Intelligent Transportation System Data Collaboration
Intelligent Transportation System Data Collaboration
Description:
Collaborate with transportation and logistics companies to create a data-sharing platform that optimizes traffic management, reduces congestion, and supports the development of an intelligent transportation system (ITS).
Objectives:
• Reduce traffic congestion and improve road safety.
• Optimize resource allocation in public transportation.
• Enhance the overall efficiency of the transportation network.
Socio-Economic Impact:
• Government: Reduced congestion, improved public safety, reduced emissions, and more efficient transportation planning.
• Private Sector: Improved fleet management, reduced operational costs, and access to statistics and insights to enhance transportation planning.
Potential Datasets:
• Real-time and predictive traffic flow data using AI and machine learning models.
• Vehicle tracking and routing data from logistics companies.
• Environmental data for air quality and emissions monitoring.
• Data on accident-prone areas, driver profiles, and historical claims data.
Potential Stakeholders:
Transportation & Logistics Companies, Automotive & Vehicle distributors, Insurance & Financial Services, Telecommunications & Network Providers.
Code: Transport & Services
Sustainable Development Goals (SDG):
International Best Practices:
In Los Angeles, the city partners with private transportation companies to create a real-time traffic management system, reducing congestion and emissions while improving travel times.
How to get involved?
D4G Alliance initiative facilitates win-win collaboration between relevant stakeholders where privately held data are utilized to produce actionable insights for the public interest in the Emirates of Abu Dhabi.
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