【正文】 With special designed agents user specific information can be provided. In urban traffic these intelligent agents are useable in delivering information about weather, traffic jams, public transport, route closures, best routes, etc. to the user via a Personal Travel Assistant. Agent technology can also be used for aggregating data for further distribution. Agents and multi agent systems are capable of simulating plex systems for traffic simulation. These systems often use one agent for every traffic participant (in a similar way as object oriented programs often use objects). The application of agents in (Urban) Traffic Control is the one that has our prime interest. Here we ultimately want to use agents for proactive traffic light control with online optimisation. Signal plans then will be determined based on predicted and measured detector data and will be tuned with adjoining agents. The most promising aspects of agent technology, the flexibility and proactive behaviour, give UTC the possibility of better anticipation of traffic. Current UTC is not that flexible, it is unable to adjust itself if situations change and can39。t handle unprogrammed situations. Agent technology can also be implemented on several different control layers. This gives the advantage of being close to current UTC while leaving considerable freedom at the lower (intersection) level. Designing agent based urban traffic control systems The ideal system that we strive for is a traffic control system that is based on actuated traffic controllers and is able to pro actively handle traffic situations and 3 handling the different, sometimes conflicting, aims of traffic controllers. The proposed use of the concept of agents in this research is experimental. Assumptions and considerations on agent based urban traffic control There are three aspects where agent based traffic control and management can improve current state of the art UTC systems: Adaptability. Intelligent agents are able to adapt its behaviour and can learn from earlier situations. Communication. Communication makes it possible for agents to cooperate and tune signal plans. Proactive behaviour. Due to the pro active behaviour traffic control systems are able to plan ahead. To be acceptable as replacement unit for current traffic control units, the system should perform the same or better than current systems. The agent based UTC will require online and proactive reaction on changing traffic patterns. An agent based UTC should be demand responsive as well as adaptive during all stages and times. New methods for traffic control and traffic prediction should be developed as current ones do not suffice and cannot be used in agent technology. The adaptability can also be divided in several different time scales where the system may need to handle in a different way (Rogier, 1999): gradual changes due to changing traffic volumes over a longer period of time, abrupt changes due to changing traffic volumes over a longer period of time, abrupt, temporal, changes due to changing traffic volumes over a short period of time, abrupt, temporal, changes due to prioritised traffic over a short period of time One way of handling the balance between performance and plexity is the use of a hierarchical system layout. We propose a hierarchy of agents where every agent is responsible for its own optimal solution, but may not only be influenced by adjoining agents but also via higher level agents. These agents have the task of solving conflicts between lower level agents that they can39。t solve. This represents current traffic control implementations and idea39。s. One final aspect to be mentioned is the robustness of agent based systems (if all munication fails the agent runs on, if the agent fails a fixed program can be executed. To be able to keep our first urban traffic control model as simple as possible we have made the following assumptions: we limit ourselves to inner city traffic control (road segments, intersections, corridors), we handle only controlled intersections with detectors (intensity and speed) at all road segments, we only handle cars and we use simple rule bases for knowledge representation. Types of agents in urban intersection control As we divide the system in several, recognisable, parts we define the following 4 types of agents: Roads are represented by special road segment agents (RSA), Controlled intersections are represented by intersection agents (ITSA), 4 For specific, defined, areas there is an area agent (higher level), For specific routes there can be route agents, that spans several adjoining road segments (higher level). We have not chosen for one agent per signal. This may result in a more simple solution but availabl