Estimating network travel time reliability with network partitioning

Saedi, Ramin; Saeedmanesh, Mohammadreza; Zockaie, Ali; Saberi, Meead; Geroliminis, Nikolas; Mahmassani, Hani S.

doi:10.1016/j.trc.2020.01.013

Cited by 47 publications

(24 citation statements)

References 47 publications

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“…NFD is an important indicator of the network-wide traffic state and is used to compare the performance, stability, travel time reliability, and congestion characteristics of urban networks (25,(30)(31)(32). The NFD can be estimated using a traffic simulator, sampled observations of loop detectors, and vehicle trajectories, or by using an analytical approach (28).…”

Section: Network Fundamental Diagrammentioning

confidence: 99%

Comparison of Support Vector and Non-Linear Regression Models for Estimating Large-Scale Vehicular Emissions, Incorporating Network-Wide Fundamental Diagram for Heterogeneous Vehicles

Saedi

Verma

Zockaie

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Estimation of vehicular emissions at network level is a prominent issue in transportation planning and management of urban areas. For large networks, macroscopic emission models are preferred because of their simplicity. However, these models do not consider traffic flow dynamics that significantly affect emissions production. This study proposes a network-level emission modeling framework based on the network-wide fundamental diagram (NFD), via integrating the NFD properties with an existing microscopic emission model. The NFD and microscopic emission models are estimated using microscopic and mesoscopic traffic simulation tools at different scales for various traffic compositions. The major contribution is to consider heterogeneous vehicle types with different emission generation rates in a network-level model. This framework is applied to the large-scale network of Chicago as well as its central business district. Non-linear and support vector regression models are developed using simulated trajectory data of 13 simulated scenarios. The results show a satisfactory calibration and successful validation with acceptable deviations from the underlying microscopic emissions model regardless of the simulation tool that is used to calibrate the network-level emissions model. The microscopic traffic simulation is appropriate for smaller networks, while mesoscopic traffic simulation is a proper means to calibrate models for larger networks. The proposed model is also used to demonstrate the relationship between macroscopic emissions and flow characteristics in the form of a network emissions diagram. The results of this study provide a tool for planners to analyze vehicular emissions in real time and find optimal policies to control the level of emissions in large cities.

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Section: Network Fundamental Diagrammentioning

confidence: 99%

Comparison of Support Vector and Non-Linear Regression Models for Estimating Large-Scale Vehicular Emissions, Incorporating Network-Wide Fundamental Diagram for Heterogeneous Vehicles

Saedi

Verma

Zockaie

et al. 2020

Transportation Research Record: Journal of the Transportation R

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“…The heterogeneous spatiotemporal distribution of congestion across real networks often creates hysteresis in the NFD ( 39 , 40 ). Hysteresis is a loop (complete or incomplete) in the NFD diagram that shows the degree to which the system is unstable during the unloading period.…”

Section: Mesoscopic Simulation Frameworkmentioning

confidence: 99%

Impacts of Connected and Autonomous Vehicles on Traffic Flow with Heterogeneous Drivers Spatially Distributed over Large-Scale Networks

Fakhrmoosavi

Saedi

Zockaie

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Connected and automated vehicle technologies are expected to significantly contribute in improving mobility and safety. As connected and autonomous vehicles have not been used in practice at large scale, there are still some uncertainties in relation to their applications. Therefore, researchers utilize traffic simulation tools to model the presence of these vehicles. There are several studies on the impacts of vehicle connectivity and automation at the segment level. However, only a few studies have investigated these impacts on traffic flow at the network level. Most of these studies consider a uniform distribution of connected or autonomous vehicles over the network. They also fail to consider the interactions between heterogeneous drivers, with and without connectivity, and autonomous vehicles at the network level. Therefore, this study aims to realistically observe the impacts of these emerging technologies on traffic flow at the network level by incorporating adaptive fundamental diagrams in a mesoscopic simulation tool. The adaptive fundamental diagram concept considers spatially and temporally varying distributions of different vehicle types with heterogeneous drivers. Furthermore, this study considers the intersection capacity variations and fundamental diagram adjustments for arterial links resulting from the presence of different vehicle types and driver classes. The proposed methodology is applied to a large-scale network of Chicago. The results compare network fundamental diagrams and hysteresis loop areas for different proportions of connected and autonomous vehicles. In addition to quantifying impacts of connected and autonomous vehicles, the results demonstrate the impacts of various factors associated with these vehicles on traffic flow at the network level.

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“…Thus, our definition of RNP is geared towards the structural properties of the network that shapes the flows within the network and affects operational performance [61,62]. The definition acknowledges but excludes the analysis of further notions or indicators of network performance, such as levels of service, capacity, safety, smoothness of flow, reliability, vulnerability, accessibility, resource constraints, or travel time reliability [63], that, respectively, represent the functionality of the network for particular research goals. As our analysis is restricted to network driven costs only, it is confined to a share of the total cost only.…”

Section: Fundamentals On Road Network Performance Measurementsmentioning

confidence: 99%

“…et al [78] find that declared data regarding bases might not be as accurate as inferred data, suggesting the identification of central network nodes via algorithms instead of relying on survey data to determine meaningful points of origin. Referring to Saedi et al [63] our approach does not report RNP across the complete road network but well-defined partitions.…”

Section: Fundamentals On Road Network Performance Measurementsmentioning

confidence: 99%

Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements

2020

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Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.

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Estimating network travel time reliability with network partitioning

Cited by 47 publications

References 47 publications

Comparison of Support Vector and Non-Linear Regression Models for Estimating Large-Scale Vehicular Emissions, Incorporating Network-Wide Fundamental Diagram for Heterogeneous Vehicles

Comparison of Support Vector and Non-Linear Regression Models for Estimating Large-Scale Vehicular Emissions, Incorporating Network-Wide Fundamental Diagram for Heterogeneous Vehicles

Impacts of Connected and Autonomous Vehicles on Traffic Flow with Heterogeneous Drivers Spatially Distributed over Large-Scale Networks

Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements

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