01099230

Component

https://doi.org/10.3141/2088-20

http://scholar.google.com...baut&publication_year=2008

Capturing variability within flow is an important task for traffic flow models. The linearity of the congested part of the fundamental diagram induces a linear speed–spacing relationship at an individual level, characterized by two parameters. This study assumes that most intervehicle variability can be accounted for by estimating these two parameters for each vehicle. Two methods are presented to quantify individual linear speed–spacing relationships. The first method is based on data: it estimates the speed–spacing relationship by fitting the experimental speed–spacing scatter plot with a straight line. The second method is based on simulation: it computes the optimum parameters so that the simulated trajectories obtained by Newell’s car-following algorithm reproduce as closely as possible the experimental vehicle’s trajectories. Both proposed methods are implemented on the Next Generation Simulation trajectory data set recorded on I-80. The individual parameters for the speed–spacing relationship are quantified, and their distributions are specified. The need to distinguish driver behavior on a lane-by-lane basis is discussed. The results tend to prove that taking into account individual variability between drivers can improve the accuracy of simulated trajectories.

01121596

English

pp 188-197

2008

Transportation Research Record: Journal of the Transportation Research Board

9780309126038

Print

Figures (8) ; References (20) ; Tables (2)

Behavior; Car following; Drivers; Operating speed; Traffic characteristics; Traffic flow; Traffic speed; Vehicle spacing; Vehicle trajectories

Next Generation Simulation program

Car following models; Speed spacing relationships

Highways; Operations and Traffic Management; I71: Traffic Theory

TRIS, TRB, ATRI

Jan 29 2008 3:55PM

• Asymptotic Stability and Vehicle Safety in Dynamic Car-Following Platoon
• Calibrating Car-Following Models by Using Trajectory Data: Methodological Study
• Comparison of Simulation-Based and Model-Based Calibrations of Traffic-Flow Microsimulation Models
• Comparisons of Speed–Spacing Relations Under General Car Following Versus Lane Changing
• Desired Speed Distributions on Two-Lane Highways Under Various Conditions
• Empirical Measurement of Freeway Oscillation Characteristics: An International Comparison
• Empirical Study of Behavioral Theory of Traffic Flow: Analysis of Recurrent Bottleneck
• Estimating Acceleration and Lane-Changing Dynamics from Next Generation Simulation Trajectory Data
• Evaluation of Corridor Traffic Management and Planning Strategies That Use Microsimulation: A Case Study
• FASTLANE: New Multiclass First-Order Traffic Flow Model
• From Existing Accident-Free Car-Following Models to Colliding Vehicles: Exploration and Assessment
• Lane Selection Model for Urban Intersections
• Macroscopic Modeling Framework Unifying Kinematic Wave Modeling and Three-Phase Traffic Theory
• Microsimulation Calibration Using Speed–Flow Relationships
• Modeling Driver Behavior as Sequential Risk-Taking Task
• New Behavioral Model for Microscopic Freeway Traffic-Flow Simulation
• On-Ramp Metering Based on Three-Phase Traffic Theory Downstream Off-Ramp and Upstream On-Ramp Bottlenecks
• Oversaturated Freeway Flow Algorithm for Use in Next Generation Simulation
• The Less-Than-Perfect Driver: A Model of Collision-Inclusive Car-Following Behavior
• Use of Microsimulation to Model Day-to-Day Variability of Intersection Performance
• Validity of Trajectory-Based Calibration Approach of Car-Following Models in Presence of Measurement Errors
• What Do Different Traffic Flow Models Mean for System-Optimal Dynamic Traffic Assignment in a Many-to-One Network?