DYNAMIC TRAFFIC FLOW
MODELLING
AND CONTROL
TABLE OF CONTENTS
1. INTRODUCTION
1.1 Some Basic Notions
2. TRAFFIC FLOW MODELING
2.1 Microscopic Models
(Car-following equation; Stability of a string of vehicles; Lane changing models; Microscopic simulation tools)
2.2 Macroscopic Models
(Definitions; Speed-flow relationship and Fundamental Diagram; Conservation equation; Kinematic waves and shock waves; Drivers’ anticipation; Second-order models; Model limitations; Modelling of on-ramp flow; Modelling of incidents; Testing control strategies via simulation; Fuel consumption models)
2.3 Model Validation
(Basic validation procedure; Case studies)
2.4 Critical Discussion
(General remarks on modelling; Qualitative and quantitative model features; Discretisation; Comparative evaluation; Future research needs; Macroscopic versus microscopic modelling)
3. MODELING OF TRAFFIC NETWORKS
3.1 Fixed-Routing Modeling
(Macroscopic node interfaces; Turning rates; Urban junction modelling; Platoon dispersion; Saturation flow)
3.2 Traffic Assignment: Basic Notions
(User and system optimality; Braess paradox; Stochastic traffic assignment; Day-to-day dynamics; Limitations)
3.3 Dynamic Traffic Assignment
(Time-dependent travel times; Microscopic, mesoscopic, and macroscopic dynamic traffic assignment; Splitting rates; Instantaneous and experienced travel time; Feedback and iterative algorithms)
3.4 Dynamic Network Models
(METANET/METACOR, CONTRAM/MCONTRM, INTEGRATION, DYNAMIT)
4. MEASUREMENTS AND ESTIMATION
4.1 Measurement Devices and Data Processing
(Loop detectors; Traffic occupancy; Space mean speed and time mean speed; Data processing for single and multiple loops; Ultrasonic detectors; Video sensors; Video image processing; Average travel time; Floating car surveys)
4.2 Estimation of Traffic Variables
(State estimation for a single section; State estimation for multisection freeway links; Extended Kalman Filter application)
4.3 Automatic Incident Detection
(Definitions, context, and impact; Performance criteria; Loop-based AID; Classification of methods; California algorithm; Exponential Smoothing; Neural Networks; Optimal calibration; The DAISI tool for AID; Video sensor based AID)
4.4 Origin-Destination Matrix Estimation
(Problem statement; Static O-D estimation; Dynamic O-D estimation; Kalman Filter application)
5. FREEWAY TRAFFIC CONTROL
5.1 Introduction
(Control measures; Basic problems)
5.2 Ramp Metering
(Why ramp metering; Implementation issues; Fixed-time ramp metering using Linear and Quadratic Programming; Local ramp metering strategies; ALINEA; Coordinated feedback ramp metering using LQ-control; METALINE; Simulation results; Field results from Paris, Amsterdam, Glasgow; Corridor impact of ramp metering; Nonlinear optimal ramp metering and applications)
5.3 Lane Control
(Variable speed limitation; Warning messages; Reversable flow; Impact on traffic flow; Implementation examples)
5.4 Route Information and Guidance
(General introduction and examples; Proposed approaches; Iterative, optimal control, and feedback (P, PI, LQI) approaches; Simulation examples)
5.5 Case Studies
(The Aalborg VMS information and guidance system; The interurban Scottish highway network system of VMS for drivers information and guidance; Goals, characteristics, control strategy design, simulation tests, implementation and impact for both systems)
5.6 Integrated Freeway Network Traffic Control
(Optimal integrated freeway network control; AMOC; Simulation examples)
6. ROAD TRAFFIC CONTROL
6.1 Introduction
(Basic definitions; Stages, split, cycle, and offset; Classification of control strategies)
6.2 Isolated Intersection Control
(Fixed-time strategies; SIGSET and SIGCAP; Phase-based approach; Application examples; Real-time strategies; Vehicle-interval method; Volume-density method; MOVA)
6.3 Fixed-Time Coordinated Control
(MAXBAND: Details of problem formulation and solution, extension to networks, examples, recent extensions; MULTIBAND; TRANSYT: Problem description, model, and optimisation approach; Signal control and traffic assignment)
6.4 Coordinated Real-Time Strategies
(SCOOT, OPAC; PRODYN, COP, CRONOS; Store-and-forward based approaches: Linear Programming, Quadratic Programming, LQ-regulation; TUC)
6.5 Parking Control Systems
(Design principles and examples)
6.6 Integrated Urban-Freeway Traffic Control
(Aims; Basic methodological approaches)
6.7 A Case Study
(Glasgow implementation and field evaluation of IN-TUC)
APPENDIX A: KALMAN FILTER
A1. The Kalman Filter for Linear Systems
(Problem formulation; Filtering and one-step prediction; Recursive solution)
A2. Extended Kalman Filter
(Nonlinear problem and suboptimal solution)
APPENDIX B: LINEAR-QUADRATIC OPTIMAL CONTROL
B1. Problem Formulation
(Linearisation; Problem Formulation)B2. LQ and LQI Regulators
(LQ-regulator; Problem augmentation for LQI control)B3. The Impact of Constant Disturbances
(Constant disturbances; Steady-state error)
APPENDIX C: NONLINEAR OPTIMAL CONTROL
C1. Problem Formulation and Necessary Conditions
C2. Feasible Direction Algorithm
(Reduced and constrained gradients; Algorithmic steps; Descent directions)