Towards application of automated planning in urban traffic control

Abstract

Abstract-Advanced urban traffic control systems are often based on feed-back algorithms. For instance, current traffic control systems often operate on the basis of adaptive green phases and flexible co-ordination in road (sub) networks based on measured traffic conditions. However, these approaches are still not very efficient during unforeseen situations such as road incidents when changes in traffic are requested in a short time interval. Therefore, we need self-managing systems that can plan and act effectively in order to restore an unexpected road traffic situations into the normal order. A significant step towards this is exploiting Automated Planning techniques which can reason about unforeseen situations in the road network and come up with plans (sequences of actions) achieving a desired traffic situation. In this paper, we introduce the problem of selfmanagement of a road traffic network as a temporal planning problem in order to effectively navigate cars throughout a road network. We demonstrate the feasibility of such a concept and discuss our preliminary evaluation in order to identify strengths and weaknesses of our approach and point to some promising directions of future research.

A Hybrid Approach to Process Planning: The Urban Traffic Controller Example

“…3. The domain model is made up of static and dynamic part (Jimoh et al, 2013a). The static part represents road network topology, such as road name, road capacity, road length and junctions linking the roads.…”

“…Control systems which support Urban Traffic Control (UTC), such as those controlling networks of traffic lights, have utilised AI techniques since the 1970's (Jimoh and McCluskey, 2014). These systems are embedded in a real-time control environment and are often based on algorithms that rely on feedback and adaptation.…”

“…Therefore, there is a need for intelligent controls that can effectively generate plans and execution towards restoring an unpredicted traffic situation to desired condition. One promising direction is by creating a hybrid control design that will support intelligent systems to spontaneously reason and deliberate with their declarative knowledge, towards managing themselves during unexpected situations (Jimoh et al, 2013a). Such intelligent controls would be an achievement in the urban traffic control domain and this paper is a step towards realising such goal.…”

Self-management in Urban Traffic Control: An Automated Planning Perspective

“…In this work, a network of roads, as shown in Figure 3, within Huddersfield town center area of United Kingdom, was considered for our experimental analysis [28,29].…”

Automated planning for Urban traffic control: Strategic vehicle routing to respect air quality limitations

“…Whereas there has been a long record of the use of AI techniques in road transportation [16,24], with some notable exceptions, for example [1,13,26], there has been little application of AI Planning and Scheduling techniques to urban traffic control. The novelty of this paper lies in the application of automated planning techniques for strategic urban traffic control, in order to calculate routes for vehicles entering an urban area to satisfy regional-level constraints.…”