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Toward a personalized autonomous transportation system: Vision, challenges, and solutions
Linlin You1, Mai Hao1, Jian Sun2
1School of Intelligent Systems Engineering, Sun Yat-Sen University, Shenzhen 518107, China.
Innovation (Cambridge (Mass.))
|October 17, 2024
Summary
Intelligent transportation systems evolve into autonomous transportation systems (ATS) to overcome fragmentation. A new TPE framework using blockchain, federated learning, and large models ensures trustworthy, private, and equal mobility services.
Area of Science:
- Intelligent Transportation Systems (ITS)
- Autonomous Transportation Systems (ATS)
- Cloud-Edge-Device Continuum
Background:
- Fragmented ITS lead to isolated systems, resource competition, and information gaps, degrading traffic management and service levels.
- The evolution towards ATS aims to create a collaborative, sustainable ecosystem with cloud-edge-device interoperability.
- Key challenges for ATS include disparate data, deficient models, and conflicting interests in supporting autonomous and personalized mobility.
Purpose of the Study:
- To address the challenges hindering the development and widespread adoption of autonomous transportation systems (ATS).
- To propose an innovative framework ensuring trustworthy, private, and equitable mobility services within an ATS.
- To enable personalized mobility solutions while maintaining data privacy and system integrity.
Main Methods:
- Design and integration of a novel framework named TPE (Trustworthy, Private, and Equal-serving).
- Seamless integration of blockchain technology for a trustworthy operating environment.
- Application of federated learning for processing private data into globally shareable knowledge.
- Development of large-scale models for personalized adaptation and mobility services.
Main Results:
- The TPE framework successfully integrates blockchain, federated learning, and large-scale models.
- It establishes a trustworthy operating environment for autonomous transportation systems.
- Enables the processing of private data for generating globally applicable knowledge and personalized services.
Conclusions:
- The TPE framework provides an innovative solution to critical challenges in autonomous transportation systems.
- ATS empowered by TPE can effectively serve diverse user groups with enhanced privacy and equity.
- This approach facilitates a more systematic balance between mobility demand and supply with reduced human intervention.
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