Analysis of LWR model with fundamental diagram subject to uncertainties

2012 ◽  
Vol 8 (6) ◽  
pp. 387-405 ◽  
Author(s):  
Jia Li ◽  
Qian-Yong Chen ◽  
Haizhong Wang ◽  
Daiheng Ni
Keyword(s):  
Fundamental Diagram ◽  
Lwr Model

Field Theory for Some Traffic Phenomena and Fundamental Diagram

2021 ◽  
pp. 036119812110064
Author(s):  
Daiheng Ni
Keyword(s):  
Field Theory ◽  
Traffic Flow ◽  
Causal Effect ◽  
Microscopic Approach ◽  
Fundamental Diagram ◽  
Longitudinal Control ◽  
Effect Analysis ◽  
Vehicle Trajectories ◽  
Vehicle Motion ◽  
Cross Reference

A fundamental diagram consists of a scatter of traffic flow data sampled at a specific location and aggregated from vehicle trajectories. These trajectories, if presented equivalently, constitute a microscopic version of the (conventional) fundamental diagram. The cross-reference between vehicle trajectories and the microscopic fundamental diagram provides details of vehicle motion dynamics which allow causal-effect analysis on some traffic phenomena and further reveal the microscopic basis of the conventional fundamental diagram. This observation inspires theoretical modeling by a microscopic approach to address traffic phenomena and the conventional fundamental diagram. Derived from the field theory of traffic flow, the longitudinal control model is capable of serving the purpose without the modifications or exceptions used by other approaches.

scholarly journals A Three-Phase Fundamental Diagram from Three-Dimensional Traffic Data

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 17
Author(s):  
Maria Laura Delle Delle Monache ◽  
Karen Chi ◽  
Yong Chen ◽  
Paola Goatin ◽  
Ke Han ◽  
...  
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Traffic Data ◽  
Fundamental Diagram ◽  
Model Based Clustering ◽  
Three Phase ◽  
Characterization Of Solutions ◽  
Two Phases

This paper uses empirical traffic data collected from three locations in Europe and the US to reveal a three-phase fundamental diagram with two phases located in the uncongested regime. Model-based clustering, hypothesis testing and regression analyses are applied to the speed–flow–occupancy relationship represented in the three-dimensional space to rigorously validate the three phases and identify their gaps. The finding is consistent across the aforementioned different geographical locations. Accordingly, we propose a three-phase macroscopic traffic flow model and a characterization of solutions to the Riemann problems. This work identifies critical structures in the fundamental diagram that are typically ignored in first- and higher-order models and could significantly impact travel time estimation on highways.

scholarly journals A Cellular Automaton Traffic Flow Model with Advanced Decelerations

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yingdong Liu
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Flow Model ◽  
Stable State ◽  
Practical Significance ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
Short Time ◽  
Vehicle Deceleration ◽  
Real Traffic

A one-dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta-stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.

OPTIMAL VELOCITY MODEL WITH RELATIVE VELOCITY

2006 ◽  
Vol 17 (01) ◽  
pp. 65-73 ◽  
Author(s):  
SHIRO SAWADA
Keyword(s):  
Nonlinear Analysis ◽  
Relative Velocity ◽  
Velocity Model ◽  
Fundamental Diagram ◽  
Optimal Velocity ◽  
Traffic Jam ◽  
Optimal Velocity Model ◽  
Linear And Nonlinear ◽  
The Stability ◽  
Good Agreement

The optimal velocity model which depends not only on the headway but also on the relative velocity is analyzed in detail. We investigate the effect of considering the relative velocity based on the linear and nonlinear analysis of the model. The linear stability analysis shows that the improvement in the stability of the traffic flow is obtained by taking into account the relative velocity. From the nonlinear analysis, the relative velocity dependence of the propagating kink solution for traffic jam is obtained. The relation between the headway and the velocity and the fundamental diagram are examined by numerical simulation. We find that the results by the linear and nonlinear analysis of the model are in good agreement with the numerical results.

scholarly journals A Modified Cellular Automaton Model for Accounting for Traffic Behaviors during Signal Change Intervals

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Chih-Cheng Hsu ◽  
Yu-Chiun Chiou
Keyword(s):  
Microscopic Analysis ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Fundamental Diagram ◽  
Macroscopic Fundamental Diagram ◽  
Proposed Model ◽  
Signal Change ◽  
Ca Model ◽  
Speed Adjustment ◽  
Diagram Analysis

Previous cellular automata (CA) models have been developed for simulating driver behaviors in response to traffic signal control. However, driver behaviors during traffic signal change intervals, including cross/stop decision and speed adjustment, have not yet been studied. Based on this, this paper aims to propose a change interval CA model for replicating driver’s perception and response to amber light based on stopping probability and speed adjusting functions. The proposed model has been validated by exemplified and field cases. To investigate the applicability of the proposed model, macroscopic and microscopic analyses are conducted. Although the macroscopic fundamental diagram analysis reveals only a small decrease in maximum traffic flow rates with considering driver behaviors in change intervals, in the microscopic analysis, the proposed model can present reasonable vehicular trajectories and deceleration rates during slowdown process.

scholarly journals Calibration of the Fundamental Diagram Based on Loop and Probe Data

2016 ◽  
Vol 2560 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Aurélien Clairais ◽  
Aurélien Duret ◽  
Nour-Eddin El Faouzi
Keyword(s):  
Fundamental Diagram
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