Dealing with Uncertainty in Operational Transport Planning

2007

In order to address limitations of static traffic assignment, recent research focused on the development of Dynamic Traffic Assignment (DTA) models that are capable of estimating time-varying network conditions by capturing traffic flow and route choice behavior. Such models compute the spatio-temporal path for every vehicle so that no user can switch path and improve his travel. Moreover, they account for real-time routing behavior in response to congestion due to recurrent and non-recurrent events. In this context, DTA models provide transportation planners and engineers with modern tools to improve the accuracy of traditional transportation planning approaches and enable modeling of Intelligent Transportation Systems technologies that are used to improve transportation system management.

2005

This paper deals with the real time regulation of traffic within a disturbed transportation system. We show the necessity of a decision support system that detects, analyzes and resolves the unpredicted disturbances. Due to the disturbed aspect of transportation system, we present a multi-agent approach for the regulation process. This approach includes an anytime algorithm, which permits to access to solutions in real time. The quality of the results increases with allocated time. Our system is able to foresee all behaviors according to the environment with which it interacts. These aims offer real guarantees with respect to the temporal deadlines. The main objective is not to search an optimal solution for a disturbance, but to define a set of possible solutions.

2012

In multi-agent routing, there is a set of mobile agents each with a start location and destination location on a shared infrastructure. An agent wants to reach its destination as quickly as possible, but conflicts with other agents must be avoided. We have previously developed a single-agent route planning algorithm that can find a shortest-time route that does not conflict with any previously made route plans. In this paper, we want to compare this route planning approach with non-planning approaches, in which intersection agents determine which agent may enter an intersection next, and where the agent will subsequently go (given its destination). When making these decisions, the intersection agents use only locally observed traffic information. Our experiments show that context-aware routing produces more efficient results in case no incidents disrupt the execution. However, in the face of unexpected incidents, the performance of the intersection management policies proves very robust, while context-aware routing only produces good results when coupled with effective plan repair mechanisms.

Abstract Road traffic systems are complex, heterogeneous, expensive to maintain, and difficult to optimise. It raises several challenges related to congestion, environment, safety, support, information management, scheduling and large software maintenance. Incorporating autonomic principles of self-management to transport management systems will aim directly at tackling the challenges and overcoming the shortfall of conventional systems. Among the main challenges are the extensively studied path planning algorithms, used in traffic flow management, navigation and scheduling applications. In this paper, we give an overview of our current research direction aiming towards the gradual development of road traffic management systems using a set of distributed systems, endowed with self-management properties. We then investigate developing autonomic self-management properties for path planning. We propose hyper-heuristic model for the selection and construction of path planning heuristics, to be used in building autonomic properties for the future Autonomic Road Transport Support (ARTS). Keywords: Autonomic Systems, ARTS, Path Planning, Distributed Decision Making, Hyper-heuristics, Road Traffic Management Systems, Transport.

Transportation Research Part C: Emerging Technologies, 1994

This study presents a framework for integrating planning and analysis in a computer supported environment that facilitates deliberation and consensus seeking. The planning process conducted with the aid of an intelligent facilitator benefits from on-line analysis capabilities that are integrated into a unified computer system called PLANiTS (Planning and Analysis to Integrate Intelligent Urban Transportation Systems). It is constructed around four components or bases: policy and goals, strategy and action, knowledge, and methods and tools. This proposed methodology involves extensive use of knowledge bases in assessing transportation actions.

2010

In the Netherlands, the common approach for road network traffic control is top-down control by applying so-called scenarios. However, when the number of scenarios are getting larger, operators are not able to handle. In this paper, we will present an approach to improve the scenario-based control from a bottom-up approach by using so-called scenario coordination module. The bottom-up approach introduces a set of agents called buildingblocks. A road network can be divided into several subnetworks and each subnetwork can be divided into several buildingblocks. The combination of buildingblocks can represent a scenario. Moreover, they can communicate with each other and try to resolve the conflicts by themselves. By using this approach, the scenario-based top-down control becomes more dynamic, flexible and more adaptive to the current traffic pattern. It improves the performance of the topdown control. This approach has been applied in the operational traffic control system for the Dutch city of Amsterdam. It was developed at the Dutch traffic management company Trinité Automation B.V.

… of the European Simulation and Modelling …, 2005

Transportation Research Part A: General, 1990

Fundamental to the operation of most currently envisioned Intelligent Vehicle-Roadway System (IVRS) projects are advanced systems for surveillance, control and management of integrated freeway and arterial networks. A major concern in the development of such Smart Roads, and the focus of this paper, is the provision of decision support for traffic management center personnel, particularly for addressing nonrecurring congestion in large or complex networks. Decision support for control room staff is necessary to effectively detect, verify and develop response strategies for traffic incidents. The purpose of this paper is to suggest a novel artificial intelligence-based solution approach to the problem of providing operator decision support in integrated freeway and arterial traffic management systems, as part of a more general IVRS. A conceptual design is presented that is based on multiple real-time knowledge-based expert systems (KBES) integrated by a distributed blackboard problem-solving architecture. The paper expands on the notions of artificial intelligence and Smart Roads, and in particular the role, characteristics and requirements of KBES for real-time decision support. The overall concept of a decision support architecture is discussed and the blackboard approach is defined. A conceptual design for the proposed distributed blackboard architecture is presented, and discussed in terms of the component KBES functions at an areawide level, as well as at the subnetwork or individual traffic control center level.

… Research part C: …, 2005

Modern decision support systems (DSS) not only store large amounts of decision-relevant data, but also aim at assisting decision-makers to explore the meaning of that data, and to take decisions based on understanding. In transportation domains, a multiagent approach to the construction of DSS is becoming increasingly popular, because it does not only reduce design complexity, but it also adequately supports a dialogue-based stance on decision support interactions. However, despite recent advances in the field of agent-oriented software engineering, a principled approach to the design of multiagent systems for decision support is still to come.

2002

Abstract In transport, and especially public transport, many inefficiencies occur due to lack of coordination between companies. To reduce such inefficiencies, a multi-agent planning method is proposed that can be applied to coordinate the plans of both public transport and freight transport organizations.