scholarly journals Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran

2021 ◽  
Vol 6 (3) ◽  
pp. 46
Author(s):  
Amir Masoud Rahimi ◽  
Maxim A. Dulebenets ◽  
Arash Mazaheri
Keyword(s):  
Intelligent Transportation Systems ◽  
Network Performance ◽  
Traffic Simulation ◽  
Transportation Networks ◽  
Transportation Network ◽  
Travel Speed ◽  
Transportation Systems ◽  
Mitigation Strategies ◽  
Northern Iran ◽  
Microsimulation Models

Industrialization, urban development, and population growth in the last decades caused a significant increase in congestion of transportation networks across the world. Increasing congestion of transportation networks and limitations of the traditional methods in analyzing and evaluating the congestion mitigation strategies led many transportation professionals to the use of traffic simulation techniques. Nowadays, traffic simulation is heavily used in a variety of applications, including the design of transportation facilities, traffic flow management, and intelligent transportation systems. The literature review, conducted as a part of this study, shows that many different traffic simulation packages with various features have been developed to date. The present study specifically focuses on a comprehensive comparative analysis of the advanced interactive microscopic simulator for urban and non-urban networks (AIMSUN) and SimTraffic microsimulation models, which have been widely used in the literature and practice. The evaluation of microsimulation models is performed for the four roadway sections with different functional classifications, which are located in the northern part of Iran. The SimTraffic and AIMSUN microsimulation models are compared in terms of the major transportation network performance indicators. The results from the conducted analysis indicate that AIMSUN returned smaller errors for the vehicle flow, travel speed, and total travel distance. On the other hand, SimTraffic provided more accurate values of the travel time. Both microsimulation models were able to effectively identify traffic bottlenecks. Findings from this study will be useful for the researchers and practitioners, who heavily rely on microsimulation models in transportation planning.

scholarly journals Deep Autoencoder Neural Networks for Short-Term Traffic Congestion Prediction of Transportation Networks

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2229 ◽  
Author(s):  
Sen Zhang ◽  
Yong Yao ◽  
Jie Hu ◽  
Yong Zhao ◽  
Shaobo Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Transportation Systems ◽  
Neural Network Models ◽  
Computation Efficiency ◽  
Congestion Prediction

Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available online traffic service provider Washington State Department of Transportation. We then propose a deep autoencoder-based neural network model with symmetrical layers for the encoder and the decoder to learn temporal correlations of a transportation network and predicting traffic congestion. Our experimental results on the SATCS dataset show that the proposed DCPN model can efficiently and effectively learn temporal relationships of congestion levels of the transportation network for traffic congestion forecasting. Our method outperforms two other state-of-the-art neural network models in prediction performance, generalization capability, and computation efficiency.

Simplex-Based Calibration of Traffic Microsimulation Models with Intelligent Transportation Systems Data

2003 ◽  
Vol 1855 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Kyu-Ok Kim ◽  
L. R. Rilett
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
System Modeling ◽  
Intelligent Transportation ◽  
Simplex Algorithm ◽  
Transportation System ◽  
Transportation Systems ◽  
Test Bed ◽  
Morning Peak ◽  
Microsimulation Models

In recent years, microsimulation has become increasingly important in transportation system modeling. A potential issue is whether these models adequately represent reality and whether enough data exist with which to calibrate these models. There has been rapid deployment of intelligent transportation system (ITS) technologies in most urban areas of North America in the last 10 years. While ITSs are developed primarily for real-time traffic operations, the data are typically archived and available for traffic microsimulation calibration. A methodology, based on the sequential simplex algorithm, that uses ITS data to calibrate microsimulation models is presented. The test bed is a 23-km section of Interstate 10 in Houston, Texas. Two microsimulation models, CORSIM and TRANSIMS, were calibrated for two different demand matrices and three periods (morning peak, evening peak, and off-peak). It was found for the morning peak that the simplex algorithm had better results then either the default values or a simple, manual calibration. As the level of congestion decreased, the effectiveness of the simplex approach also decreased, as compared with standard techniques.

Calibration of Microsimulation Models Using Nonparametric Statistical Techniques

2005 ◽  
Vol 1935 (1) ◽  
pp. 111-119 ◽  
Author(s):  
Seung-Jun Kim ◽  
Wonho Kim ◽  
L. R. Rilett
Keyword(s):  
Travel Time ◽  
Intelligent Transportation Systems ◽  
Absolute Error ◽  
Calibration Procedure ◽  
Transportation Systems ◽  
Related Data ◽  
Kolmogorov Smirnov ◽  
The Mean ◽  
Simulation Results ◽  
Microsimulation Models

The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank–sum test, the Moses test and the Kolmogorov–Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel times are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.

Simulation of an Arterial Incident Environment with Probe Reporting Capability

1998 ◽  
Vol 1644 (1) ◽  
pp. 116-123 ◽  
Author(s):  
Natacha Thomas ◽  
Bader Hafeez
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Simulation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Incident Detection ◽  
Travel Times ◽  
Control Center ◽  
Microscopic Traffic Simulation ◽  
Arterial Streets ◽  
Detection Systems

Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.

scholarly journals Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3371 ◽  
Author(s):  
Shafqat Jawad ◽  
Junyong Liu
Keyword(s):  
Power Distribution ◽  
Traffic Congestion ◽  
Large Scale ◽  
Network Performance ◽  
Transportation Networks ◽  
Transportation Systems ◽  
Survey Analysis ◽  
Power Networks ◽  
Interdependent Network ◽  
Electrical Vehicle

The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across charging service, transportation, and power networks. However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion, charging loads on the power grid, and high costs. Therefore, this article presents comparative survey analytics of large-scale EV integration’s impact on charging service network scheduling, transportation networks, and power networks. Moreover, price mechanism strategies to determine the charging fares, minimize investment profits, diminish traffic congestion, and reduce power distribution constraints under the influence of various factors were carried out. Additionally, the survey analysis stipulates the interdependent network performance index, ascertaining travel distance, route selection, long-term and short-term planning, and different infrastructure strategies. Finally, the limitations of the proposed study, potential research trends, and critical technologies are demonstrated for future inquiries.

scholarly journals Analysis of Transportation Network Vulnerability and Resilience within an Urban Agglomeration: Case Study of the Greater Bay Area, China

2020 ◽  
Vol 12 (18) ◽  
pp. 7410
Author(s):  
Mingyu Chen ◽  
Huapu Lu
Keyword(s):  
Natural Hazards ◽  
Network Performance ◽  
Simulation Analysis ◽  
Transportation Networks ◽  
Transportation Network ◽  
Urban Agglomeration ◽  
Complex Network Theory ◽  
Bay Area ◽  
Targeted Attacks

Recently, urban agglomerations have become the main platform of China’s economic development. As one of those, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has an important strategic position in national blueprints. Its amazing achievement is inseparable from reliable and resilient transportation networks. With the aim of improving the sustainability of the GBA, this paper presents a novel view of vulnerability and resilience of integrated transportation networks within an urban agglomeration. According to complex network theory, the integrated transportation network model of the GBA was established. Various scenarios were considered to improve the overall level of defensive ability, including random failures, targeted attacks and natural hazards. Vulnerability and resilience assessment models were developed to investigate the influences on the whole network. Finally, a simulation analysis was conducted on the GBA to examine the variations in network performance when faced with different attack scenarios. The results indicate that the transportation network of the GBA is more vulnerable and has less resilience to targeted attacks, while natural hazards had little influence on the performance, to a certain extent. Moreover, the betweenness recovery strategy seemed to be the best choice for every attack scenario.

scholarly journals Bi-Level Optimization as a Tool for Implementation of Intelligent Transportation Systems

2017 ◽  
Vol 17 (2) ◽  
pp. 97-105 ◽  
Author(s):  
Krasimira Stoilova ◽  
Todor Stoilov ◽  
Vladimir Ivanov
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Transportation Network ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Formal Description ◽  
Traffic Flows ◽  
Level Control ◽  
Traffic Lights ◽  
Level Problem

Abstract The Intelligent Transportation System (ITS) is used as a term for integrating requirements and functionalities towards transportation systems, which in urban environment raises complex exploitation and control problems. Important part of the ITS is the control which has to be applied for traffic flows. The control processes are strongly linked with requirements and targets for optimization of the transportation behavior. The paper applies new optimization formal description of control by bi-level optimization. Except the trivial traffic lights control, the bi-level formalization allows additional traffic characteristics to be defined like maximal/minimal values. The paper defines, solves and provides numerical simulations for minimization of the vehicle queues in front of the traffic lights. Such bi-level optimization problem is applied simultaneously for maximization the traffic flows on arterial and important directions of the urban transportation network. The formal description of the bi-level problem is provided. The results of the bi-level control have been compared with the cases of single optimization of the vehicles queues. The simulation results prove that the bi-level problem gives benefits satisfying an additional goal, which improves additional characteristic of the transport behavior. The bi-level optimization formalism can be used as a tool for implementation of integration of ITS control policies.

Microscopic simulation of lane changing behaviour at freeway weaving sections

1999 ◽  
Vol 26 (6) ◽  
pp. 840-851 ◽  
Author(s):  
A F Al-Kaisy ◽  
J A Stewart ◽  
M Van Aerde
Keyword(s):  
Simulation Model ◽  
Empirical Data ◽  
Intelligent Transportation Systems ◽  
Traffic Simulation ◽  
Essential Element ◽  
Simulation Models ◽  
Transportation Systems ◽  
Microscopic Simulation ◽  
Lane Changing ◽  
Microscopic Traffic Simulation

Microscopic traffic simulation models are being increasingly used to evaluate Intelligent Transportation Systems (ITS) strategies and to complement empirical data in developing new analytical procedures and methodologies. Lane changing rules are an essential element of any microscopic traffic simulation model. While most of these rules are based on theories and hypotheses, to date no attempt has been made to investigate the consistency of lane changing behaviour from microscopic simulation with empirical observations. The research presented in this paper examined this consistency at freeway weaving areas using empirical data. These data were collected in the late 1980s at several major freeway weaving sections in the State of California. The microscopic traffic simulation model INTEGRATION was used to perform simulation experiments in this research. Vehicle distributions, both total and by type of movement, were used as measures to investigate the lane changing activity that took place at these freeway areas. This examination revealed significant agreement between patterns of lane changing behaviour as observed in the field and as reproduced by microscopic simulation. Most quantitative discrepancies were shown to be a function of user-specified input data or due to some inherent limitations in the empirical data.Key words: simulation, lane changing, weaving, freeways.

scholarly journals Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System

2020 ◽  
Vol 12 (18) ◽  
pp. 7297 ◽  
Author(s):  
Chansoo Kim ◽  
Segun Goh ◽  
Myeong Seon Choi ◽  
Keumsook Lee ◽  
M. Y. Choi
Keyword(s):  
Gini Coefficient ◽  
City Planning ◽  
Transportation Networks ◽  
Transportation Network ◽  
Growth Dynamics ◽  
Transportation Systems ◽  
The Gini Coefficient ◽  
Bus Stops ◽  
Bus System ◽  
Bus Transportation

Bus transportation networks are characteristically different from other mass transportation systems such as airline or subway networks, and thus the usual approach may not work properly. In this paper, to analyze the bus transportation network, we employ the Gini coefficient, which measures the disparity of weights of bus stops. Applied to the Seoul bus system specifically, the Gini coefficient allows us to classify nodes in the bus network into two distinct types: hub and peripheral nodes. We elucidate the structural properties of the two types in the years 2011 and 2013, and probe the evolution of each type over the two years. It is revealed that the hub type evolves according to the controlled growth process while the peripheral one, displaying a number of new constructions as well as sudden closings of bus stops, is not described by growth dynamics. The Gini coefficient thus provides a key mathematical criterion of decomposing the transportation network into a growing one and the other. It would also help policymakers to deal with the complexity of urban mobility and make more sustainable city planning.

On Modeling and Verification of Agent-Based Traffic Simulation Properties in Alloy

2012 ◽  
Vol 4 (4) ◽  
pp. 38-60 ◽  
Author(s):  
Junia Valente ◽  
Frederico Araujo ◽  
Rym Z. Wenkstern
Keyword(s):  
Intelligent Transportation Systems ◽  
Large Scale ◽  
Traffic Simulation ◽  
Simulation Models ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Agent Based ◽  
Traffic Models ◽  
First Order ◽  
New Generation

The advances in Intelligent Transportation Systems (ITS) call for a new generation of traffic simulation models that support connectivity and collaboration among simulated vehicles and traffic infrastructure. In this paper we introduce MATISSE, a complex, large scale agent-based framework for the modeling and simulation of ITS and discuss how Alloy, a modeling language based on set theory and first order logic, was used to specify, verify, and analyze MATISSE’s traffic models.

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