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ABSTRACT

In Singapore, roads today already take up 12% of its total land area and with the limited land available. Singapore cannot afford to exhaust its land area by building more roads to accommodate vehicles and further expand the road network.

Parking space is simply the provision for the storage of vehicles. Car parks can be provided in a variety of land uses ranging from residential to shopping centers. Furthermore, car park can cause a serious impact on aesthetics whether it is on street, or in multi-storey aboveground or underground structures. These car parks consume both land and resources, that might be put to better usage in other areas, for instance, building another development or private homes.

A strategic approach to parking would connect the separate decisions of parking provision at individual sites with the achievement of wider planning goals. For instance, saving the land for other usage. A poor planning in car park would result in jams, bad traffic management and causing overspill at the surrounding areas. This is avoidable only if appropriate planning process is in placed, it helps to determine the future parking arrangement associated hence, preventing it to cause unnecessary headaches for the drivers. The main concern of planning parking activity will take note of the ways land and natural environments are conserved, valued, developed or organized using geographical understanding.

Data mining is the computational process of discovering patterns in large datasets, also known as “big data”. Whereas, for our project, the data collected are in time-series format. And time-series data is considered to be multidimensional data, as there is one observation per time unit and each time unit represents a dimension.

Parking utilization provides a time-series of typical parking demand for the development in that area that parking day. Thus, by comparing parking utilization comprehensively, the study will be able to clearly identify patterns and trends of those high and low usage car parks.

Hence, this paper seeks to explore using time-series data mining techniques to discover patterns and trends of similar car park sites within 29 shopping retail malls.

INTRODUCTION

Parking requirements are the exclusive domain of local government and it is subjected to their concerns. Minimally parking requirements include four important elements, (1) the land use for the parking, (2) the car park ratio with regard to the size of the development, (3) taking into consideration of the demand and supply for the car park lots and (4) the car parks surrounding will also influence the demand required (Marsden, 2006).

Cities created off-street parking to ensure that new developments have sufficient space and ample parking (Barter, 2010). A lack of parking will result in generating traffic congestion and causing car to park and spill over to the surrounding areas. Therefore, car park planners and public officials must be able to accurately estimate the number of parking lots required in an amenities to eliminate these parking issues (Bartner, 2010).

In Singapore, roads today already take up 12% of its total land area and with the limited land available. Singapore cannot afford to exhaust its land area by building more roads to accommodate vehicles and further expand the road network.

With the increase of Singapore population in the recent years, the scarcity must be allotted wisely. As Singapore continues to grow as a city, there is a need to increase the supply for housing, industrial and office estate. Therefore, it is not a realistic plan for every Singaporean household to own a car (LTA, 2012).

Having said that, car is not a basic necessity in Singapore since public transportation is well developed and easily accessible. However, Singaporeans seem to think otherwise as the number of households in Singapore that own a car increased to 45% in 2013 from 40% in 2008. In order to curb the amount of car ownership and to ensure the roads is smooth flowing and congestion-free, the authority affirmed that it would continue to emphasize the vehicle ownership and usage restraint measure.

Since 1990, the Certificate Of Entitlement (COE) system has enabled Singapore to exercise effective control of vehicle population growth. As Singapore becomes more urbanized, the social cost of car ownership will also increase. This is because land has to be set aside for parking spaces at not only where we reside, but also at the places where we work, study and play. Allocating more land for car parks means that there is less land for other developments, such as housing, schools or healthcare facilities. On top of that, illegal parking and congestion in local neighborhoods may also become more prevalent.

With these considerations in mind, the authority would like to understand the car park occupancy situation in Singapore. Thus, the authority has requested a consultancy firm to find out more through site survey and observation in theses car parks. The information collected is transformed into knowledge with the help of the team assisting the consultancy firm in producing detailed reports, info-graphics and consolidated data for each car park sites to summarize the findings. This information is crucial to authority, as it will help it to better forward plan and handle the car park issues in Singapore.

Apart on assisting the consultancy firm in report the independent car park site situation, the team will explore and demonstrate the effective use of time-series data mining in analyzing complex data. This research study will help the authority to discover new insights on several clusters of shopping malls that are grouped together based on their similar characteristics through utilizing the car park occupancy.

Car Park Sites

The consultancy firm had completed the data collection process and compiled the results. Its primary focus is to work on the analysis and to report the findings of the 65 car park sites. Additionally, they had also created clusters by grouping the nearby car park sites together. For instance, the car parks of Punggol Plaza and Punggol 21 CC are grouped together, as they are geographically located next to each other.

The allocation of the reports required for all of these car park sites are as shown below:

As of the initial meeting on 30th December 2015, the consultancy firm had completed and submitted 10 reports to the authority. Hence, there are 45 outstanding reports, info-graphics and excel files need to be worked on. the consultancy firm’s submission deadline for the reports is 31st January 2016. Therefore, the team’s initial job scope is to assist the team in the consultancy firm in meeting its submission deadline.

After the completion of phase 1, the team will further process the data collected to coming up with new insights. Additional initiatives will include the comparison of the different car park sites, as well as, a national average representation. This will allow the business owner, to better understand the situation nationwide rather than looking at each car park site’s situation independently. Additionally, the team will also conduct a focus study using time-series clustering on shopping mall car park sites. The team would like to explore and demonstrate with the use of time-series analysis to group similar characteristics shopping mall car park sites together based on their car park occupancy. And lastly, sharing the findings and evaluate the accuracy of the analysis by linking back to the real world.

Project Objective And Business Problem

The objective of this project is to assist a consultancy firm in understanding the current parking situations in 65 different locations in Singapore. These 65 parking locations compromise of 30 retail malls, 15 retails and Food & Beverage (F&B) clusters in landed housing estates, 10 hawker centers, and 10 community clubs.

The study was conducted previously by the consultancy firm through parking occupancy surveys, human traffic counts, and interview survey at selected locations at stipulated times. The collected data will then be further processed before submitting it to the authority to understand the current parking situation at these locations. The team will be splitting the project into two phases to complete.

For phase 1, the team will be assisting the consultancy firm to analyze each car park site situation. Each parking site result collected is tabulated into a single Microsoft Excel spreadsheet file according to each survey type. Using the excel spreadsheet, it will help to generate charts and graphs for the info-graphics. Finally, a final report will share the findings of each parking site. It includes a write-up of the characteristics and methodology of the entire process, all location maps and captured images (if any). Lastly, the final report will be structured as per the format shown below:

1. Executive Summary
2. Site Background
3. Site Characteristics
4. Site Assessment
5. Survey Deployment Plan
6. Survey Findings
7. Conclusion
8. Appendices
 8.1 Site Map of the parking locations
 8.2 Car park characteristics
 8.3 Pre Survey Observations & Results
 8.4 Info-graphic to summarize the results collected
 8.5 Survey Questionnaire Template