Autonomous vehicle routing strategies analyzed for market efficiency

A new paper explores market efficiency in the context of autonomous vehicle fleets, proposing randomized routing strategies. The research suggests that unpredictable travel times for human-driven vehicles, resulting from randomized CAV routing, can be more efficient than system-optimum or user-equilibrium routing when human drivers show diverse attitudes towards CAVs. The authors recommend augmenting market-share objectives with mean system-wide travel time to encourage cooperation and social welfare. AI

IMPACT This research could inform the development of more efficient and socially beneficial routing algorithms for autonomous vehicle fleets.

RANK_REASON Academic paper on multiagent systems research. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.MA (Multiagent) →

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