A adaptability mechanisms study of traffic liability-division in autonomous vehicle era

This paper addresses the adaptability challenge of autonomous vehicles (AVs) to traditional traffic governance systems by proposing a liability integration model that incentivizes producers to assume accident liability; and employs a four-party evolutionary game (government, insurer, producer, consumer) grounded in prospect theory to argue the proposition. Through rigorous mathematical modeling, six equilibrium states are derived, covering the full spectrum of feasible states under the current situations related with AVs. Among the six identified equilibria, only State 4 satisfies the Pareto efficiency criterion, enabling all stakeholders to pursue value-maximizing strategies. The remaining states represent coordination failures that necessitate governance interventions to achieve higher-order equilibria. To facilitate the transition from suboptimal equilibria to the optimal State 4, a set of governance mechanisms is proposed, focusing on strategic alignment and systemic coordination. Furthermore, computational simulations validate the robustness of the proposed suggestions, confirming the analytical conclusions under varied parameter configurations. Our findings provide critical insights for advancing the construction of governance frameworks tailored to AVs, having both important theoretical and practical implications.