NSF/USDOT: Context-Aware Software Agents for Multi-Modal Travel

University Of California-Santa Cruz, Santa Cruz CA

Investigators

Abstract

This project addresses the use of software agents in a highly personalized intelligent Advanced Travel Information System (ATIS), providing integrated real-time traffic advice to travelers. Travelers will use increasingly powerful personal and in-vehicle wireless appliances, which monitor the user's context, location and motion (via GPS and other sensors), preferences, priorities, schedule and situation. USDOT studies suggest that information customized to a traveler's specific needs and situation will enable better transit decisions, adjusting schedule, routing, and travel modes (car, bus, train, etc.), and coordinating with other travelers, colleagues and family. This should improve the overall transport system convenience, utilization and safety. Software agents are loosely coupled software elements, ideal for highly flexible, dynamic, and complex systems. Agents are autonomous, pursuing a task agenda and collaborating with other agents via messages. ATIS agents represent traveler goals, preferences and plans, monitor trips, adapt plans to changing circumstances, and prioritize guidance and delegated actions. Agents combine information from multiple sources on routes, congestion, incidents, weather, transit modes, and schedules to make real-time, traveler-specific recommendations. The research goal is to determine how to effectively create, evolve and use models of traveler context, plans, routes and services which enable multiple agents to autonomously maintain their individual information, and to negotiate and combine information with other agents for useful and timely travel recommendations. Research outcomes include: 1) concepts, relationships and attributes for user and travel information; 2) models and representations to drive agent behavior and collaboration; 3) an agent "intelligence" engine integrating rules, machine learning, and information retrieval; and, 4) an evaluation of the technology in a prototype ATIS test bed. More broadly, the research addresses fundamental issues in intelligent multi-agent system development, valuable to other context-aware, agent-based applications and research. The results will enable improvements in numerous user-oriented systems, including space, defense, health care, manufacturing, finance, e-commerce, and transportation, reducing user errors and increasing user satisfaction. Graduate and undergraduate students will participate in the research, results will be incorporated into the education of a diverse student body, and key software components will be distributed as open source.