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Advanced Mobility and Transport Engineering

Book Description

Multimodal transport network customers need to be directed during their travels. A travel support tool can be offered by a Multimodal Information System (MIS), which allows them to input their needs and provides them with the appropriate responses to improve their travel conditions.

The goal of this book is to design and develop methodologies in order to realize a MIS tool which can ensure permanent multimodal information availability before and during travel, considering passengers' mobility.

The authors propose methods and tools that help transport network customers to formulate their requests when they connect to their favorite information systems through PC, laptop, cell phone, Portable Digital Assistant (PDA), etc. The MIS must automatically identify the websites concerning the customer's services. These sites can, in fact, represent transport services, cultural services, tourist services, etc. The system should then be able to collect the necessary travel information from these sites in order to construct and propose the most convenient information according to the user's requests.

Contents

1. Agent-oriented Road Traffic Simulation, René Mandiau, Sylvain Piechowiak, Arnaud Doniec and Stéphane Espié.

2. An Agent-based Information System for Searching and Creating Mobility-aiding Services, Slim Hammadi and Hayfa Zgaya.

3. Inter-vehicle Services and Communication, Sylvain Lecomte, Thierry Delot and Mikael Desertot.

4. Modeling and Control of Traffic Flow, Daniel Jolly, Boumediene Kamel and Amar Benasser.

5. Criteria and Methods for Interactive System Evaluation: Application to a Regulation Post in the Transport Domain, Houcine Ezzedine, Abdelwaheb Trabelsi, Chi Dung Tran and Christophe Kolski.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Preface
  5. Introduction
  6. Chapter 1: Agent-oriented Road Traffic Simulation
    1. 1.1. Introduction
    2. 1.2. The principle of multi-agent systems
      1. 1.2.1. Motivations
      2. 1.2.2. Agents versus multi-agent systems
        1. 1.2.2.1. Agents
        2. 1.2.2.2. Environment
        3. 1.2.2.3. Interaction
        4. 1.2.2.4. Organization
    3. 1.3. General remarks on traffic simulation devices
      1. 1.3.1. Granularity level
      2. 1.3.2. A centralized approach for traffic simulation
      3. 1.3.3. Behavioral approaches
        1. 1.3.3.1. Approaches based on cellular automatons
        2. 1.3.3.2. Approaches influenced by robotics
        3. 1.3.3.3. Current multi-agent approaches
    4. 1.4. ArchiSim simulator
      1. 1.4.1. A distributed architecture
      2. 1.4.2. A behavioral model of agents
        1. 1.4.2.1. Environment and perception
        2. 1.4.2.2. Agents and interactions
    5. 1.5. The issue of traffic simulation in intersections
      1. 1.5.1. Behavioral model of agents
        1. 1.5.1.1. Normative model versus non-normative model
        2. 1.5.1.2. Anticipative model
      2. 1.5.2. Illustrative example of the proposed model
        1. 1.5.2.1. Norm violation by the agents
        2. 1.5.2.2. Deadlock anticipation
    6. 1.6. Assessment of different scenarios
      1. 1.6.1. Assessing the execution time of agents
      2. 1.6.2. Reducing the number of deadlock situations
      3. 1.6.3. Real situations
    7. 1.7. Conclusion
    8. 1.8. Bibliography
  7. Chapter 2: An Agent-based Information System for Searching and Creating Mobility-aiding Services
    1. 2.1. Introduction
    2. 2.2. Formulating the problem
    3. 2.3. The global architecture of the system
      1. 2.3.1. Modeling based on communicating agents
      2. 2.3.2. Local databases within the ISAM
      3. 2.3.3. Dynamic data archiving model
        1. 2.3.3.1. Data classification and archiving
        2. 2.3.3.2. Functioning
    4. 2.4. Proposal of a resolution system with several interactive entities: a dynamic multi-agent system
    5. 2.5. The behavior of a scheduling agent
      1. 2.5.1. First level of optimization: building initial route plans for mobile agents
        1. 2.5.1.1. Description
        2. 2.5.1.2. Route plan representations
      2. 2.5.2. Second level of optimization: creating services using an evolutionary framework
        1. 2.5.2.1. Solution modelling
        2. 2.5.2.2. The adopted genetic operators
          1. 2.5.2.2.1. Crossover operator with external control
          2. 2.5.2.2.2. Mutation operator with integrated control
        3. 2.5.2.3. Generating definite route plans
        4. 2.5.2.4. The functions of evaluation
        5. 2.5.2.5. Generating solutions
    6. 2.6. Managing system robustness when dealing with disruptions: advancing a negotiation process between stationary and mobile entities
      1. 2.6.1. Initiators and participants
      2. 2.6.2. The proposed protocol
    7. 2.7. The usefulness of a dedicated dynamic ontology
      1. 2.7.1. Terms
      2. 2.7.2. Predicates
    8. 2.8. Simulations and results
      1. 2.8.1. Intra-system communication
      2. 2.8.2. The validity and assessment of the mobile agent paradigm
      3. 2.8.3. Example of a mobility-aiding services demand scenario
        1. 2.8.3.1. Initial route plans and definite route plans of ICAs
        2. 2.8.3.2. Applying the negotiation process
      4. 2.8.4. Case study of an itinerary service [KAM 07]
        1. 2.8.4.1. The organization of cooperative information mobility service
        2. 2.8.4.2. The shortest distributed route algorithm
    9. 2.9. Conclusion and perspectives
    10. 2.10. List of abbreviations
    11. 2.11. Bibliography
  8. Chapter 3: Inter-vehicle Services and Communication
    1. 3.1. Introduction
    2. 3.2. The specificity of inter-vehicle communication
      1. 3.2.1. What is an inter-vehicle service?
      2. 3.2.2. Inter-vehicle services versus ambient computing
      3. 3.2.3. What type of stakeholders are involved?
    3. 3.3. Inter-vehicle communication
      1. 3.3.1. What constraints?
        1. 3.3.1.1. The dynamic aspect
        2. 3.3.1.2. Networks
      2. 3.3.2. Can we do without communication architecture?
        1. 3.3.2.1. The example of VESPA
        2. 3.3.2.2. The EasyRide example
        3. 3.3.2.3. The example of RouveCOM
      3. 3.3.3. Data exchange or service invocation?
    4. 3.4. Deployment and maintenance
      1. 3.4.1. What are the deployment needs?
      2. 3.4.2. Available deployment mechanisms
        1. 3.4.2.1. Platforms with dynamic services
        2. 3.4.2.2. Execution environments and available models
        3. 3.4.2.3. OSGi
        4. 3.4.2.4. Limits and alternatives
      3. 3.4.3. Application of the VESPA example
        1. 3.4.3.1. A dynamic platform for the field of transport
        2. 3.4.3.2. A dynamic inter-vehicle communication application
    5. 3.5. What kind of future can we envisage for inter-vehicle services and communication technologies?
    6. 3.6. Bibliography
  9. Chapter 4: Modeling and Control of Traffic Flow
    1. 4.1. General introduction
      1. 4.1.1. Different models of road traffic flow
      2. 4.1.2. Classification criteria for road traffic flow system models
    2. 4.2. Microscopic models
      1. 4.2.1. Car-following models
        1. 4.2.1.1. Safety distance model
        2. 4.2.1.2. Optimal speed model
        3. 4.2.1.3. Stimulus-response models
        4. 4.2.1.4. Psychological models
      2. 4.2.2. The cellular automata model
    3. 4.3. Macroscopic models
      1. 4.3.1. LWR-type first-order models
      2. 4.3.2. Superior-order or second-order models
    4. 4.4. General remarks concerning macroscopic and microscopic models
      1. 4.4.1. Links between models
      2. 4.4.2. Domains of application of macroscopic and microscopic models
      3. 4.4.3. Movement toward hybrid models
    5. 4.5. Hybrid models
      1. 4.5.1. The Magne model (MicMac)
      2. 4.5.2. The Poschinger model
      3. 4.5.3. The Bourrel model (HYSTRA)
      4. 4.5.4. The Mammar model
      5. 4.5.5. The Espié model
      6. 4.5.6. The El Hmam hybrid model
        1. 4.5.6.1. Principle of microscopic modeling based on the agent paradigm
        2. 4.5.6.2. Architecture of the microscopic model based on the agent paradigm
          1. 4.5.6.2.1. Physical elements of the network
          2. 4.5.6.2.2. Simulation agents
        3. 4.5.6.3. Hybrid model validation procedure
      7. 4.5.7. Comparison of the hybrid models presented and general remarks
    6. 4.6. Different strategies for controlling road traffic flow systems
      1. 4.6.1. Regulation of access: definition and history
      2. 4.6.2. Access regulation methods (metering systems)
        1. 4.6.2.1. Static regulation
        2. 4.6.2.2. Dynamic regulation
        3. 4.6.2.3. Fixed-cycle access regulation strategies
        4. 4.6.2.4. Adaptive access regulation strategies
      3. 4.6.3. Adaptive local access regulation strategies (responsive ramp metering control strategy)
        1. 4.6.3.1. The demand-capacity strategy
        2. 4.6.3.2. Occupancy strategy
        3. 4.6.3.3. Wotton-Jeffreys strategy
        4. 4.6.3.4. Rijkswaterstaat strategy
        5. 4.6.3.5. Predictive local access regulation algorithms: the ALINEA strategy
        6. 4.6.3.6. Comparison of the ALINEA strategy with the demand—capacity and occupancy strategy strategies
      4. 4.6.4. Adaptive strategies for coordinated access regulation (multivariable regulator strategies)
        1. 4.6.4.1. The METALINE strategy
        2. 4.6.4.2. Comparison of ALINEA and METALINE
      5. 4.6.5. Implementation of regulation via traffic lights
      6. 4.6.6. Evaluation of access control (effects of access regulation)
    7. 4.7. Conclusion
    8. 4.8. Bibliography
  10. Chapter 5: Criteria and Methods for Interactive System Evaluation: Application to a Regulation Post in the Transport Domain
    1. 5.1. Introduction
    2. 5.2. Principles and criteria of evaluation
      1. 5.2.1. Principle of evaluation
      2. 5.2.2. Classifications of evaluation methods
    3. 5.3. Methods, techniques and tools for the evaluation of interactive systems
      1. 5.3.1. User-centered approaches
        1. 5.3.1.1. Usage diagnosis
          1. 5.3.1.1.1. Usage questionnaire
          2. 5.3.1.1.2. Interview
          3. 5.3.1.1.3. Electronic monitoring
          4. 5.3.1.1.4. Eye tracking
        2. 5.3.1.2. Estimation of workload
        3. 5.3.1.3. Design tests
        4. 5.3.1.4. Conclusions about user-centered approaches and their place in the development cycle
      2. 5.3.2. Expert-based approaches
        1. 5.3.2.1. Specialist intervention
        2. 5.3.2.2. Usability inspection methods
        3. 5.3.2.3. Evaluation grids
        4. 5.3.2.4. Conclusions on expert-based approaches and their place in the development cycle
      3. 5.3.3. Analytical approaches
        1. 5.3.3.1. Formal predictive models
          1. 5.3.3.1.1. Use of task models as evaluation supports
          2. 5.3.3.1.2. Use of linguistic models as evaluation supports
        2. 5.3.3.2. Formal (quality) HMI models
        3. 5.3.3.3. Conclusions about analytical approaches and their place in the development cycle
      4. 5.3.4. Synthesis of evaluation methods, techniques and tools
    4. 5.4. Toward automated or semi-automated evaluation assistance tools
      1. 5.4.1. Tools utilizing ergonomic guidelines
      2. 5.4.2. Tools for the collection of interaction data to support the evaluation
    5. 5.5. Proposal of a generic and configurable environment to aid in the evaluation of agent-based interactive systems: EISEval
      1. 5.5.1. Motivation
      2. 5.5.2. Principles of the proposed EISEval evaluation environment
      3. 5.5.3. Structure of the environment proposed
    6. 5.6. Context of operation of the proposed evaluation environment
      1. 5.6.1. SART project
      2. 5.6.2. The IAS agent-based interactive system
        1. 5.6.2.1. State of traffic interface agent
        2. 5.6.2.2. State of a line interface agent
        3. 5.6.2.3. Station interface agent
        4. 5.6.2.4. Vehicle interface agent
        5. 5.6.2.5. Global view interface agent
        6. 5.6.2.6. Message interface agent
      3. 5.6.3. Application of the proposed EISEval environment to evaluate IAS
        1. 5.6.3.1. Preparation of evaluation
        2. 5.6.3.2. Experiment scenario
        3. 5.6.3.3. Approach for the evaluation of an interactive system using EISEval
        4. 5.6.3.4. Results of evaluation of the IAS based on module 6 criteria
          1. 5.6.3.4.1. Readability criterion
          2. 5.6.3.4.2. Criterion: protection against errors
    7. 5.7. Conclusion
    8. 5.8. Bibliography
  11. List of Authors
  12. Index