Accessible Hobart Revamp using AI and GIS

Project Info

Team Name


Team 1023


Team Members


vedaanth k gureja , Aniruddha Biswas

Project Description


Background
Hobart is facing congestion problem in the CBD. Micro mobility has the potential to reduce Hobart’s congestion. While active transport is very popular in Hobart,
Large numbers of very short car trips tend to congest the streets
Leads to increasing demands for parking lanes 


#hobart #ai #gis #arcgis #trafficcams #vehicledetection

Data Story


Approach
1. Optimal routes to use electric Scooters
2. Use AI to Detect Vehicles on Congested roads using the Traffic Cams
3. Use AI-based systems for traffic Management using the Shortlisted Traffic Cam data

Stage 1: Optimal routes to use electric Scooters
* For finding the optimal routes we have utilized open datasets:
* These datasets helped us in mapping topographic information:
*The information varied from bus stops, car parks, open playgrounds, parks, hospitals and schools.
*The idea behind this was to detect heavy pedestrian presence in the city.

Optimal Routes for using Electric Scooter
* The choice of optimal routes is based on Heuristics.
* In our proposal, we suggested that scooters should be operated on parallel streets of the pedestrian congested street.
Stage 2: Use AI to Detect Vehicles on Congested roads using the Traffic Cams
Stage 3: Use AI-based systems for traffic Management using the Shortlisted Traffic Cam data


Evidence of Work

Video

Team DataSets

CoH Buildings

Data Set

CoH Trees - Significant Tree Locations

Data Set

CoH Trees - with Set ID

Data Set

The List Tasmania

Data Set

Layer: Facilities Zoom in

Data Set

LIST Topography and Relief:

Data Set

City of Hobart Open Data

Data Set

City of Hobart - Open Space Parks

Data Set

City of Hobart Playground Locations

Data Set

Challenge Entries

Rethinking mobility for a more accessible Hobart

Micromobility has the potential to reduce Hobart’s congestion. Given Hobart’s topography and location of residential and retail precincts, our challenge is to understand which micromobility vehicles, routes and nodes would be beneficial to making the city quicker to navigate for the largest number of vehicle types and transport users.

Go to Challenge | 3 teams have entered this challenge.