Disaggregate Path Flow Estimation in an Iterated Dynamic Traffic Assignment Microsimulation

Flötteröd, Gunnar; Liu, Ronghui

doi:10.1080/15472450.2013.806854

Cited by 15 publications

(6 citation statements)

References 34 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further improvement can potentially be achieved by a more comprehensive and diverse initial pool of routes. Additionally, different optimization algorithms like Cadyts [31]- [33] can be applied for a comparison of traffic flow calibration procedures. In order to increase the accuracy of the simulation, fixed-time traffic lights must be replaced by a traffic adaptive traffic light control using rule-based or data-driven techniques.…”

Section: Discussionmentioning

confidence: 99%

Automated Calibration of Traffic Demand and Traffic Lights in SUMO Using Real-World Observations

Harth¹,

Langer²,

Bogenberger

2022

SUMO Conf Proc

View full text Add to dashboard Cite

Virtual traffic environments allow for evaluations of automated driving functions as well as future mobility services. As a key component of this virtual proving ground, a traffic flow simulation is necessary to represent real-world traffic conditions. Real-world observations, such as historical traffic counts and traffic light state information, provide a basis for the representation of these conditions in the simulation. In this work, we therefore propose a scalable approach to transfer real-world data, exemplarily taken from the German city Ingolstadt, to a virtual environment for a calibration of a traffic flow simulation in SUMO. To recreate measured traffic properties such as traffic counts or traffic light programs into the simulation, the measurement sites must first be allocated in the virtual environment. For the allocation of historical real-world data, a matching procedure is applied, in order to associate real-world measurements with their corresponding locations in the virtual environment. The calibration incorporates the replication of realistic traffic light programs as well as the adjustment of simulated traffic flows. The proposed calibration procedure allows for an automated creation of a calibrated traffic flow simulation of an arbitrary road network given historical real-world observations.

show abstract

Section: Discussionmentioning

confidence: 99%

Automated Calibration of Traffic Demand and Traffic Lights in SUMO Using Real-World Observations

Harth¹,

Langer²,

Bogenberger

2022

SUMO Conf Proc

View full text Add to dashboard Cite

show abstract

“…At the upper level (1a), the decision variable (𝑋) is the vector of time-dependent OD flows, and the problem can be presented as the constrained generalized/ordinary least squares (GLS/OLS) problem. Furthermore, at the lower level (1a), the traffic assignment 𝑨(𝑿) is derived analytically (Maher et al 2001), according to simulation-based models (Flötteröd and Liu 2014;Shafiei et al 2018;Zhang et al 2021), based on machine learning as dynamically learn mapping between link flow and OD demands according to the traffic measurements data (Ou et al 2019;Krishnakumari et al 2020), or combinations of them (Osorio 2019a).…”

Section: Fig 1 General Bi-level Od Estimation Frameworkmentioning

confidence: 99%

Time-dependent estimation of origin-destination matrices using partial path data and link counts

Vahidi

Shafahi

2022

Preprint

View full text Add to dashboard Cite

The precise estimation of time-varying demand matrices using traffic data is an essential step for planning, scheduling, and evaluating advanced traffic management systems (ATMS). This paper presents an innovative method (based on the least squares approach) to deal with the inherent complexities in estimating the dynamic characteristics of changing demand flow over time and considering congestion conditions. The time-dependent Origin-Destination (OD) demand matrices of the network are estimated by exploitation of the received partial paths data from an automated vehicle identification (AVI) system, and vehicle counts data from loop detectors on a subset of the links. A traffic assignment approach based on partial paths is embedded into the measurement equations of the least squares model. For all time intervals, the relation between the variable aspects of congestion (the temporal and spatial distribution of the OD traffic flows) is established by their variance-covariance matrices. The LSQR algorithm, an iterative algorithm that is logically equivalent to the conjugate gradient method, is employed for solving the proposed least squares problem. Numerical examples performed on three different approaches (only link counts data, only partial path flows data, and both of them) show that using the variance-covariance matrices is more precise for estimating time-dependent OD matrices. The Sioux Falls network is presented to examine the solution algorithm’s effectiveness and the model’s main ideas. This paper reports the features of the discussed model based on synthetic data as proof of concept that using partial path flows significantly improves the results for solving time-dependent OD matrices estimation problems.

show abstract

“…At the same time, within-day and day to day dynamics of traffic re-routing has been considered by Bie and Lo (2010), Cantarella and Cascetta (1995), Flötteröd andLiu (2014), Liu et al (2006), Smith (1984a) and others. These papers do not involve RPAP.…”

Section: A1 Route Choice Modellingmentioning

confidence: 99%

Route choice and traffic signal control: A study of the stability and instability of a new dynamical model of route choice and traffic signal control

Liu

Smith

2015

Transportation Research Part B: Methodological

Self Cite

View full text Add to dashboard Cite

This paper presents a novel idealised dynamical model of day to day traffic re-routeing (as traffic seeks cheaper routes) and proves a stability result for this dynamical model. (The dynamical model is based on swapping flow between paired alternative segments (these were introduced by Bar Gera (2010)) rather than between routes.) It is shown that under certain conditions the dynamical system enters a given connected set of approximate equilibria in a finite number of days or steps. This proof allows for saturation flows which act as potentially active flow constraints. The dynamical system involving paired alternative segment swaps is then combined with a novel green-time-swapping rule; this rule swaps green-time toward more pressurised signal stages. It is shown that if (i) the delay formulae have a simple form and (ii) the "pressure" formula fits the special control policy P 0 (see Smith, 1979a, b), then the combined flow-swapping / green-time-swapping dynamical model also enters a given connected set of approximate consistent equilibria in a finite number of steps. Computational results confirm, in a simple network, the positive P 0 result and also show, on the other hand, that such good behaviour may not arise if the equi-saturation control policy is utilized. The dynamical models described here do not represent blocking back effects.

show abstract

Disaggregate Path Flow Estimation in an Iterated Dynamic Traffic Assignment Microsimulation

Cited by 15 publications

References 34 publications

Automated Calibration of Traffic Demand and Traffic Lights in SUMO Using Real-World Observations

Automated Calibration of Traffic Demand and Traffic Lights in SUMO Using Real-World Observations

Time-dependent estimation of origin-destination matrices using partial path data and link counts

Route choice and traffic signal control: A study of the stability and instability of a new dynamical model of route choice and traffic signal control

Contact Info

Product

Resources

About