Transport simulation beyond traditional approaches 1st Edition by Edward Chung, Andre Gilles Dumont ISBN 2940222290 9782940222292

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ISBN 10: 2940222290 
ISBN 13: 9782940222292
Author: Edward Chung, Andre Gilles Dumont

In recent years, the transport simulation of large road networks has become far more rapid and detailed, and many exciting developments in this field have emerged. Within this volume, the authors describe the simulation of automobile, pedestrian, and rail traffic coupled to new applications, such as the embedding of traffic simulation into driving simulators, to give a more realistic environment of driver behavior surrounding the subject vehicle. New approaches to traffic simulation are described, including the hybrid mesoscopic-microscopic model and floor-field agent-based simulation. Written by an invited panel of experts, this book addresses students, engineers, and scholars, as well as anyone who needs a state-of-the-art overview of transport simulation today.

Transport simulation beyond traditional approaches 1st Table of contents:

PART I MACROSCOPIC TO VEHICLE-EMBEDDED MICROSCOPIC SIMULATION
CHAPTER 1 THE ROLE OF MACROSCOPIC MODELING IN THE SIMULATION, SURVEILLANCE AND CONTROL OF MOTORWAY NETWORK TRAFFIC
1.1 Introduction
1.2 Macroscopic modeling of motorway network traffic
1.2.1 The non-destination-oriented model
1.2.2 The destination-oriented model
1.2.3 Model summary
1.2.4 Model validation
1.3 Dynamic traffic assignment (DTA) and route guidance (RG)
1.3.1 Feedback strategies
1.3.2 Iterative strategies
1.4 Motorway network traffic surveillance
1.5 Optimal control of motorway traffic
1.5.1 Ramp metering
1.5.2 Route guidance
1.5.3 Integrated control
1.6 Conclusions
1.7 References
CHAPTER 2 HYBRID TRAFFIC SIMULATION MODELS: VEHICLE LOADING AT MESO-MICRO BOUNDARIES
2.1 Introduction
2.2 Hybrid modeling framework
2.3 Modeling traffic dynamics at meso-micro boundaries
2.4 Vehicle loading
2.4.1 Vehicle loading in existing microscopic models
2.4.2 Proposed loading method
2.5 Case study
2.6 Conclusions
2.7 References
CHAPTER 3 SIMULATION OF VEHICLES IN A DRIVING SIMULATOR USING MICROSCOPIC TRAFFIC SIMULATION
3.1 Introduction
3.2 The simulation model
3.2.1 The moving window
3.2.2 Generation of new vehicles
3.2.3 Sub-models for driving behavior and vehicle movement
3.2.4 The candidate areas
3.3 Validation
3.3.1 Overtaking rates
3.3.2 User evaluation
3.4 Concluding remarks and future research
3.5 Acknowledgments
3.6 References
PART II LANE CHANGING
CHAPTER 4 INTEGRATED LANE-CHANGING MODELS
4.1 Introduction
4.2 Methodology
4.3 Integration of MLC and DLC
4.4 Explicit target lane choice
4.5 Cooperative and forced gap acceptance
4.6 Accounting for heterogeneity
4.7 Conclusions
4.8 Acknowledgments
4.9 References
CHAPTER 5 TRAFFIC SIMULATION OF A RURAL 2 + 1 HIGHWAY IN HOKKAIDO
5.1 Introduction
5.2 Study Sites
5.2.1 Outline of the field survey on National Highway 38 in Shiranuka
5.2.2 Results of the field survey on National Highway 38 in Shiranuka
5.3 SIM-R Traffic Micro-simulation Program
5.3.1 Simulation outline
5.3.2 Basic model for vehicle behaviors
5.4 Model of Lane-changing Behavior on a Rural 2 + 1 Highway
5.4.1 Changing from the main lane to the left-hand auxiliary lane
5.4.2 Re-entering the main lane from the left-hand auxiliary lane
5.5 Simulation Run
5.5.1 Simulation requirements
5.5.2 Simulation results
5.6 Discussion and Conclusions
5.6.1 Field survey results for National Highway 38 in Shiranuka
5.6.2 Lane-changing behavior model of rural 2 + 1 highways
5.6.3 Calibration of parameters of the SIM-R traffic micro-simulation for the lane-changing behavior
5.7 Acknowledgments
5.8 References
CHAPTER 6 MECHANICAL RESTRICTION VS. HUMAN OVERREACTION: THE MODELING OF SYNCHRONIZED TWO-LANE TRAFFIC
6.1 Introduction
6.2 Model definition of the single lane model
6.3 Stability of the model
6.4 Two-lane traffic
6.5 Two-lane model
6.6 Results
6.7 Summary and outlook
6.8 References
PART III PEOPLE-CENTERED AND RAIL SIMULATION
CHAPTER 7 PEDESTRIAN SIMULATION TAKING INTO ACCOUNT STOCHASTIC ROUTE CHOICE AND MULTIDIRECTIONAL FLOW
7.1 Introduction
7.2 Framework of an integrated dynamic pedestrian route choice and flow model
7.3 Network-based route choice model
7.3.1 Network structure for pedestrians
7.3.2 Route generation and route choice
7.4 Path choice model
7.5 Flow propagation model
7.5.1 Cell transmission model
7.5.2 Modification of CTM
7.6. Application to simple case studies
7.6.1 Test for flow propagation model
7.6.2 Network test
7.7 Conclusions
7.8 Acknowledgements
7.9 References
CHAPTER 8 F.A.S.T. – FLOOR FIELD AND AGENT BASED SIMULATION TOOL
8.1 Introduction
8.2 A model of pedestrian motion
8.3 Evacuation exercise in a primary school
8.3.1 Results
8.3.2 Comparison to simulation results
8.4 Summary
8.5 Appendix A: Equations
8.6 Acknowledgments
8.7 References
CHAPTER 9 INCORPORATING PATTERN-MATCHING INTO DATA-ORIENTED ACTIVITY SIMULATION USING PROBE PERSON SYSTEMS
9.1 Background and objectives of study
9.2 Preprocessing of location data
9.2.1 Data processing
9.2.2 Node index and data cube storage
9.3 Pattern-matching method for location data
9.3.1 Dot-matrix method
9.3.2 Scoring model method
9.3.3 Multidimensional scale alignment method
9.4 Case study
9.5 Simulation study
9.6 Conclusion
9.7 References
CHAPTER 10 SIMULATION OF URBAN RAIL OPERATIONS: MODELS AND CALIBRATION METHODOLOGY
10.1 Introduction
10.2 The simulation model
10.3 Calibration methodology
10.4 Case study
10.5 Conclusions
10.6 Acknowledgments
10.7 References
PART IV SIMULATION APPLICATION
CHAPTER 11 TRAFFIC SIMULATION FOR AN EXPRESSWAY TOLL PLAZA BASED ON SUCCESSIVE VEHICLE TRACKING DATA
11.1 Introduction
11.2 Massive tracking of vehicle trajectories
11.2.1 Video survey and tracking
11.2.2 Estimated trajectories
11.2.3 Speed and acceleration
11.2.4 Headway and capacity
11.3 Modeling of traffic flow in toll plaza
11.3.1 Flow modeling
11.3.2 Lane choice behavior in the toll plaza
11.3.3 Basic structure of lane choice model
11.3.4 Split-side choice model and its calibration
11.3.5 Target gate choice model and its calibration
11.3.6 Lane change planning model
11.4 Validation and Case Studies
11.4.1 Reproducibility of lane choice behavior
11.4.2 Validation of speed
11.4.3 Count of ‘near-miss’ opportunities
11.5 Case Studies
11.5.1 Case-80-1
11.5.2 Case-80-2
11.5.3 Case-80-3
11.5.4 Summary of the case studies
11.6 Conclusions
11.7 References
CHAPTER 12 TIME-DEPENDENT ORIGIN-DESTINATION ESTIMATION WITHOUT ASSIGNMENT MATRICES
12.1 Introduction
12.2 Methodology
12.3 Case study I: Synthetic network
12.4 Case study II: Los angeles, california
12.5 Conclusion
12.6 Acknowledgement
12.7 References

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