Team Name:
iWing-Team 681
Team Members:
iWing-Team 681
The Darwin government has provided a wealth of accessible traffic infrastructure data that will help Identify (and justify) the ideal locations for e-mobility stations in Darwin CBD. In this challenge, our team will present a method to identify the location of sub-traffic stations. Due to limited time, we will give an example of location information based on this method later. This challenge will focus on the methods we have found and their practical feasibility.
According to the survey, in 2016, both people across Australia and the northern territory of the people's way of major commuter is private cars, the proportion of more than 50% (https://profile.id.com.au/australia/travel-to-work? WebID = 250). Electric cars have attracted a lot of people's attention because of their environmentally friendly features, and the government is hoping to increase investment to attract people to use electric cars for commuting. Electric cars, on the other hand, are a headache because of the scarcity of charging facilities. Electric car owners can choose to charge at home after work, but how to charge in the work area at work or in CBD on weekends is a headache.
According to our team, the principles for establishing e-mobility stations in the CBD area of Darwin are as follows:
1. It should be built where there are enough parking Spaces
2. The address does not affect traffic
3. It's not far from the destination of most commuters
The principle of the first and the second is based on the charging time is longer (https://pod-point.com/guides/driver/how-long-to-charge-an-electric-car) generally, therefore charging vehicles should not affect the normal traffic. The third point is to consider the availability of charging facilities. If an e-mobility station is built very far from the destination, people will not choose it.
The data sets we mainly used were Transportation Application, City of Darwin Parking PayStay Zones and Google map Traffic Layer API.
After the above three principles are digitized, two structured data standards can be obtained:
1.ShapArea field (Transportation Application) is greater than 3000 or TotalParking_Bays is greater than 250 (City of Darwin Parking PayStay Zones) (to meet sufficient Parking Spaces and not affect traffic)
2.Google map shows congestion on Monday at 8.30am and Saturday at 12.00pm
Their idea is to screen the Parking Spaces with TotalParkingBays field greater than 250 through City of Darwin Parking PayStay Zones, pour their coordinates into the Google map Traffic Layer, and observe whether the two periods of 8.30am on Monday and 12.00pm on Saturday are congested to confirm whether the Parking lot is suitable.
Through the above methods, we found that Carparks: SRFCP198 is an appropriate choice.
Currently, in our work, we have encountered a resistance. There is no coordinate data in Transportation Application and the data that can be linked to City of Darwin Parking PayStay Zones. But our group was convinced that since both data sets could be presented in arcgis, coordinate data must exist.
Description of Use Identify the traffic flow in the location of the parking lot
Description of Use Identify the coordinates of the parking lot and the number of parking Spaces
Description of Use Identify parking area
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 45 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 39 teams have entered this challenge.
Eligibility: Must use Tasmanian data
Go to Challenge | 9 teams have entered this challenge.
Eligibility: Use at least one City of Darwin data source.
Go to Challenge | 7 teams have entered this challenge.
