Incentive-based decentralized routing for connected and autonomous vehicles using information propagation
نویسندگان
چکیده
Routing strategies under the aegis of dynamic traffic assignment have been proposed in literature to optimize system performance. However, challenges persisted their deployment ability and effectiveness due inherent strong assumptions on traveler behavior availability network-level real-time information, high computational burden associated with computing network-wide flows real-time. To address these gaps, this study proposes an incentive-based decentralized routing strategy nudge network performance closer optimum for context where all vehicles are connected autonomous (CAVs). The consists three stages. first stage incorporates a local route switching dynamical approximate optimal flow area based vehicles’ knowledge information. This is sense that it only updates choices rather than network, which circumvents entire network. second optimizes each CAV by considering individual heterogeneity preferences (e.g., value time) maximize utilities travelers area. Constraints also incorporated ensure routes can achieve approximated stage. third leverages expected envy-free incentive mechanism accept determined analytically discusses convergence system. We show rational budget-balanced, willing participate guarantee balance between payments compensations, respectively. Further, conditions compatibility analyzed proved, ensuring behavioral honesty disclosing Thereby, enhance user satisfaction fully environments.
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ژورنال
عنوان ژورنال: Transportation Research Part B-methodological
سال: 2021
ISSN: ['1879-2367', '0191-2615']
DOI: https://doi.org/10.1016/j.trb.2021.05.004