Smart and Accessible Transportation Hub
| Smart and Accessible Transportation Hub | |
|---|---|
| |
 Accessible Transportation | |
| Team Organizations | CUNY City College Rutgers University Lighthouse Guild NJ Transit; NYC Mayor's Office for People with Disabilities (MOPD); NYS Commission for the Blind (NYSCB) |
| Team Leaders | Zhigang Zhu Jie Gong |
| Participating Municipalities | Passaic NJ |
| Status | Ready for Public Announcement |
| Document | None |
Description
This GCTC Team aims to systematically investigate a novel cyber-physical infrastructure framework that can effectively and efficiently transform existing transportation hubs into smart facilities. The Smart Hub is capable of providing better location-awareness services (e.g. finding terminals, improving travel experience, obtaining security alters) to the traveling public, especially for the underserved populations including those with visual impairment, Autism Spectrum Disorder (ASD), or simply navigation challenges.
Challenges
TBD
Solutions
- Relative localization of mobile devices with Bluetooth connections which generate a locally connected graph (mobile graph).
- Registration of the dynamic mobile graph with the 3D model of the environment at various levels using both visual and digital designs.
- Optimized and customized feedback to users in a crowded environment using the semantic 3D model, the crowd analysis results and the bus schedule information
Major Requirements
- Develop and assemble project team
- Create scope and requirements and a project plan
- Design system architecture with both stationary and mobile nodes
- Develop mobile applications for mobile graph localization
- Register the mobile graph with the 3D model; design and roll out pilot
- Gain stakeholder support esp. PANYNJ and buy-in from the community
- Run pilot for two months
Performance Targets
| Key Performance Indicators (KPIs) | Measurement Methods |
|---|---|
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Standards, Replicability, Scalability, and Sustainability
- Requires interoperable WiFi, Bluetooth and 3D model interfaces.
- Establishes standardized procedures for location-aware services.
- Standardized processes are not unique to city or region and can be replicated and scaled up in multiple cities/communities. The solution is planned and designed to be replicated in 2 transportation hubs in the New York City area.
- The system will have its own business model to create sustainable revenue stream.
Cybersecurity and Privacy
TBD
Impacts
- Improve efficiency of big transportation hubs
- Improve quality of life for persons with visual impairments and/or ASDs, among others
- Improve travel safety and user experience in crowded environments
Demonstration/Deployment
- Phase I Pilot/Demonstration June 2016:
A demonstration system in small scale in a campus building for providing users travel guidance. Videos and visual demos to show the 3D modeling, crowd detection, and preliminary user localization.
- Phase II Deployment June 2017:
A demonstration system in a transportation station in the New York City area for providing users travel guidance. Videos and visual demos to show the 3D modeling, crowd detection, and user localization and navigation assistance.