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As the first of the project, the Author decide to write a brief history of car parking system and its processes so as to enlighten and understand clearer what the project is all about. Some of the features of the current car parking systems will be documented here, together with the major and general types of car parking system. The author hopes to find and document some basic advantages, disadvantages, and symbols used in car parking area.
The chapter is also going to explore the product of the research conducted on existing car parking systems. The scope of this chapter is basically to identify some car parking system and compare them, to produce some limitations of the current system. The author will then propose some solutions to implement from the problems being identified. All of the above findings will be hopefully documented at the end of this chapter.
Car parking system is a system that is used to help managing cars in parking area in other to avoid congestion and arrange cars in an allocated position. The system also helps to track how many cars pass through the gate and the duration taken by each, and then it will calculate the amount of money a car should pay when exiting. Car parking system is being used in many congested area or location where there are many meeting point of people like where there are more than one shopping complex near to each other or where there is megamall or stadium. For example like Sunway pyramid, Lowyat and Timesqure, and Midvaley megamall all in Malaysia.
Types of car Parking System
Based on the authors’ research, there are mainly four categories of car park guidance systems using different technologies – wired sensor-based, wireless sensor-based and image-based, counter-based.
Wired sensor-based system is using detection sensors such as ultrasonic sensors which are installed at each parking lot. These sensors are wired to a central control unit that store and manage the parking occupancy information. This information is then forward to display panels at intentional locations in the car park. The display panels provide information, direction and guide the drivers to vacant parking lots.
With the advancement of wireless technologies, wireless based methods have been employed in parking guidance systems. Wireless sensors nodes are deployed and each parking lot is equipped with one node. The sensor board is equipped with the sensors of light, temperature, acoustic and a sounder. In using wireless technologies, disadvantage in employing sensor at each parking lot is still present and can be very costly as each sensing unit is usually attached with a processing unit and a transceiver.
Image based techniques or some people call it as video sensor techniques. There are arguments concerning the viability of using image-based techniques. The disadvantages are video sensor is energetically expensive and video sensor can generate large amount of data which can be difficult to transmit in a wireless network.
The last category of car park guidance systems use is Counter-based systems which use sensors to count the number of vehicles entering and exit a car park area. This can be gate-arm counters and induction loop detectors located at the entrances and exits. This system can give information on the total number of vacant lots in a closed car park area, but does not help much in guiding the driver to the exact location of the vacant lots.
General features of Car Parking System
Enable the driver to collect ticket upon entrance: car Parking system should be able to allow the driver to get his ticket after he press the button of the gate barrier.
The system should record the entire cars that pass through the entrance.
The system should allow the gate to open whenever a driver has press the button and take his ticket.
Allow the drivers to make payment: if it’s of commercial use, the system should enable the drivers to make payment of their charges before exiting.
Allow the driver to exit: if the driver has paid his charges and require exiting, the system should open the gate to allow him exiting.
Process of Car parking System
From the research conducted, the author can state that, there is not much direct interaction between the system and the user. Though some parking systems have different procedures, but for a parking system like in Sunway pyramid, the author got to understand that the process is generally as follows.
The customer presses the button on the machine; ticket will come out from it and the customer take his ticket and then the gate will open. The customer will now proceed to the available space. The available spaces are known by the green light bulb on top of each available lot. The red light on top of parking lot indicate either the space is being reserved or there is car parked at it.
For the process of exiting, if the customer is using “touch and go” (Malaysian prepaid card), there is a sensor provided which will read the card and if there is enough money the system will deduct the amount of the charges.
But if the customer is going to pay cash there are available paying machines which the customer will insert his ticket and the system will read the ticket, estimate the hours spent and calculate the amount to be paid by the customer. Customer should insert the money stated by the system into machine. The system will validate the ticket and assign 15minutes on it which is enough for a person to his vehicle to the nearest exit gate.
Advantages of Car Parking System
The automated parking system increases the number of cars that can be parked in a garage. It provides more parking spaces since the cars are well organised parked.
If you use automated parking system, you will need only a less area of land for building a garage.
This system enables safe parking of cars as compared to the ramp-style parking facilities.
This method of parking is so convenient for the drivers and they need not have to walk in search of parking spaces.
This system reduces the maintenance costs of the garages since it significantly lowers the ventilation and lighting requirements and no need of costly deck repairs as well.
As said earlier, the chances of vehicle getting damaged due to improper parking are considerably reduced in automated car parking system.
With automated car parking system, there are no or very minimal chances of the vehicle getting lost. But, this is not the case in traditional parking method.
Existing Car parking System
In many cities today, several car parking systems can be found in different parking areas or complex. The parking systems help both the users and the drivers to have a conducive and free environment for their parking activities using. Thus, the author has decided to choose the following parking system to compare for his review of the existing systems:
Sunway pyramid car parking system
Figure 1.1: slot machine, (Sunway, 2010).
Some facility attached to the system
Figure 1.2: parking space, (Sunway, 2010).
Left picture-reserved lot(red light) right picture-available space(green light)
Car Park Occupancy Information System (COINS)
Figure 1.1 http://www.iaeng.org/IJCS/issues_v35/issue_1/IJCS_35_1_02.pdf
Lowyat car parking system
The Author is going to use some criteria to compare and evaluate the existing systems. The criteria are:
Information on available space:
This is based on the information provided by each system on the available space inside each of the parking area.
This will assess how reliable is the system to its users. The services it provides both to the admin and customers.
Information on the number of cars:
The information each system provide on how many cars are inside each of the parking area.
Help and Support:
This principle will be used to evaluate the system ability to provide customer support through the different means available.
The criteria used to assign a particular lot to a particular parson such as administrator or for other purposes.
Using the above evaluation criteria, the Author is going to compare the systems using 3 as the highest value and 1 as the lowest.
Information on available space
Information on the number of cars
Help and Support
Table 1.0 Comparison on the existing car parking systems
Strengths of Existing Systems
The interface design of most of the systems is made simple and rare advertisements are displayed. This permits users to perform their activities effectively.
There is no restriction or limitation of time for a car to spend in each parking area.
All the system provide very affordable price to the customer. The charges are base on hours spend by a car in the parking area.
Limitations of the Existing Systems
None of the system is providing the information of each car (plate number). For security purpose. For example security agency want know the car that are inside the parking area for traceability.
The system do not assign car to a specific parking lot and this result in roaming of cars inside the area in searching of parking space.
Some of the system does synchronize the free parking zones after the vacation of vehicle.
The possible way to solve those problems is by using the computer-based system with some additional features or functionality. Some of the features are:-
Assigning the bay number to a car from the entrance gate
Synchronizing the free parking zones after the vacation of each car.
To eliminate the long travelling of vehicle by assigning the car to the nearest possible lot.
The use of sensor at each lot can be avoided since the car is being assigned to a specific lot. There by reducing the cost of developing and the cost of maintaining the area.
Also like stated in the study of COINS system light is very crucial to sensor because it helps in detecting the presence of vehicle. Insufficient light will cause the system to perform improperly. But in the case computer base system all this will not be a factor.
From the research and comparisons being conducted by the author on several types of the car parking systems, the author have come to understand clearer the criteria used to judge and rank parking systems online. Hence, the evaluation has educated the author a lot about car parking systems and how they operate. The problems being identified by the author in the existing systems has made clear what mistakes should be avoided in this project to make it unique, acceptable, and user friendly.
CHAPTER 2.0 SIMULATOR
The term simulation is defined as the process of creating an abstract representation of an existing or proposed system in order to identify and understand those factors which control the system and/or to predict or forecast the future behavior of the system. Almost every system which can be quantitatively explained using equations and/or rules can be simulated.
The essential purpose of simulation is to shed light on the fundamental mechanisms that control the behavior of a system. More practically, simulation can be used to determine what you can do to influence that future behavior. That is, simulation can be used to forecast the way in which the system will develop and respond to its surroundings, so that you can recognize any necessary changes that will help make the system perform the way that you want it to. (Goldsim 2010)
An example of a use of a computer simulator might be an engineering company working on designing a better wing for aircraft. Rather than spending resources developing prototypes of each new design, and testing them in wind tunnels or on real aircraft, a simulation can be run as a substitute. (wisegeek, 2003)
Computer simulation is the discipline of designing a model of an actual or theoretical physical system, executing the model on a digital computer, and analyzing the execution output. To understand actuality (reality) and all of its complexity, we must develop artificial objects and dynamically act out roles with them. Computer simulation is the electronic counterpart of this type of role playing and it serves to drive synthetic environments and virtual worlds. (wisegeek, 2003)
Simulation of a system can be done at many different levels of fidelity so that whereas one will think of physics-based models and output, another may think of more abstract models which yield higher-level, less detailed output as in a queuing network. Models are designed to provide solution at a given abstraction level. The more in depth the model, the more detailed the output. The kind of output you need will imply the type of model you will employ. (wisegeek, 2003)
To simulate something physical, you will first need to create a mathematical model which represents that physical object. Models can take many forms including constraint, declarative, functional, spatial or multimodal. A multimodal is a model containing multiple integrated models each of which represents a level of granularity for the physical system. The next task, once a model has been developed, is to invoke the model on a computer that is, you need to create a computer program which steps through time while updating the state and event variables in your model. There are lots of ways to step through time. You can, for instance, leap through time using event scheduling or you can make use of small time increments using time slicing. You can also simulate the program on a massively parallel computer. This is called distributed and parallel simulation. For many large-scale models, this is the only feasible way of getting answers in a reasonable amount of time.
When to Use Simulation
Simulation is a decision analysis and support tool. Simulation software allows you to assess, compare and optimize other designs, plans and policies. As such, it provides a tool for explaining and defending decisions to a variety of stakeholders.
Simulation should be used when the penalty of a proposed action, plan or design cannot be directly and immediately observed (i.e., the consequences are delayed in time and/or dispersed in space) and/or it is simply impractical or prohibitively expensive to test the alternatives directly. For example, when developing a strategic plan for a company, the impacts are likely to take months (or years) to show up.
Simulation is particularly important when there is significant uncertainty regarding the outcome or consequences of a particular alternative under consideration.
The reality is not available (the technology is not in place to realize the concept)
The reality is too dangerous (safety critical test)
To save money and time (development) (VIP, 2010)
Perhaps most importantly, simulation should be used when the system under consideration has complex interactions and requires the input from multiple disciplines. In this case, it is complicated for any one person to easily understand the system. A simulation model can act as the framework to assimilate the various components in order to better realize their interactions. As such, it becomes a management tool that keeps you focused without getting lost in unimportant details.
Types of Simulation
Parallel discrete event simulation is concerned with execution on multiprocessor computing platforms containing multiple central processing units (CPUs) that interact frequently, e.g., thousands of times per second (PARALLEL AND DISTRIBUTED SIMULATION SYSTEMS, 1997).
188.8.131.52. Example of parallel simulation is parallel simulation system for freeway traffic flows which is being developed with a network of PCs under the Windows.NET environment. Basic segment types of a freeway were recognized and existing macroscopic models were tailored for each segment type. The parallel algorithm first divides the whole section of a given freeway into multiple subsections depending on the number of PC’s available in a network and the computational complexity of each subsection. Flows of each traffic sub section are simulated in parallel and the data at the internal boundaries between two consecutive subsections are exchanged through a communication function at every time step.
Distributed simulation is concerned with the execution of simulations on loosely coupled systems where interactions take much more time, e.g., milliseconds or more, and occur less often. It includes execution on geographically distributed computers interconnected via a wide area network such as the Internet (PARALLEL AND DISTRIBUTED SIMULATION SYSTEMS, 1997).
In both cases the execution of a single simulation model, perhaps composed of several simulation programs, is distributed over multiple computers.
Benefits of Simulation
Parallel and distributed simulation systems can provide substantial benefit to these applications in several ways:
1. Execution times of analytic simulations can be reduced by subdividing a large simulation computation into many sub-computations that can execute concurrently. One can reduce the execution time by up to a factor equal to the number of processors that are used. This may be important simply because the simulation takes a long time to Execute, e.g., simulations of communication networks containing tens of thousands of nodes may require days or weeks for a single run.
2. Very fast executions are needed for on-line simulations because there is often very little time available to make important decisions. In many cases, simulation results must be produced in seconds in order for simulation results to be useful. Again, parallel simulation provides a means to reduce execution time.
3. Simulations used for virtual environments must execute in real time, i.e., the simulator must be able to simulate a second of activity in a second of wall clock time so that the virtual environment appears realistic in that it evolves as rapidly as the actual system. Distributing the execution of the simulation across multiple processors can help to achieve this property. Ideally, scalable execution can be obtained whereby the distributed simulation continues to run in real time as the system being simulated and the numbers of processors are increased in proportion.
(PARALLEL AND DISTRIBUTED SIMULATION SYSTEMS, 1997).
Time Parallel Simulation
Time-parallel simulation methods have been developed for attacking specific simulation problems with well-defined objectives, e.g., measuring the loss rate of a finite capacity queues of an ATM multiplexer (PARALLEL AND DISTRIBUTED SIMULATION SYSTEMS, 1997). Time-parallel algorithms divide the simulated time axis into intervals, and assign each interval to a different processor. This allows for massively parallel execution because simulations often span long periods of simulated time.
A central question that must be addressed by time parallel simulators is ensuring the states computed at the “boundaries” of the time intervals match. Specifically, it is clear that the state computed at the end of the interval [Ti-1, Ti] must match the state at the beginning of interval [Ti, Ti+1]. Thus, this approach relies on being able to perform the simulation corresponding to the ith interval without first completing the simulations of the preceding (i-1, i-2, … 1) intervals.
Because of the “state-matching” problem, time-parallel simulation is really more of a methodology for developing massively parallel algorithms for specific simulation problems than a general approach for executing arbitrary discrete event simulation models on parallel computers. Time parallel algorithms are currently not as robust as space parallel approaches because they rely on specific properties of the system being modeled, e.g., specification of the system’s behavior as recurrence equations and/or a relatively simple state descriptor. This approach is currently limited to a handful of applications, e.g., queuing networks, Petri nets, cache memories, and multiplexers in communication networks.
(PARALLEL AND DISTRIBUTED SIMULATION SYSTEMS, 1997).
The most basic reason for which people choose smart tools is to be able to automate simple things, for example like in the smart homes lighting, heating and air conditioning controls. So it is in the reservation of lots and assigning of parking lot in the car parking complex.
Another important aspect coming from the usage of a smart tools simulator is energy conservation.
Smart tools could be divided into two main categories:
â€¢ Programmable tools – are those programmed to perform an action triggered by an input detected,
â€¢ Intelligent tools – are those that possess some kind of intelligence that govern its operation. (Smart House Simulation Tool,2006)
2.1 Programmable tools
Programmable tools will be those, whose reactions are based only on simple inputs, and possess no built-in intelligence. Such a tool for a predefined input (from either sensor(s) or user controller(s)) has a predefined (programmed) set of actions to perform. Examples of such actions might be e.g. detection of car at an entrance of parking area, or selection of parking areas. All these are predefined settings by a user in system.
Virtually all of currently manufactured and sold ‘smart tool’ systems belong to this group. With mass production it was possible to lower the end-user price to a level acceptable by middle-class customers – cost can lie between 50 and 120 (and up) Euro per square meter (poradnik 2006), depending on a set of desired features and controlled operations.
The biggest problem with this type of smart tools is that they have to be reprogrammed when some of the features become unnecessary and/or added. That presents a problem for many people and requires calling a technician to get the job done. Hence increasing tension to develop some smart tools solution that – basing on artificial intelligence – will adapt its operation to changing user behaviour. A tool that will not have to be first programmed and then reprogrammed all the time. A tool that will think how to make a user satisfied, lower his workload and lower the tool operation cost at the same time.
That tension leads to development of the tool that belongs to the second category.
2.2 Intelligent Tools
They represent the state-of-the-art technology. Those type of installations are driven by artificial intelligence, and instead of having to be programmed they are able to learn (i.e. program themselves) basing on observation of inhabitants behaviour over a period of time.
It one of the first successful implementations was well known Adaptive House developed by M. Mozer at University of Colorado back in 1998.
Complete system could be decomposed down to building blocks, which could be grouped into following categories:
â€¢ Data mining
â€¢ Decision making
2.2.1. Data mining
It is an area known from e.g. statistics or pattern recognition. It could be defined as searching large volumes of data for patterns.
In case of intelligent parking system, it will be implemented as looking for a specific behavior pattern through the saved logs of past activities, and trying to match the specific situation to a previously observed one.
One problem is that constantly growing amount of data (from actuators operation) demands a method for storage enabling short data access time. Second problem is to fine tune a method to ‘mine’ the data out from the database, so it can be used by the next stage of the intelligent car parking system. Several techniques to perform these operations are presented with some details in (Causal Reasoning for Alert Generation in Smart Homes,2006).
Having (possibly close) matched the current scenario to one from the past, that module passes the data to the next, far more complicated module that is responsible for making decisions.
2.2.2. Decision Making
The role of the Decision Making section is, as name implies, to make a decision of what action should be taken by the system, basing on the input from sensors and data fed by data mining unit. There is plenty of logic that could be implemented here. Decisions have to be performed accurately, because some everyday life situations can be potentially dangerous.
Second aspect is developing logic for intelligent system is a major task, far beyond the capability of a single person, and is supposed to be carried out by a group of researchers, in most of the cases they are university scientists.
2.3 Smart Tool System/Simulator In Car Park
Smart tool systems concentrate on providing assistance to both admin and customer while they are dealing with their daily routine. Most simple solutions control only the detection of car and time at entrance, then issue ticket to the driver, basing on pre-programmed settings or simple input. With adding more types of actuators operating new kinds of devices we can increase number of features in our smart tool of car parking system, enabling it to control more aspects of system operations, like reservation of space, capturing car number and converting it to the editable format which can be as one of the details in recognizing the vehicle and the driver, and provision of security. The most important extension, still being in experimental stage and waiting for deployment in broad scale, is implementing intelligence to collect data from this complicated inputs, process them, and control system in an adaptive way.
Those are the features necessary to create a smart tool. In case of creating a smart tool simulator, many things are simpler. We do not have to create the entire technical infrastructure, because action takes place on the computer display. However, we have to give user a way to define a tool outline, to place and configure inputs, and a framework to simulate all events taking place in the car parking complex.
2.4 Requirements for the Simulator
The smart tool simulator is supposed to fulfill the following conditions:
1. Should be easy to use, to attract possibly broadest audience.
2. Should enable defining a tool outline, so that user can define a tool on his choice, instead of playing only with built-in templates.
3. Should enable user to bind a specific action to specific input (basic rule of operation of a programmable tool). Example: driver entering the area is detected by pressing the button, and then the operation automatically starts. (Smart House Simulation Tool,2006)
Advantages of Simulation
Simulators are able to provide users with practical feedback when designing real world systems. This allows the developers to determine the correctness and efficiency of a design before the system is actually constructed. Consequently, the user may discover the qualities of alternative designs without actually physically building the systems. By investigating the effects of specific design decisions during the design phase rather than the development phase, the overall cost of building the system diminishes significantly.
Simulators permit system designers to study a problem at several different levels of abstraction. By approaching a system at a higher level of abstraction, the designer is better able to understand the behaviors and interactions of all the high level components within the system and is therefore better equipped to counteract the complexity of the overall system. This complexity may simply overpower the designer if the problem had been tackled from a lower level.
Simulators can be used as an effective way for teaching or demonstrating concepts to users. This is particularly true of simulators that make intellectual use of computer graphics and animation. Such simulators dynamically show the behavior and relationship of all the simulated system’s components, thereby providing the user with a meaningful understanding of the system’s nature. (Donald, 1996)
Disadvantages of simulation
Expensive to build a simulation model.
Expensive accomplish simulation.
Sometimes it is difficult to understand the simulation results.
(Meng Xiannong 2002)
Importance of simulation
You may wonder whether simulation must be used to study dynamic systems. Simulation is often essential in the following cases:
The model is very complex with many variables and interacting components. E.g. flight simulator.
The underlying variables relationships are nonlinear
The model contains random varieties. E.g. Science-based simulations
The model output is to be visual as in a 3D computer animation.
The power of simulation is that, even for easily solvable linear systems a uniform model execution technique can be used to work out a large variety of systems without resorting to a “bag of tricks” where one must choose special purpose and sometimes mysterious solution methods to avoid simulation (The Art and Science of Digital World Construction, 1995).
Another important characteristic of the simulation technique is that one can build a simulation model to replicate the actual system. When someone uses the closed-form approach, the model is sometimes twisted to suit the closed-form nature of the solution method rather than to accurately represent the physical system. A harmonious concession is to tackle system modeling with a hybrid approach using both closed-form methods and simulation. For example, we might initiate to model a system with closed-form analysis and then progress later with a simulation. This evolutionary system is often very effective (The Art and Science of Digital World Construction, 1995).
In this chapter, advantages of smart tool technologies were outlined, together with a short classification of currently available solutions. Distinction between programmable tool and intelligent tool were outlined, basing primarily on the presence or absence of a self-learning logic unit, trying to fit the car park infrastructure operation to inhabitant behavior that may change over time. Features implemented in current projects were outlined and summarized, and given as a brief requirements list such a smart car park simulator should fulfill. Those requirements will be considered in the design issues that will follow later in the project.
Parallel and distributed simulation technologies address issues concerning the execution of simulation program
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