Deep neural network for lateral control of self-driving cars in urban environ...IAESIJAI
The exponential growth of the automotive industry clearly indicates that self-driving cars are the future of transportation. However, their biggest challenge lies in lateral control, particularly in urban bottlenecking environments, where disturbances and obstacles are abundant. In these situations, the ego vehicle has to follow its own trajectory while rapidly correcting deviation errors without colliding with other nearby vehicles. Various research efforts have focused on developing lateral control approaches, but these methods remain limited in terms of response speed and control accuracy. This paper presents a control strategy using a deep neural network (DNN) controller to effectively keep the car on the centerline of its trajectory and adapt to disturbances arising from deviations or trajectory curvature. The controller focuses on minimizing deviation errors. The Matlab/Simulink software is used for designing and training the DNN. Finally, simulation results confirm that the suggested controller has several advantages in terms of precision, with lateral deviation remaining below 0.65 meters, and rapidity, with a response time of 0.7 seconds, compared to traditional controllers in solving lateral control.
REVIEW OF MICROSCOPIC TRAFFIC FLOW USING ARTIFICIAL INTELLIGENCE.pptxNafisaBashir1
Microscopic traffic flow is the type of flow that deals with each vehicle as an individual vehicle. As we are surrounded by artificial intelligence and technology is advancing towards it, how do these two come together to solve our traffic issues.
The development of driverless vehicles is fast, and the technology has the potential to significantly affect the transport system, society and environment
Deep neural network for lateral control of self-driving cars in urban environ...IAESIJAI
The exponential growth of the automotive industry clearly indicates that self-driving cars are the future of transportation. However, their biggest challenge lies in lateral control, particularly in urban bottlenecking environments, where disturbances and obstacles are abundant. In these situations, the ego vehicle has to follow its own trajectory while rapidly correcting deviation errors without colliding with other nearby vehicles. Various research efforts have focused on developing lateral control approaches, but these methods remain limited in terms of response speed and control accuracy. This paper presents a control strategy using a deep neural network (DNN) controller to effectively keep the car on the centerline of its trajectory and adapt to disturbances arising from deviations or trajectory curvature. The controller focuses on minimizing deviation errors. The Matlab/Simulink software is used for designing and training the DNN. Finally, simulation results confirm that the suggested controller has several advantages in terms of precision, with lateral deviation remaining below 0.65 meters, and rapidity, with a response time of 0.7 seconds, compared to traditional controllers in solving lateral control.
REVIEW OF MICROSCOPIC TRAFFIC FLOW USING ARTIFICIAL INTELLIGENCE.pptxNafisaBashir1
Microscopic traffic flow is the type of flow that deals with each vehicle as an individual vehicle. As we are surrounded by artificial intelligence and technology is advancing towards it, how do these two come together to solve our traffic issues.
The development of driverless vehicles is fast, and the technology has the potential to significantly affect the transport system, society and environment
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.
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
Monitoring traffic in urban areas is an important task for intelligent transport applications to alleviate the traffic problems like traffic jams and long trip times. The traffic flow in urban areas is more complicated than the traffic flow in highway, due to the slow movement of vehicles and crowded traffic flows in urban areas. In this paper, a vehicle detection and classification system at intersections is proposed. The system consists of three main phases: vehicle detection, vehicle tracking and vehicle classification. In the vehicle detection, the background subtraction is utilized to detect the moving vehicles by employing mixture of Gaussians (MoGs) algorithm, and then the removal shadow algorithm is developed to improve the detection phase and eliminate the undesired detected region (shadows). After the vehicle detection phase, the vehicles are tracked until they reach the classification line. Then the vehicle dimensions are utilized to classify the vehicles into three classes (cars, bikes, and trucks). In this system, there are three counters; one counter for each class. When the vehicle is classified to a specific class, the class counter is incremented by one. The counting results can be used to estimate the traffic density at intersections, and adjust the timing of traffic light for the next light cycle. The system is applied to videos obtained by stationary cameras. The results obtained demonstrate the robustness and accuracy of the proposed system.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
The realistic mobility evaluation of vehicular ad hoc network for indian auto...ijasuc
In recent years, continuous progress in wireless communication has opened a new research field in
computer networks. Now a day’s wireless ad-hoc networking is an emerging research technology that
needs attention of the industry people and the academicians. A vehicular ad-hoc network uses vehicles as
mobile nodes to create mobility in a network.
It’s a challenge to generate realistic mobility for Indian networks as no TIGER or Shapefile map is
available for Indian Automotive Networks.
This paper simulates the realistic mobility of the Vehicular Ad-hoc Networks (VANETs). The key feature of
this work is the realistic mobility generation for the Indian Automotive Intelligent Transport System (ITS)
and also to analyze the throughput, packet delivery fraction (PDF) and packet loss for realistic scenario.
The experimental analysis helps in providing effective communication for safety to the driver and
passengers.
Online/Offline Lane Change Events Detection AlgorithmsFeras Tanan
Abstract—in this paper, We are presenting two algorithms
for lane change detection. The first one is used
for online detection (real-time detection) with accuracy of
85% and the other one is used for offline detection with
accuracy of 95%. The main purpose of the offline detection
algorithm is to find at which GPS locations the number
of happened left/right lane changes.
For the purpose of these algorithms we used the
”crowd-sensing” approach which means that the sensors of
different mobile devices that were fixed in different cars
are the sources of input data for the above mentioned
algorithms. Specifically speaking, we used Accelerometer
and Gyroscope sensors. We also presented an algorithm
for blinker pattern extraction using the microphone sensor.
Keywords: Pattern Extraction, Lane Change detection,
Accelerometer, Gyroscope and Crowd Sensing
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
Recently, rates of vehicle ownership have risen globally, exacerbating problems including air pollution,
lack of parking, and traffic congestion. While many solutions to these problems have been proposed,
Carpooling is one of the most effective solutions to this problems Recently, several carpooling
platforms have been built on cloud computing systems, with originators posting online list of
departure/arrival points and schedules from which participants can search for rides that match their
needs. In this paper, an improved carpool system is described in detail and called the improved
intelligent carpool system (IICS), which provides car poolers the use of the carpool services via a smart
handheld device anywhere and at any time. This IICS Consist the geographical, traffic, and societal
information and used to manage requests and find minimum route. We apply advanced genetic-based
carpool route and matching algorithm (AGCRMA) for this multiobjective optimization problem called
the carpool service problem (CSP).
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
More Related Content
Similar to AD VANCED TRAFFIC ENGINEERING ASSIGNMENT CIV 8331
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.
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
Monitoring traffic in urban areas is an important task for intelligent transport applications to alleviate the traffic problems like traffic jams and long trip times. The traffic flow in urban areas is more complicated than the traffic flow in highway, due to the slow movement of vehicles and crowded traffic flows in urban areas. In this paper, a vehicle detection and classification system at intersections is proposed. The system consists of three main phases: vehicle detection, vehicle tracking and vehicle classification. In the vehicle detection, the background subtraction is utilized to detect the moving vehicles by employing mixture of Gaussians (MoGs) algorithm, and then the removal shadow algorithm is developed to improve the detection phase and eliminate the undesired detected region (shadows). After the vehicle detection phase, the vehicles are tracked until they reach the classification line. Then the vehicle dimensions are utilized to classify the vehicles into three classes (cars, bikes, and trucks). In this system, there are three counters; one counter for each class. When the vehicle is classified to a specific class, the class counter is incremented by one. The counting results can be used to estimate the traffic density at intersections, and adjust the timing of traffic light for the next light cycle. The system is applied to videos obtained by stationary cameras. The results obtained demonstrate the robustness and accuracy of the proposed system.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
The realistic mobility evaluation of vehicular ad hoc network for indian auto...ijasuc
In recent years, continuous progress in wireless communication has opened a new research field in
computer networks. Now a day’s wireless ad-hoc networking is an emerging research technology that
needs attention of the industry people and the academicians. A vehicular ad-hoc network uses vehicles as
mobile nodes to create mobility in a network.
It’s a challenge to generate realistic mobility for Indian networks as no TIGER or Shapefile map is
available for Indian Automotive Networks.
This paper simulates the realistic mobility of the Vehicular Ad-hoc Networks (VANETs). The key feature of
this work is the realistic mobility generation for the Indian Automotive Intelligent Transport System (ITS)
and also to analyze the throughput, packet delivery fraction (PDF) and packet loss for realistic scenario.
The experimental analysis helps in providing effective communication for safety to the driver and
passengers.
Online/Offline Lane Change Events Detection AlgorithmsFeras Tanan
Abstract—in this paper, We are presenting two algorithms
for lane change detection. The first one is used
for online detection (real-time detection) with accuracy of
85% and the other one is used for offline detection with
accuracy of 95%. The main purpose of the offline detection
algorithm is to find at which GPS locations the number
of happened left/right lane changes.
For the purpose of these algorithms we used the
”crowd-sensing” approach which means that the sensors of
different mobile devices that were fixed in different cars
are the sources of input data for the above mentioned
algorithms. Specifically speaking, we used Accelerometer
and Gyroscope sensors. We also presented an algorithm
for blinker pattern extraction using the microphone sensor.
Keywords: Pattern Extraction, Lane Change detection,
Accelerometer, Gyroscope and Crowd Sensing
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
Recently, rates of vehicle ownership have risen globally, exacerbating problems including air pollution,
lack of parking, and traffic congestion. While many solutions to these problems have been proposed,
Carpooling is one of the most effective solutions to this problems Recently, several carpooling
platforms have been built on cloud computing systems, with originators posting online list of
departure/arrival points and schedules from which participants can search for rides that match their
needs. In this paper, an improved carpool system is described in detail and called the improved
intelligent carpool system (IICS), which provides car poolers the use of the carpool services via a smart
handheld device anywhere and at any time. This IICS Consist the geographical, traffic, and societal
information and used to manage requests and find minimum route. We apply advanced genetic-based
carpool route and matching algorithm (AGCRMA) for this multiobjective optimization problem called
the carpool service problem (CSP).
Similar to AD VANCED TRAFFIC ENGINEERING ASSIGNMENT CIV 8331 (20)
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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TOP 10 B TECH COLLEGES IN JAIPUR 2024.pptxnikitacareer3
Looking for the best engineering colleges in Jaipur for 2024?
Check out our list of the top 10 B.Tech colleges to help you make the right choice for your future career!
1) MNIT
2) MANIPAL UNIV
3) LNMIIT
4) NIMS UNIV
5) JECRC
6) VIVEKANANDA GLOBAL UNIV
7) BIT JAIPUR
8) APEX UNIV
9) AMITY UNIV.
10) JNU
TO KNOW MORE ABOUT COLLEGES, FEES AND PLACEMENT, WATCH THE FULL VIDEO GIVEN BELOW ON "TOP 10 B TECH COLLEGES IN JAIPUR"
https://www.youtube.com/watch?v=vSNje0MBh7g
VISIT CAREER MANTRA PORTAL TO KNOW MORE ABOUT COLLEGES/UNIVERSITITES in Jaipur:
https://careermantra.net/colleges/3378/Jaipur/b-tech
Get all the information you need to plan your next steps in your medical career with Career Mantra!
https://careermantra.net/
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
1. BAYERO UNIVERSITY KANO
FACULTY OF ENGINEERING
CIVIL ENGINEERING DEPARTMENT
ADVANCED TRAFFIC ENGINEERING
BY
ABDULRASHID HASSAN MUSA
Reg No: SPS/19/MCE/00027
ASSIGNMENT ON:
REVIEW OF MICROSCOPIC TRAFFIC MODEL USING ARTIFICIAL INTELLIGENCE
SUBMITTED TO
PROF. H.M.ALHASSAN
DECEMBER, 2022
2. Roadway safety continues to be a major public health concern. Recent statistics show that more than 30,000
fatalities occur due to motor vehicle accidents, and in the year 2012, motor vehicle crashes resulted in more
than 2 million injuries. As a result of these ongoing trends, simulators continue to become more abundant in
applications ranging from Intelligent Transportation Systems (ITS) research, autonomous driving, human
factors studies, rehabilitation, and driver training and workload applications. However, many current
commercial simulators lack realism with regards to accompanying traffic, which often does not satisfactorily
respond to the real-time actions of the human subject who is operating the simulation. Artificial traffic
simulation models found within commercial driving simulators are often “macroscopic” in nature – they
aggregate the description of overall traffic flow, which is based on “idealistic” driver behavior. This lack of
network realism (particularly in the vicinity of the human subject operating the simulator) limits the application
scope.
INTRODUCTION
3. In a simple term Artificial intelligence is the ability of a digital computer or computer-controlled robot to
perform tasks commonly associated with intelligent beings (Goggle search engine). While microscopic
traffic flow models are a class of scientific models of vehicular traffic dynamics that describe and simulate
single vehicle-driver units, like the position and velocity of a single vehicle. AI is in the spotlight as one of
the emerging fields transforming the transport sector. It is not a new term. Academics ups and downs
future progress talked about artificial intelligence as early as the 1950s. Since then, AI has undergone a
number of, where optimistic expectations were followed by bitter disillusion. In recent years, AI has made
a lot of progress, as machine learning techniques have been combined with technologies used for
searching and analyzing the large quantities of data (otherwise known as big data and data mining)
produced by the development of the digital world. Other reasons for its successful growth include the
development of communications networks and the internet of things, as well as progress in transport
devices. The AI in transport is expected to be even more spectacular, although there is no agreement on
the timing and exact nature of these developments
LITERATURE REVIEW
4. Applications of Artificial intelligence
Self-driving car
Machine learning
Natural language processing
Pattern recognition
Algorithm
Data security
Robotic processing automation
Etcetera
5. AIMS AND OBJECTIVES OF THE RESEARCH
To get a deeper understanding of microscopic traffic models using
artificial intelligence
6. DEFICIENCIES OF THE PREVIOUS RESEARCH IN THIS AREA
Related research has noted that existing microscopic traffic simulation models (based on available car-
following, gap-acceptance, and lane-changing models) often lack the level-of-detail required for safety
evaluations, which demand models that reflect errors in drivers’ perception, decision-making, and actions
(Cunto and Saccomanno, 2006). Other researchers (e.g., Punzo and Ciuffo, 2011) have emphasized the four
main requirements for appropriately integrated (TS-DS) simulation models. These are:
Accurate road matching between traffic and driving simulators;
Synchronization of traffic and driving modules with real time;
Consistency of the updating calculation frequency; and
Management of autonomous vehicle visualization.
7. In particular response to these four stated research needs, and to the various shortcomings of the related work
that came before ours, we have constructed our own Artificially Intelligent Transportation Model (AITM) intended
for clinical, training, and research simulation applications. In this paper, we describe the design of the major
components of the AITM, and some of its preliminary shortcomings that necessitated critical modifications. Prior
to that discussion, we first present ideas for the extensibility of our work to related domains in M&S research.
BROADER IMPACTS
SIMULATION HARDWARE
ENVIRONMENT DESCRIPTION
12. AITM DESIGN (PRELIMINARY)
METHODOLOGY
In this section, the primary features of the AITM are described, including the motion model (both for linear
motion and for turning motion), collision detection between moving objects (both between AI vehicles, and
the human driven participant), models describing vehicle behavior both at signalized intersections and at
stop signs, the AI vehicle lane-changing model. This section concludes with an overview of major
shortcomings of the preliminary model that necessitated further development.
13. Determining if any two 3D objects intersect – a technique commonly known as collision detection - is not
an easy task. The key to optimize these calculations is to efficiently discard non-colliding objects before
applying a full collision test (to all other candidate objects in the scene). The typical path for discarding
objects is to first divide a virtual scene into segments, while keeping track of which segment the object in
question is located, and then using collision tests with all the non-discarded objects in that segment. One
common procedure is known as the Oriented Bounding Box (Eberly, 2008).
COLLISION DETENTION
14. The Oriented Bounding Box
This method rotates the bounding box with the geometry so that the bounding box represents the
geometry of the object, even when rotated. This technique was chosen for the current effort, as the AI
vehicles traverse within specific lanes of traffic which are at different orientations, and collision will be
detected with other vehicles within the same lane (or adjacent, parallel lanes of travel). Also, a bounding
box serves as a sufficiently accurate representation of the shape of a motor vehicle.
15. As shown in Figure 4- above, the bounding box is attached to the AI vehicle, and new
coordinates are calculated (using matrix transformations) each time the AI vehicle
moves or rotates. In addition, the bounding box was extended in the direction of the
heading of each AI vehicle to detect collisions with other moving vehicles. The length
of the bounding box was assigned to be dependent on both travel speed and the
posted speed limit
Figure 4 – Oriented Bounding Box (3D)
16. TRAFFIC SIGNAL MODEL
Now that the AI vehicles are able to detect (and avoid) collision with one another, the next step was to add logic for
AI vehicles when in the vicinity of signalized intersections. This algorithm handles all decisions to be made
depending on the current “status” (i.e., red (R), yellow (Y), green (G)) of each intersection. Obviously, the AI
vehicles need to know the state of each signalized intersection as they traverse the virtual environment. A particular
3-bay (G-Y-R) traffic signal at a 4-way intersection has two sides, and therefore, a total of five possible basic states
(i.e., R-R, G-R, G-Y, Y-G, R-G), discounting turning arrows, flashing lights, and other more advanced signal states.
18. STOP SIGN MODEL
The scope of the traffic signal algorithm was expanded to include all traffic signals within the current virtual
environment and its logic was extended for application at intersections governed by stop signs. The algorithm
was designed to account for “all-way” stop signs and “single way” stop signs. For the former, the algorithm
keeps track of the vehicles waiting at the stop sign, and reserves slots for each vehicle as soon as it reaches
the stop sign. According to the slot reserved, each vehicle is given a “go” signal to cross the intersection. As
soon as an AI vehicle starts moving through the intersection, a programmer indicator internally denotes that the
intersection is occupied, and the algorithm waits for that vehicle to clear the intersection.
19. LANE CHANGING MODEL
Lateral movement (e.g., lane changing) by AI vehicles is necessary to represent real environment traffic scenarios.
For example, the AI vehicles in the left-most lane will take a left turn at an approaching intersection, vehicles in
middle lanes will continue straight, and the vehicles in the right-most lane will turn right (or go straight). These
decisions were made using stochastic effects, as each AI vehicle approaches each given intersection. For an AI
vehicle to change lanes, the heading angle no longer conforms to the (global) heading angle with the street upon
which the vehicle is traveling. To assure that the lane change appears fluid, the lane changing function increments
this heading angle in small amounts (heuristically chosen to be approximately 2.5 degrees) at each frame
rendering, as demonstrated in the figure below
20. Figure 7 – Lane Changing Transition Zone Figure 8 – Lane Changing Collision Detection
21. DEFICIENCIES OF THE CURRENT MODEL AND IMPROVEMENT
Once the preliminary model was designed, we were able to perform in-house testing and validation to observe
the operability of the AI Traffic Model. In so doing, a number of deficiencies were noted that were difficult to
forecast during the initial development phase. Three such deficiencies are described and illustrated here with
some detail, along with brief descriptions of how these model deficiencies were ultimately improved, or
circumvented altogether. Perhaps by offering these challenges, we will provide insight for future application
developers in transportation based M&S who might face similar difficulties.
25. CONCLUSIONS
Roadway safety and sustainability continue to be major public health concerns, and subsequently, simulators (and
other M&S technologies) continue to become more abundant in a wide variety of Intelligent Transportation Systems
(ITS) research applications (e.g., autonomous driving, human factors, and rehabilitation). To confront these
problems, standalone simulators are often implemented as an analysis and decision-making tool. Driving
Simulators (e.g., to monitor driver behavior, performance, and attention), and Traffic Simulators (e.g., to plan,
design and operate transportation systems) have been employed with some success. However, while traffic
simulation models allow for capturing dynamics of full-scale traffic networks, they often lack behavioral realism.
Largely for these reasons, an Artificially Intelligent Traffic Model (AITM) was constructed to operate in conjunction
with a custom-designed driving simulation environment. The framework presented in this paper has been designed
as an alternative for commercial “microscopic” traffic simulators, whose operability is often more concerned with
gross end mass vehicle behavior, with individual vehicle movements that are not fluid, and therefore not suitable for
integration with live human subjects.
26. While vehicle and transportation network technologies continue to evolve, there is an increasing urgency
for improved fidelity for driving/traffic simulation research. As such, the research described here can be
expanded and improved in numerous ways, and to conclude the paper, a few detailed suggestions are
offered below:
RECOMMENDATION
27. Implement customized human behavior models to enhance the traffic mobility: The proposed concept is
to override the (artificially intelligent) driver behavior model with experimentally attained, subject-specific
human behavior performance models.
28. Provide a high-fidelity, multiple-participant capability to facilitate research that involves real-time interaction
between human participants. Two or more driving simulators should be able to connect in real-time, which
would enable human drivers to interact with each other. Despite the success of driving simulators such as
DiVE (Prendinger et al., 2014) that have already provided certain level of multiple driver capacity, there is
still room for improvement in terms of functionality and fidelity
29. Integrated Traffic-Driving-Network Simulation The microscopic traffic model presented in this work has
been the first step towards the development of a more complete integrated simulation environment for
transportation research. While there have been numerous studies that have attempted to develop
integrated two-way simulators (e.g., traffic-driving, traffic-network), none has attempted to integrate all
three types of simulators. To this end, a 3-in-1 Integrated Traffic-Driving-Network Simulator (ITDNS) is
currently under development and ongoing enhancement (Zhao et al., 2013).