Difference between revisions of "Car Park Overspill Study PROJECT DOCUMENTATION FINAL"
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There have been some research papers discussing the behavior of the drivers when they park cars in a car park. We selected a few relevant heuristic parking algorithms and compare them in the following table: | There have been some research papers discussing the behavior of the drivers when they park cars in a car park. We selected a few relevant heuristic parking algorithms and compare them in the following table: | ||
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| + | === Model Interface === | ||
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Revision as of 12:09, 13 April 2016
Contents
Preliminary Phase
Scope
Our sponsor requires us to finish 5 final reports of different development sites during the preliminary phase of our project. The necessary data and infographics are prepared by the sponsor and his tea, our job scope is to compile the report using the sample template and interpret the data to generate some insights which can be helpful for LTA future planning. A typical final report contains the following components:
- Executive Summary
- Site Background
- Site Characteristics
- Site Assessment
- Survey Findings
- Conclusion
“Executive Summary” gives a brief overview of the report and its conclusion. “Site Background”, “Site Characteristics” and “Site Assessment” provides the basic information of the site, such as the nature, the size, the transportation availability of the site and etc. Our focus is on “Survey Findings” which uses the data collected on both weekday and weekend at the site to generate some insights. The generated insights elaborate on the vehicles traffic pattern, the human traffic during different period of the day and most importantly whether there is overspill, this helps LTA understands the utilization rate of the car park and make certain adjustments in the future.
Actual Deliverables
By the end of the preliminary phase, our group has finished 5 final reports as planned at the beginning of the project. These 5 final reports are:
- Final Report - Greenwood Ave & Hillcrest Rd
- Final Report - Vivocity
- Final Report - Frankel Ave
- Final Report - Jalan Mata Ayer
- Final Report - Yuhua Market & Hawker Centre
Phase 2
Revised Methodology
We have revised our goal of Phase 2, instead of building a simulation tool with projection of a car park together with its surrounding environment such as streets and roads, now we aim to let the tool to simulate a car park inside traffic only. Considering the raw data at hand, it includes surveyed car parks inbound and outbound traffic. The data become more meaningful when we uncover the pattern of car arriving at a car park and apply the pattern into a model which simulates the traffic inside a car park only. Therefore, we redefined the Phase 2 objective, and accordingly we update the preparing data process to suit the updated needs.
Data Preparation
To help us understand the traffic situation inside a car park, we process the raw data in the following steps:
1. Based on the nature of the car park's associated site, hence, we categorized 4 sets of data - Shopping Malls, F&B Clusters, Community Clubs, and Hawker Centres. The following table shows the basic information of each category:
| Site Category | Shopping Mall | Community Club | Hawker Centre | F&B Cluster |
|---|---|---|---|---|
| Num of Samples | 17 | 10 | 10 | 7 |
| Survey Periods | 10am - 9pm (Weekday & Weekend) | 9am - 6pm (Weekend), 2pm - 10pm (Weekday) | 7am - 3pm (Weekday & Weekend), 6pm - 8pm(Weekday) | 10am - 10pm (Weekday & Weekend) |
2. Organize the Inbound Traffic data of each site in a site category, such that we have a collection of data showing the number of arriving cars at each car park in each 15 minutes interval from 7:00 am to 10:00 pm. The following screen shot shows an example of the collection of data of Shopping Mall Category sites:
3. Since the survey of Inbound Traffic data was collected in varied time periods in a day, there are missing data in the in some time intervals in the consolidated data set, we replace the missing data with mean value of each data row.
4. We understand that the car parks' associated development site have varied capacities in accommodating patrons or customers, so we normalized the data , by applying below formula:
The following screen shot shows an instance of data has been normalized:
5. After normalizing the data, in each site category, we still found a few outliers with normalized value deviating from the mean value greatly. To ensure that the data as input is effective in representing the general cases to the agent-based model we build, we have to remove those outliers. The following plot chart shows an example of the effect before and after removing the outliers:
Implementation of Agent-based Model
Defining agent behavior
In Agent-based Modelling, agents can be categorized into animated ones and inanimated ones. In NetLogo, the animated agents are called "turtles", and the inanimated agents are called "patches". In our case, the only "turtle" is car object. The rest objects like roads, traffic cross corners, parking lots, entrance, exit and lift are "patches".
Define Parking Car's behavior:
There have been some research papers discussing the behavior of the drivers when they park cars in a car park. We selected a few relevant heuristic parking algorithms and compare them in the following table:
Model Interface
