City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.

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The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

Computer and Information Science ◽

10.5539/cis.v11n3p57 ◽

2018 ◽

Vol 11 (3) ◽

pp. 57

Author(s):

Xiao-Yan Cao ◽

Bing-Qian Liu ◽

Bao-Ru Pan ◽

Yuan-Biao Zhang

Keyword(s):

Traffic Congestion ◽

Large Scale ◽

Gated Communities ◽

Urban Traffic ◽

Average Delay ◽

Traffic Demand ◽

Car Following ◽

Car Following Model ◽

Urbanization In China ◽

The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

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Sum Rate of Multiuser Large-Scale MIMO in the Presence of Antenna Correlation and Mutual Coupling

Wireless Communications and Mobile Computing ◽

10.1155/2019/7985414 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7

Author(s):

Yusheng Li ◽

Kang An ◽

Tao Liang ◽

Weixin Lu

Keyword(s):

System Performance ◽

Mutual Coupling ◽

Large Scale ◽

Mimo System ◽

Base Station ◽

Closed Form Expression ◽

Channel State ◽

Antenna Correlation ◽

Sum Rate ◽

The Impact

A multiuser large-scale MIMO system with antenna correlation and mutual coupling is investigated in this paper. Based on the maximum signal-to-interference-plus-noise ratio (SINR) criteria, the optimal beamforming (BF) vector at the base station (BS) for each user is first obtained using statistical channel state information (CSI). Then, a closed-form expression for the achievable sum rate is derived in terms of a finite number of generalized Meijer-G functions, which is applicable to an arbitrary number of array elements and/or users, and provides an efficient means of evaluating the system performance. Finally, numerical results are provided to confirm the validity of the theoretical analysis and show the impact of various channel parameters on the system performance.

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RSU LOCALIZATION MODEL AND SIMULATION OPTIMIZATION FOR VII NETWORK

Transport ◽

10.3846/16484142.2011.638024 ◽

2012 ◽

Vol 26 (4) ◽

pp. 394-402 ◽

Cited By ~ 4

Author(s):

Jian Sun ◽

Yuwei Yang

Keyword(s):

Penetration Rate ◽

Traffic Monitoring ◽

Simulation Software ◽

Traffic Information ◽

Market Penetration ◽

Test Bed ◽

Evaluation Measures ◽

Localization Model ◽

Component Object ◽

The Impact

While facing the needs for Vehicle Infrastructure Integration (VII) applications in traffic management, the paper deals with the problem of locating Road Side Units (RSU) for VII deployment. After analyzing the difference between traditional problems of locating traffic information detector and the problem of RSU location, a significance ranking model for RSU localization and three kinds of Significance Degree (SD) computing strategies are put forward. A VII simulation environment for the purpose of RSU localization optimization within VISSIM microscopic traffic simulation software is established developing add-on functions using VISSIM's Component Object Model (COM). A VII test bed of the Olympic Park network in Beijing is taken as an example to evaluate the performance of RSU localization model. The results of simulation experiments indicate that the mixed SD strategy considering both speed and route monitoring is superior to the other two SD strategies. Then, the impact of RSU number and OBE market penetration rate on the evaluation measures of traffic monitoring are studied with reference to the proposed mixed SD strategy. In this case, the evaluation measures of optimized RSU configurations generated by the ranking algorithm are always better than those of random RSU configurations. In addition, the benefits of optimized RSU configurations increase along with RSU number and market penetration rate while the benefits of random RSU configurations are more fluctuant.

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The Impact of Coil Position and Number on Wireless System Performance for Electric Vehicle Recharging

Sensors ◽

10.3390/s21134343 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4343

Author(s):

Naoui Mohamed ◽

Flah Aymen ◽

Zaafouri Issam ◽

Mohit Bajaj ◽

Sherif S. M. Ghoneim ◽

...

Keyword(s):

System Performance ◽

Mutual Inductance ◽

Transportation Systems ◽

Electrical Machine ◽

Wireless System ◽

Size Number ◽

External Conditions ◽

The Impact ◽

The Relationship ◽

The Ideal

Recently, most transportation systems have used an integrated electrical machine in their traction scheme, resulting in a hybrid electrified vehicle. As a result, an energy source is required to provide the necessary electric power to this traction portion. However, this cannot be efficient without a reliable recharging method and a practical solution. This study discusses the wireless recharge solutions and tests the system’s effectiveness under various external and internal conditions. Moreover, the Maxwell tool is used in this research to provide a complete examination of the coils’ position, size, number, and magnetic flux evolution when the coils are translated. In addition, the mutual inductance for each of these positions is computed to determine the ideal conditions for employing the wireless recharge tool for every charging application. A thorough mathematical analysis is also presented, and the findings clearly demonstrate the relationship between the magnet flux and the various external conditions employed in this investigation.

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INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications

Sensors ◽

10.3390/s21062127 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2127

Author(s):

Mohamed M. G. Farag ◽

Hesham A. Rakha ◽

Emadeldin A. Mazied ◽

Jayanthi Rao

Keyword(s):

Los Angeles ◽

Real Time ◽

Large Scale ◽

Transportation Systems ◽

High Fidelity ◽

Communication Model ◽

Modeling Framework ◽

Modeling Tools ◽

Modeling Tool ◽

Traffic Demand

The transportation system has evolved into a complex cyber-physical system with the introduction of wireless communication and the emergence of connected travelers and connected automated vehicles. Such applications create an urgent need to develop high-fidelity transportation modeling tools that capture the mutual interaction of the communication and transportation systems. This paper addresses this need by developing a high-fidelity, large-scale dynamic and integrated traffic and direct cellullar vehicle-to-vehicle and vehicle-to-infrastructure (collectively known as V2X) modeling tool. The unique contributions of this work are (1) we developed a scalable implementation of the analytical communication model that captures packet movement at the millisecond level; (2) we coupled the communication and traffic simulation models in real-time to develop a fully integrated dynamic connected vehicle modeling tool; and (3) we developed scalable approaches that adjust the frequency of model coupling depending on the number of concurrent vehicles in the network. The proposed scalable modeling framework is demonstrated by running on the Los Angeles downtown network considering the morning peak hour traffic demand (145,000 vehicles), running faster than real-time on a regular personal computer (1.5 h to run 1.86 h of simulation time). Spatiotemporal estimates of packet delivery ratios for downtown Los Angeles are presented. This novel modeling framework provides a breakthrough in the development of urgently needed tools for large-scale testing of direct (C-V2X) enabled applications.

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Developing an Eco-Driving Application for Semi-Actuated Signalized Intersections and Modeling the Market Penetration Rates of Eco-Driving

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119839960 ◽

2019 ◽

Vol 2673 (5) ◽

pp. 466-477 ◽

Cited By ~ 1

Author(s):

Saleh R. Mousa ◽

Sherif Ishak ◽

Ragab M. Mousa ◽

Julius Codjoe

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Fuel Consumption ◽

Signalized Intersections ◽

Market Penetration ◽

Automated Vehicles ◽

Gas Emissions ◽

Traffic Demand ◽

The Impact ◽

Connected Automated Vehicles

Eco-driving is one of the most effective techniques for making the transportation sector more sustainable in relation to fuel consumption and greenhouse gas emissions. Eco-driving applications guide drivers approaching signalized intersections to optimize the fuel consumption and reduce greenhouse gas emissions. Unlike pre-timed traffic signals, developing eco-driving applications for semi-actuated signals is more challenging because of variations in cycle length as a result of fluctuations in traffic demand. This paper presents a framework for developing an eco-driving application for connected/automated vehicles passing through semi-actuated signalized intersections. The proposed algorithm takes into consideration the queue effects because of traditional and connected/automated vehicles. Results showed that the fuel consumption for vehicles controlled by the developed model was 29.2% less than for the case with no control. A sensitivity analysis for the impact of market penetration (MP) indicated that the savings in fuel consumption increase with higher MP. Furthermore, when MP is greater than 50%, the model provides appreciable savings in travel times. In addition, the estimated acceleration noise for the vehicles controlled by the algorithms was 21.9% less than for the case with no control. These reductions in fuel consumption and acceleration noise demonstrate the ability of the algorithm to provide more environmentally sustainable semi-actuated signalized intersections.

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Analyzing the Impact of Traffic Congestion Mitigation: From an Explainable Neural Network Learning Framework to Marginal Effect Analyses

Sensors ◽

10.3390/s19102254 ◽

2019 ◽

Vol 19 (10) ◽

pp. 2254 ◽

Cited By ~ 2

Author(s):

Jianping Sun ◽

Jifu Guo ◽

Xin Wu ◽

Qian Zhu ◽

Danting Wu ◽

...

Keyword(s):

Large Scale ◽

Mitigation Strategies ◽

Mobile Phone Data ◽

Marginal Effect ◽

Data Set ◽

Neural Network Learning ◽

Traffic Demand ◽

Congestion Mitigation ◽

Learning Framework ◽

The Impact

Computational graphs (CGs) have been widely utilized in numerical analysis and deep learning to represent directed forward networks of data flows between operations. This paper aims to develop an explainable learning framework that can fully integrate three major steps of decision support: Synthesis of diverse traffic data, multilayered traffic demand estimation, and marginal effect analyses for transport policies. Following the big data-driven transportation computational graph (BTCG) framework, which is an emerging framework for explainable neural networks, we map different external traffic measurements collected from household survey data, mobile phone data, floating car data, and sensor networks to multilayered demand variables in a CG. Furthermore, we extend the CG-based framework by mapping different congestion mitigation strategies to CG layers individually or in combination, allowing the marginal effects and potential migration magnitudes of the strategies to be reliably quantified. Using the TensorFlow architecture, we evaluate our framework on the Sioux Falls network and present a large-scale case study based on a subnetwork of Beijing using a data set from the metropolitan planning organization.

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Traffic Demand Forecast and Control in Large-Scale Activities

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.209-211.998 ◽

2012 ◽

Vol 209-211 ◽

pp. 998-1003

Author(s):

Liang Zhi Zhang ◽

Lei Jia ◽

Mei Xia Wang

Keyword(s):

Traffic Control ◽

Large Scale ◽

Control Measures ◽

Traffic Load ◽

Demand Forecast ◽

Traffic Demand ◽

The Road ◽

Traffic Forecasting ◽

Before And After ◽

The Impact

In order to alleviate traffic load during large-scale activities held in cities, the concepts of traffic planning is applied in this paper. To forecast traffic demand of large-scale activities, the traditional four-stage method is imposed. Traffic forecasting model is set up in simulation tool TransCAD, and then traffic loads are gained in road around large-scale activities. Based on the result of simulate, appropriate measures are taken and re-assignment is implemented. By comparing simulation results between before and after the implementation of traffic control measures, the impact of large-scale activities to the road network and effectiveness of control measures are verified in the paper.

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Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz

Electronics ◽

10.3390/electronics9020262 ◽

2020 ◽

Vol 9 (2) ◽

pp. 262 ◽

Cited By ~ 3

Author(s):

Omar A. Saraereh ◽

Ashraf Ali ◽

Imran Khan ◽

Khaled Rabie

Keyword(s):

Communication Networks ◽

Large Scale ◽

Vehicular Networks ◽

High Capacity ◽

Ergodic Capacity ◽

Vehicular Communication ◽

Interference Analysis ◽

Vehicular Communication Networks ◽

On The Road ◽

The Impact

High capacity and ultra-reliable vehicular communication are going to be important aspects of beyond 5G communication networks. However, the vehicular communication problem becomes complex at a large scale when vehicles are roaming on the road, while simultaneously communicating with each other. Moreover, at higher frequencies (like 28 GHz), the dynamics of vehicular communication completely shift towards unpredictability and low-reliability. These factors may result in high packet error and a large amount of interference, resulting in regular disruptions in communications. A thorough understanding of performance variations is the key to moving towards the next generation of vehicular networks. With this intent, this article aims to provide a comprehensive interference analysis, wherein the closed-form expressions of packet error probability (PEP) and ergodic capacity are derived. Using the expression of the PEP, diversity analysis is provided which unveils the impact of channel nonlinearities on the performance of interference-constrained vehicular networks. The insights provided here are expected to pave the way for reliable and high capacity vehicular communication networks.

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Impact of road architecture and design on performance of city-based VANETs

Open Computer Science ◽

10.1515/comp-2020-0217 ◽

2021 ◽

Vol 11 (1) ◽

pp. 423-436

Author(s):

Sourav Kumar Bhoi ◽

Sanjaya Kumar Panda ◽

Chittaranjan Mallick ◽

Kalyan Kumar Jena

Keyword(s):

Routing Protocols ◽

Intelligent Transportation Systems ◽

Ad Hoc Network ◽

Ad Hoc ◽

Transportation Systems ◽

Network Simulator ◽

Vehicular Communication ◽

High Speeds ◽

Architecture And Design ◽

The Impact

Abstract Vehicular communication is the communication between the vehicles to provide intelligent transportation systems (ITSs) services to the end users. It is the most advance and emerging wireless technology in ad hoc network. On the other hand, construction of roads has a great impact in forwarding the data to the destination. As vehicles are moving with high speeds, the architecture of roads can change the performance of routing and data forwarding in the vehicular ad hoc network (VANET). If the construction of the roads in a city area is planned with intelligent junctions, flyovers, multilane, etc., then the performance of the system increases. In this paper, we have analyzed the impact of road elements like intersections, flyovers, multilane, buildings, hills, etc., on VANET routing and find solutions for the problems related to the performance of the system. We also simulate the impact of these elements in VANET routing and analyzed the performance using OMNeT++ network simulator and SUMO traffic simulator. The performance is studied by comparing standard GSR and GPSR position-based routing protocols.

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