/HappyParking

Primary LanguageJavaScript

GovHack 2018 Challenge

Team Parkers - Happy Parking

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Live demo is available here.

Our aims
The Happy Parking! project aims to make the most use of the open-source data from government solving practical problems and tell stories of urban development according to historical car park data.

Part 1

Parkers aim to create a real-time web app for end-users, helping drivers to find a vacant parking spot efficiently. Our system will render the result based on the real-time parking bay senser dataset and other datasets from the melbourne open data center.

It allows users to select the location they want to go and get them all vacant car parks in the area within 500 m and match the car park restrictions with duration they are willing to park. It has a priority rank for the matching function -- free first, within the area, outside area. If there are no vacant spots in this area, users can also use the off-street car park locations to find a car park.

At the government end, the real-time parking solution can help reduce the air pollution or traffic problem that caused by circling vehicles for vacant spaces as well as reduce the time wasted in finding a vacant spot, especially in the city area.

On the other hand, the visualization shows the land utilization in a more straightforward way, which supports the government to monitor and make a decision to improve quality of life.

Part 2

In addition, the web app also provides a visualization regarding the analysis of the parking area occupancy rate based on historical data of the past years.

It demonstrates the occupancy rate changes in each street with inground sensors according to their timestamps. Regarding these car park analysis data, it enables users to understand the urban planning in Melbourne and the changes in economic centres. Moreover, support the government’s urban planning decision in car parking, Remove car parks with low occupancy rate and build greenspace or improve public transportation network construction to reduce car park stress.

We judged the occupancy rate on the peak hour(6:30-9: 00 am & 3:00-18: 30 pm) and whether it is the weekdays and weekends to make a comparison for each car par zone.

Features

On-street parking bay usage

  • We aims to discover and better utilise the benefits of public parking space in Melbourne CBD.
  • We calculated the usage of parking space from the 2016/2017 On-street Car Parking Sensor Data. alt text

Real-time on-street parking bay occupation status

  • We combined different dataset provided by the City of Melbourne.
  • We provided useful information about the vacant parking space in the city. alt text
  • We may improve the usage of vacant parking space by enabling a booking system

Used Datasets

  1. On-street Parking Bay Sensors
  2. On-street Parking Bays
  3. On-street Car Park Bay Restrictions
  4. On-street Car Parking Sensor Data - 2017
  5. On-street Car Parking Sensor Data - 2016
  6. On-street Car Parking Sensor Data - 2015
  7. On-street Car Parking Sensor Data - 2014
  8. Off-street car parks with capacity and type

Dependencies

TerriaMap prerequisites and scripts

These tools are required for build and run TerriaMap:

  • Node.js
  • GDAL (try brew install gdal)

Therea re some useful TerriaMap commands. Use these under the terriamap folder.

  • npm install: Install the dependencies of the TerriaMap. (node_modules)
  • npm run gulp: Build the TerriaMap.
  • npm start: Start the TerriaMap at localhost:3001. 4 processes will be started in the background.
  • npm stop: Stop the TerriaMap, Terminate the 4 processes.