Preference-Based Temporal Coordination: A Pre-Optimization Approach to Urban Traffic Management

Abstract

Urban traffic congestion represents a fundamental coordination failure in contemporary metropolitan transportation systems, where traditional infrastructure expansion, real-time navigation, and congestion pricing mechanisms provide reactive rather than preventive solutions. This article presents a preference-based temporal coordination framework that addresses the temporal dimension of travel decisions through overnight optimization of departure schedules collected from users the evening before travel. The framework operates through three integrated architectural layers encompassing user preference collection, constraint satisfaction optimization, and personalized schedule delivery, enabling system-wide coordination while respecting individual flexibility constraints and arrival deadlines. Theoretical foundations in Wardrop equilibrium principles and traffic assignment theory demonstrate that individual rational routing behavior produces collectively suboptimal outcomes, with dynamic demand variations exacerbating network inefficiencies. The proposed pre-optimization method distinguishes itself from real-time systems by employing computationally intensive algorithms that consider complex interactions across entire user populations simultaneously, achieving coordination impossible within second-level response constraints. Extensions incorporating carpooling coordination and multimodal transit integration multiply potential benefits through vehicle reduction and optimized mode combinations. Key challenges during implementation include overcoming cold start thresholds of adoption, obtaining user compliance, ensuring computational scalability, keeping information private, and addressing a range of equity concerns-all requiring deliberated design choices. There are environmental benefits that stem from reduced idling and smoother traffic flow, and economic effects ranging from an increase in individual productivity to deferred metropolitan investments in infrastructure. This given framework makes temporal coordination foundational infrastructure for next-generation urban mobility systems integrating autonomous vehicles and smart city ecosystems.