# Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

arXiv: https://arxiv.org/abs/2304.11397 · HTML: https://mlsanity.com/paper/2304.11397/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2023.

## Built on by (most cited first, 15 of 15)

- [Mobile Edge Intelligence for Large Language Models: A Contemporary Survey](https://mlsanity.com/paper/2407.18921/) (2024)
- [AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning](https://mlsanity.com/paper/2404.06345/) (2024)
- [Optimal Resource Allocation for U-Shaped Parallel Split Learning](https://mlsanity.com/paper/2308.08896/) (2023)
- [Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities](https://mlsanity.com/paper/2401.01544/) (2024)
- [AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging](https://mlsanity.com/paper/2408.03624/) (2024)
- [TrimCaching: Parameter-sharing AI Model Caching in Wireless Edge Networks](https://mlsanity.com/paper/2405.03990/) (2024)
- [SmartCooper: Vehicular Collaborative Perception with Adaptive Fusion and Judger Mechanism](https://mlsanity.com/paper/2402.00321/) (2024)
- [Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving](https://mlsanity.com/paper/2311.16754/) (2023)
- [Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey](https://mlsanity.com/paper/2404.16356/) (2024)
- [PartialLoading: User Scheduling and Bandwidth Allocation for Parameter-sharing Edge Inference](https://mlsanity.com/paper/2503.22982/) (2025)
- [Channel-Aware Throughput Maximization for Cooperative Data Fusion in CAV](https://mlsanity.com/paper/2410.04320/) (2024)
- [Learning from Distributed Eyes: Leveraging Collaborative Perception for Automated Model Adaptation](https://mlsanity.com/paper/2609.18511/) (2026)
- [Towards Secure and Efficient Data Scheduling for Vehicular Social Networks](https://mlsanity.com/paper/2407.00141/) (2024)
- [FedOC: Multi-Server FL with Overlapping Client Relays in Wireless Edge Networks](https://mlsanity.com/paper/2509.19398/) (2025)
- [Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff](https://mlsanity.com/paper/2603.21616/) (2026)

## Abstract (arXiv)

Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected and autonomous driving, smart and connected health, and smart living. At the same time, it is widely recognized that vehicles such as autonomous cars, equipped with significantly powerful SCCSI capabilities, will become ubiquitous in future smart cities. By observing the convergence of these two trends, this article advocates the use of vehicles to build a cost-effective service network, called the Vehicle as a Service (VaaS) paradigm, where vehicles empowered with SCCSI capability form a web of mobile servers and communicators to provide SCCSI services in smart cities. Towards this direction, we first examine the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, we will introduce the system architecture of the VaaS paradigm and discuss how it can provide SCCSI services in future smart cities, respectively. At last, we identify the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy. We expect that this paper paves the way towards developing a cost-effective and sustainable approach for building smart cities.