 1977), the first requirement comes from the studies on
psychophysical car following models. These studies indicated that drivers perceive spacing
changes through changes on visual angle subtended by the vehicle ahead.
The S shape function In order to make comparison with the original OVM, we use the
Bando’s S-shape function as the boundary function to build the DBOVF. Before modeling
the DBOVF, two requirements are considered as
(i ) The range of spacing in the steady state increases with the speed increasing;
(ii ) For a given speed Ve , the smallest and largest spacing in steady state are
17. Features of DBOVM:
The feature of DBOVM is the local stability
Considered 3 vehicles in the local stability studies. State that All vehicles are in steady
state at the beginning of the simulation:
(ⅰ) initial state on the right boundary of steady region,
(ⅱ) initial state on the left boundary of steady region,
(ⅲ) initial state satisfying the optimal function in original OVM.
18. Stability Features of the Basic DBOVM
The DBOVM does not have a uniform model expression as a multiphase car following
model, which makes it difficult for the analytical stability analysis.
Treiber and Kesting (2013) gave a detailed theoretical analysis on traffic stability. It is
pointed out that all time-continuous car-following models with a negative derivative of
acceleration with respect to speed are unconditionally locally stable, if there are no
explicit reaction times in models. if there are no explicit reaction times in models.
Recall the dual-boundary-optimal-velocity-function displayed in Figure 1, the basic
DBOVM satisfies the criterion suggested by Treiber and Kesting when the local traffic
state is located outside of the dual boundary steady region. However, as the driver
does not perform any acceleration within the steady region, it delays the driver’s
response to the leading vehicle when the traffic state moves through the dual
boundary region in the speed spacing phase diagram. Therefore, the basic DBOVM is
analogous to the OVM with explicit delay (Bando et al. 1998) in some extent. The
simulation studies on the local stability of the basic DBOVM are as follows.
19. Three vehicles are considered in the local stability studies. All vehicles are in steady state at
the beginning of the simulation. For the studies on the basic DBOVM, the initial state of
vehicles should satisfy either the left or the right boundary optimal velocity function.
Otherwise, the following vehicles may not respond to the perturbation from the leading
vehicle according to the law of the basic DBOVM.
Therefore, three simulations are conducted for three different scenarios respectively, which
are;
(ⅰ) initial state on the right boundary of steady region,
(ⅱ) initial state on the left boundary of steady region,
(ⅲ) initial state satisfying the optimal function in original OVM
20. Advantage
It reduce fuel consumption or expenditure
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
It reduce fuel consumption or expenditure
(Bando et al. 1995), all three simulations begin with the driving speed of 10 m/s for all
vehicles. Such a speed ensures that the initial condition satisfies the string stability criterion
of the original OVM Then a small perturbation is added on the leading vehicle by giving its
position an instantaneous change (either increasing by 1 m or reducing by 1m). The
simulations are conducted with the time step of 0.1 s, and results of the simulations.
21. Disadvantage
It wastes time for commercial drivers that are used to travel with high speed.
It increase travel time
It increase pollution
Application
Capacity analysis.
safety research
Traffic simulation.
Applicable in intelligent transportation systems, such as advanced vehicle control and
safety systems and autonomous cruise control systems.
Optimal speed limit is applicable on moving vehicle such as car, truck, buses etc
The parameters of general DBOVM are required to be calibrated by real traffic flow
data, and applications of the proposed model.
22. It is used in various trains such as mono rail etc.
We use real fuel-economy data to build a mathematical model for determining the
optimal speed. We'll solve the model graphically, and then analytically using calculus
23. LIMITATION
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.
The optimal velocity models have difficulty to avoid collisions in urgent braking cases. This
is mainly due to the fact that the phenomenon of anticipation is not explicitly taken into
account
CONCLUSION
Generally, it is necessary that the optimal speed function has an upper bound (maximal
speed) Also, it is important that the optimal speed function has the turning point.
The main contribution is the proposal of a simple car following model called general
Dual-Boundary-Optimal-Velocity-Model, which can describe the driving behavior of
accepting a range of satisfied conditions instead of an optimal one under steady traffic.
24. The model is developed based on the Optimal Velocity Model with only two
additional parameters.
Therefore, it is very convenient for both analytical and numerical analysis.
A simple speed adjustment mechanism is introduced into the basic DBOVM, with
which traffic state can converge to steady state everywhere inside of the two
boundary steady region.
Under the effect of speed adjustment, traffic states are transferred along some
specific paths with an approximately constant slope equal to the sensitivity parameter
of the speed difference term in general DBOVM.
25. CHARACTERISTIC OF OPTIMUM SPEED LIMIT
Synthesize Present knowledge about speed and other factors that either influence
speed or are an outcome of speed such as Safety, Environmental Impacts, Road User
Costs
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
Behavior, Weather Factors, Temporal Factors, Vehicle Classification,
The dual boundary steady region in DBOVM has the hysteresis effect, which is similar to
the effect of explicit delay in OVM.
The wider the dual boundary steady region is, the stronger the hysteresis effect will be.
In spite of the instability resulted from the hysteresis of dual boundary region, the speed
adjustment effect in general DBOVM restrains the hysteresis and improves the stability of
traffic.
26. RECOMMENDATION ON THE PROPOSED NEW MODEL
The explicit delay time τ should be included in the dynamical equation in order to
construct realistic models of traffic flow.
In open boundary optimal speed model variation of the delay time Δτ should be
introduce in new model so that the transition from unstable to meta stable and from meta
stable to stable state occur and determine it effects
Dual Boundary Optimal Speed model (DBOVM) has Present a framework in general
and such dual boundary steady region can also be introduced into other well known car
following models.
Dual Boundary Optimal Speed model (DBOVM) has Present a framework in general and
such dual boundary steady region can also be introduced into other well known car
following models.
27. The basic DBOVM should be review or proposed a new DBOVM so that it can reach the
steady state inside of the dual boundary region during the dynamic process of traffic flow.
Therefore, the amendment of the speed adjustment mechanism is necessary in the
general DBOVM.
The DBOVM should be remodel so as to have uniform model expression as a multiphase
car following model, which will makes it simple for the analytical stability analysis
28. DEMOSTRATION OF NUMERICAL SIMULATION
http://www.popsci.com/sites/popsci.com/files/traffic_simulation.gifS
29. A. Benyoussef, N. Boccara, H. Chakib, and H. Ez-Zahraouy, Chinese journal of physics 39, 428
(2004).
Analysis of Optimal Speed Model with Explicit Delay 12 may 1998.
Evans, L. and R. Rothery. Perceptual Thresholds in Car Following: A Recent Comparison.
Transportation Science, Vol. 11, No. 1, 1977, pp. 60-72.
Elvik, R., 2013. A Re-Parameterisation of the Power-Model of the Relationship between the
Speed of Traffic and the Number of Accidents and Accident Victims. Accident Analysis and
Prevention 50, 854-860
Fritzsche, H. T. A Model for Traffic Simulation. Traffic Engineering and Control, Vol. 35, No. 5,
1994, pp. 317-321.
Gao, K., R. Jiang, B. H. Wang, and Q.S.Wu. Discontinuous Transition from Free Flow to
Synchronized Flow Induced by Short-range Intersection between Vehicles in a Three-phase
Traffic flow model.( 2014)
G.F. Newell, Oper. Res. 9, 209 (1961).
Hashim.M. Alhassan, Advance Traffic Engineering Lecture Note
REFERENCE
30. Michaels, R. M. Perceptual Factors in Car Following.In Proceedings of International
Symposium on the Theory of Road Traffic Flow, 1963, pp. 44-59
M. Bando, K. Hasibe, A. Nakayama, A. Shibata, and Y. Sagiyma, Phys. Rev. E 51, 1035 (1995).
Treiber, M. and A. Kesting. Traffic Flow Dynamics: Data, Models and Simulation. Springer,
Berlin, 2013.
Wiedemann, R. and U. Reiter. Microscopic Traffic Simulation: the Simulation System
MISSION, Background and Actual State, CEC Project ICARUS (V1052), Final Report, Vol, 2,
Appendix A. Brussels: CEC, 1992.
.