Spatial crowdsourcing (SC) enables the assignment of location-based tasks to mobile users who must travel to specific locations to perform sensing or service activities. However, SC systems often operate in strategic environments where both task requesters and task executors possess private valuation information, posing challenges for designing efficient and truthful incentive mechanisms. To address these issues, this paper proposes a truthful multi-task double Auction for quality-aware spatial crowdsourcing (TRUST-SC). The proposed framework adopts a three-tier architecture. First, task executors are grouped into spatial clusters to improve scalability and reduce allocation complexity. Second, reliable executors are identified through a majority-voting-based quality evaluation process. Third, tasks are allocated, and payments are determined through a multi-unit double-auction mechanism that guarantees incentive compatibility and individual rationality. Theoretical analysis and simulation results demonstrate that the proposed mechanism achieves efficient task allocation, reliable executor selection, and improved performance compared with existing benchmark mechanisms.

翻译：空间众包（SC）能够将基于位置的任务分配给需要前往特定位置执行感知或服务活动的移动用户。然而，SC系统通常在战略环境中运行，其中任务请求者和任务执行者都拥有私有估值信息，这为设计高效且真实的激励机制带来了挑战。为解决这些问题，本文提出了一种针对质量感知空间众包的真实多任务双重拍卖机制（TRUST-SC）。所提出的框架采用三层架构。首先，将任务执行者分组为空间聚类，以提高可扩展性并降低分配复杂度。其次，通过基于多数投票的质量评估过程识别可靠执行者。最后，通过一种保证激励相容性和个体理性的多单元双重拍卖机制进行任务分配和支付确定。理论分析和仿真结果表明，与现有基准机制相比，所提出的机制实现了高效的任务分配、可靠执行者选择以及性能提升。