0LAUK0 2015 01 Week4: Difference between revisions
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== Monday == | == Monday == | ||
To find measurable quantities Li will look into literature to find good waiting time quantities. The requirements should be better defined. Kasper, Lester and Eric S will work on the introduction and objectives part of the report. While they will do this they can easily also elaborate more on the requirements and explain why our system is an improvement on the current system. Frank and Li will start on the basic set up of the simulation so that we can start on it as soon as possible. The survey should also be done this week and Eric W and Joey will organize it and organize the data. Everyone will conduct some surveys to distribute the workload. There is still some work to do on the literature studies so we will still work on this. | To find measurable quantities Li will look into literature to find good waiting time quantities. The requirements should be better defined. Kasper, Lester and Eric S will work on the introduction and objectives part of the report. While they will do this they can easily also elaborate more on the requirements and explain why our system is an improvement on the current system. Frank and Li will start on the basic set up of the simulation so that we can start on it as soon as possible. The survey should also be done this week and Eric W and Joey will organize it and organize the data. Everyone will conduct some surveys to distribute the workload. There is still some work to do on the literature studies so we will still work on this. | ||
= Progress = | = Progress = | ||
== Kasper Bakker == | == Kasper Bakker == | ||
rewrote the objectives | |||
== Frank van Heeswijk == | == Frank van Heeswijk == | ||
For the simulation part I have investigated what options there are and what their advantages and disadvantages are. | |||
The goal of the simulation is simulate the bus network in a city and we want to obtain data about the following measurements: | |||
- Amount of passengers waiting at a bus stop | |||
- Amount of passengers in the bus | |||
- Amount of buses in the system | |||
- Waiting time of a passenger at the bus stop before the bus arrives | |||
- Travel time of the bus | |||
We can then take the data and perform analysis on it to find the average, minimum, maximum, etc. values. Please note that the list of measurements is not yet finalized. | |||
We have identified three options to simulate our model: | |||
- 2D/3D graphical simulation | |||
- Business Process Modeling | |||
- Custom program that is specifically aimed at our simulation | |||
After experimenting a bit we quickly found out that a 2D/3D graphical simulation is going to cost way too much time and would still involve making our own custom program to run the busses, therefore we think that it is not a good decision to continue on that path. Afterwards I have attempted to model it into a Business Process Modeling program (CPN Tools), but the notation is difficult and I feel that it might quickly become very complicated, nevertheless it can be countered by abstracting parts of the model into components, but it will still be an issue to try to connect the model with real data and modeling certain things is simply hard. | |||
The following is an example of a model that models a bus, one stop and passengers arriving at a random interval. | |||
[http://i.imgur.com/1lTtaVl.png] | |||
Lastly I think writing our own simulation program is a good option because it gives us full control over what is important in our simulation, the only downside is that it does not come with some form of graphical output by default, though we could decide to make some simple graphical output. | |||
== Yuanlong Li == | == Yuanlong Li == | ||
-Added requirements for Introduction part | |||
-Made some progress on Road Network generation, but we might not need this thing anymore. The simulation will be shifted to process simulation. | |||
[[File:0LAUK0_2015_01_Week4_Road_Network.jpg]] | |||
== Eric Steenhof == | == Eric Steenhof == | ||
Public transportation has been around for a couple of decades now. It started with the stagecoach in the nineteenth century. Later on came the steam trains which were capable of carry large capacity of people at the same time. The trains were too big to travel in city themselfs, so the tram was invented. However not city are capable of creating a tramrail network. So with the increasing demands of mobility in the sixties, busses started to be used for public transportation in cities around the Netherlands and the rest of europe. | |||
Bus stops were created around cities and a static scheduling system was implemented. This static scheduling system uses a fixed time table around the city. The busses follow fixed routes each time and do not take into account if there are any people waiting at a bus stop or not. Meaning that the busses do not take a shorter route when nobody is willing to stop of is waiting a certain bus stop. This means it is time for a dynamic system, this will be the main focus in this report. The new scheduling system for busses aims to create a more efficient passenger flow. It will be able to send extra busses to bus stops that are or are getting too crowded and also the system will choose a shorter route to it’s destination when no passengers are waiting at the coming bus stops. Users can check in at the bus stop or with their mobile phone apps. The scheduling system will then optimize the routes by taking this information into account. A small part of the report will discusses the possibility of using autonomous busses in the new dynamic scheduling system, analyzing the impact of user, society and enterprise. | |||
Different approaches can be used to optimize this schedule. Those will be analyzed and take feedback data from a survey. This data will be inputted in a simulation in order to analyze the consequence of the different needs of the users. Furthermore in this report the infrastructure will be redesigned. The most important infrastructure alteration will be the placement of the bus depot. The simulation will also be used to validate the new dynamic scheduling system. | |||
The validation will have with different requirement like waiting time and crowdiness but also with happiness. This is a design report for dynamic schedualing bus system, incoreperating the needs of the User, Society and Entreprise. | |||
== Joey Verest == | == Joey Verest == | ||
Me and Eric have made the surveys and also have results. 102 people in total filled in the survey. The result of the online survey part can found on the following link: https://docs.google.com/forms/d/1npbu9OSgKHSL2eo8WUvONu5V62wygVl9kkTmxdj_m9s/viewanalytics | |||
== Eric Wolters == | == Eric Wolters == | ||
Together with Joey i made and conducted the survey | |||
== Lester Jones == | == Lester Jones == | ||
- Write the approach | |||
- Some more study regarding the USE-aspects |
Latest revision as of 15:33, 18 October 2015
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Week 4: 21-09-15
Meetings
Monday
To find measurable quantities Li will look into literature to find good waiting time quantities. The requirements should be better defined. Kasper, Lester and Eric S will work on the introduction and objectives part of the report. While they will do this they can easily also elaborate more on the requirements and explain why our system is an improvement on the current system. Frank and Li will start on the basic set up of the simulation so that we can start on it as soon as possible. The survey should also be done this week and Eric W and Joey will organize it and organize the data. Everyone will conduct some surveys to distribute the workload. There is still some work to do on the literature studies so we will still work on this.
Progress
Kasper Bakker
rewrote the objectives
Frank van Heeswijk
For the simulation part I have investigated what options there are and what their advantages and disadvantages are.
The goal of the simulation is simulate the bus network in a city and we want to obtain data about the following measurements:
- Amount of passengers waiting at a bus stop - Amount of passengers in the bus - Amount of buses in the system - Waiting time of a passenger at the bus stop before the bus arrives - Travel time of the bus
We can then take the data and perform analysis on it to find the average, minimum, maximum, etc. values. Please note that the list of measurements is not yet finalized.
We have identified three options to simulate our model:
- 2D/3D graphical simulation - Business Process Modeling - Custom program that is specifically aimed at our simulation
After experimenting a bit we quickly found out that a 2D/3D graphical simulation is going to cost way too much time and would still involve making our own custom program to run the busses, therefore we think that it is not a good decision to continue on that path. Afterwards I have attempted to model it into a Business Process Modeling program (CPN Tools), but the notation is difficult and I feel that it might quickly become very complicated, nevertheless it can be countered by abstracting parts of the model into components, but it will still be an issue to try to connect the model with real data and modeling certain things is simply hard.
The following is an example of a model that models a bus, one stop and passengers arriving at a random interval. [1]
Lastly I think writing our own simulation program is a good option because it gives us full control over what is important in our simulation, the only downside is that it does not come with some form of graphical output by default, though we could decide to make some simple graphical output.
Yuanlong Li
-Added requirements for Introduction part
-Made some progress on Road Network generation, but we might not need this thing anymore. The simulation will be shifted to process simulation.
Eric Steenhof
Public transportation has been around for a couple of decades now. It started with the stagecoach in the nineteenth century. Later on came the steam trains which were capable of carry large capacity of people at the same time. The trains were too big to travel in city themselfs, so the tram was invented. However not city are capable of creating a tramrail network. So with the increasing demands of mobility in the sixties, busses started to be used for public transportation in cities around the Netherlands and the rest of europe. Bus stops were created around cities and a static scheduling system was implemented. This static scheduling system uses a fixed time table around the city. The busses follow fixed routes each time and do not take into account if there are any people waiting at a bus stop or not. Meaning that the busses do not take a shorter route when nobody is willing to stop of is waiting a certain bus stop. This means it is time for a dynamic system, this will be the main focus in this report. The new scheduling system for busses aims to create a more efficient passenger flow. It will be able to send extra busses to bus stops that are or are getting too crowded and also the system will choose a shorter route to it’s destination when no passengers are waiting at the coming bus stops. Users can check in at the bus stop or with their mobile phone apps. The scheduling system will then optimize the routes by taking this information into account. A small part of the report will discusses the possibility of using autonomous busses in the new dynamic scheduling system, analyzing the impact of user, society and enterprise. Different approaches can be used to optimize this schedule. Those will be analyzed and take feedback data from a survey. This data will be inputted in a simulation in order to analyze the consequence of the different needs of the users. Furthermore in this report the infrastructure will be redesigned. The most important infrastructure alteration will be the placement of the bus depot. The simulation will also be used to validate the new dynamic scheduling system. The validation will have with different requirement like waiting time and crowdiness but also with happiness. This is a design report for dynamic schedualing bus system, incoreperating the needs of the User, Society and Entreprise.
Joey Verest
Me and Eric have made the surveys and also have results. 102 people in total filled in the survey. The result of the online survey part can found on the following link: https://docs.google.com/forms/d/1npbu9OSgKHSL2eo8WUvONu5V62wygVl9kkTmxdj_m9s/viewanalytics
Eric Wolters
Together with Joey i made and conducted the survey
Lester Jones
- Write the approach
- Some more study regarding the USE-aspects