Dual Role AoI-based Incentive Mechanism for HD map Crowdsourcing

Wentao Ye (Chinese University of Hong Kong, Shenzhen & Shenzhen Institute of Artificial Intelligence and Robotics for Society), Bo Liu (Shenzhen Institute of Artificial Intelligence and Robotics for Society), Yuan Luo (Chinese University of Hong Kong, Shenzhen & Shenzhen Institute of Artificial Intelligence and Robotics for Society), Jianwei Huang (Chinese University of Hong Kong, Shenzhen & Shenzhen Institute of Artificial Intelligence and Robotics for Society)

Abstract

A high-quality fresh high-definition (HD) map is vital in enhancing transportation efficiency and safety in autonomous driving. Vehiclebased crowdsourcing offers a promising approach for updating HD maps. However, recruiting crowdsourcing vehicles involves making the challenging tradeoff between the HD map freshness and recruitment cost. Existing studies on HD map crowdsourcing often (1) prioritize maximizing spatial coverage, and (2) overlook the dual role of crowdsourcing vehicles in HD maps, as vehicles serve both as contributors and customers of HD maps. This motivates us to propose the Dual-Role Age of Information (AoI) based Incentive Mechanism (DRAIM) to address these issues. DRAIM aims to achieve the company's tradeoff between freshness and recruitment cost.