On scalable measurement-driven modeling of traffic demand in large WLANs

2007 ◽  
Author(s):  
Merkouris Karaliopoulos ◽  
Maria Papadopouli ◽  
Elias Raftopoulos ◽  
Haipeng Shen
Keyword(s):  
Traffic Demand

Estimating Pedestrian Impact on Coordination of Urban Corridors

2019 ◽  
Vol 2673 (7) ◽  
pp. 265-280 ◽  
Author(s):  
Sharmin-E-Shams Chowdhury ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Cycle Length ◽  
Network Performance ◽  
Traffic Signals ◽  
High Fidelity ◽  
Vehicular Traffic ◽  
Traffic Demand ◽  
Advantages And Disadvantages ◽  
Street Traffic ◽  
Pedestrian Impact ◽  
Signal Operations

Pedestrian walk timings at most U.S. traffic signals are run in concurrence with relevant signal phases for vehicular traffic. This usually means that signal operations coordinated for the major street can be interrupted by a pedestrian call. Such an interruption may in practice last for a few minutes, thus causing increased delays and stops for major traffic flows. An alternative to this design is to increase the cycle length and embed pedestrian timings within the ring-barrier structure of the prevailing coordination plan. Both approaches have advantages and disadvantages. A fresh approach offered by this study is a comprehensive experimental design and holistic performance evaluation perspectives. The study examines the two abovementioned treatments of pedestrian timings for a small corridor of five intersections in Utah. The experiments have been done in a high-fidelity microsimulation environment with the Software-in-the-Loop version of the field controller (Econolite ASC/3). Findings show that either approach works well for very low traffic demands. When the traffic demand increases findings cannot be generalized as they differ for major coordinated movements versus overall network performance. While major-street traffic prefers no interruption of the coordinated operations, the overall network performance is better in the other case. This can be explained by the fact that avoiding interruptions is usually achieved at the expense of longer cycle length, which increases delay for everyone in the network.

Electric Vehicle Charger Placement Optimization in Michigan Considering Monthly Traffic Demand and Battery Performance Variations

2021 ◽  
pp. 036119812098195
Author(s):  
Fatemeh Fakhrmoosavi ◽  
MohammadReza Kavianipour ◽  
MohammadHossein (Sam) Shojaei ◽  
Ali Zockaie ◽  
Mehrnaz Ghamami ◽  
...  
Keyword(s):  
Optimal Allocation ◽  
Critical Factor ◽  
Cold Weather ◽  
Contributing Factors ◽  
Modeling Framework ◽  
Long Distance ◽  
Charging Infrastructure ◽  
Traffic Demand ◽  
Adverse Weather ◽  
Performance Variations

Limited charging infrastructure for electric vehicles (EVs) is one of the main barriers to adoption of these vehicles. In conjunction with limited battery range, the lack of charging infrastructure leads to range-anxiety, which may discourage many potential users. This problem is especially important for long-distance or intercity trips. Monthly traffic patterns and battery performance variations are two main contributing factors in defining the infrastructure needs of EV users, particularly in states with adverse weather conditions. Knowing this, the current study focuses on Michigan and its future needs to support the intercity trips of EVs across the state in two target years of 2020 and 2030, considering monthly traffic demand and battery performance variations. This study incorporates a recently developed modeling framework to suggest the optimal locations of fast EV chargers to be implemented in Michigan. Considering demand and battery performance variations is the major contribution of the current study to the proposed modeling framework by the same authors in the literature. Furthermore, many stakeholders in Michigan are engaged to estimate the input parameters. Therefore, the research study can be used by authorities as an applied model for optimal allocation of resources to place EV fast chargers. The results show that for charger placement, the reduced battery performance in cold weather is a more critical factor than the increased demand in warm seasons. To support foreseeable annual EV trips in Michigan in 2030, this study suggests 36 charging stations with 490 chargers and an investment cost of $23 million.

scholarly journals Machine Learning for Communications

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 831
Author(s):  
Vaneet Aggarwal
Keyword(s):  
Machine Learning ◽  
Augmented Reality ◽  
Video Streaming ◽  
Communication Networks ◽  
Data Analytics ◽  
Data Traffic ◽  
Traffic Demand ◽  
Performance Requirements

Due to the proliferation of applications and services that run over communication networks, ranging from video streaming and data analytics to robotics and augmented reality, tomorrow’s networks will be faced with increasing challenges resulting from the explosive growth of data traffic demand with significantly varying performance requirements [...]

scholarly journals Evaluation and Analysis of CFI Schemes with Different Length of Displaced Left-Turn Lanes with Entropy Method

2021 ◽  
Vol 13 (12) ◽  
pp. 6917
Author(s):  
Binghong Pan ◽  
Shasha Luo ◽  
Jinfeng Ying ◽  
Yang Shao ◽  
Shangru Liu ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Heavy Traffic ◽  
Efficiency Index ◽  
Entropy Method ◽  
Sustainable Transportation ◽  
Assessment Model ◽  
Left Turn ◽  
Traffic Demand ◽  
Traffic Efficiency ◽  
Multi Attribute Decision Making

As an unconventional design to alleviate the conflict between left-turn and through vehicles, Continuous Flow Intersection (CFI) has obvious advantages in improving the sustainability of roadway. So far, the design manuals and guidelines for CFI are not enough sufficient, especially for the displaced left-turn lane length of CFI. And the results of existing research studies are not operational, making it difficult to put CFI into application. To address this issue, this paper presents a methodological procedure for determination and evaluation of displaced left-turn lane length based on the entropy method considering multiple performance measures for sustainable transportation, including traffic efficiency index, environment effect index and fuel consumption. VISSIM and the surrogate safety assessment model (SSAM) were used to simulate the operational and safety performance of CFI. The multi-attribute decision-making method (MADM) based on an entropy method was adopted to determine the suitability of the CFI schemes under different traffic demand patterns. Finally, the procedure was applied to a typical congested intersection of the arterial road with heavy traffic volume and high left-turn ratio in Xi’an, China, the results showed the methodological procedure is reasonable and practical. According to the results, for the studied intersection, when the Volume-to-Capacity ratio (V/C) in the westbound and eastbound lanes is less than 0.5, the length of the displaced left-turn lanes can be selected in the range of 80 to 170 m. Otherwise, other solutions should be considered to improve the traffic efficiency. The simulation results of the case showed CFI can significantly improve the traffic efficiency. In the best case, compared with the conventional intersection, the number of vehicles increases by 13%, delay, travel time, number of stops, CO emission, and fuel consumption decrease by 41%, 29%, 25%, 17%, and 17%, respectively.

scholarly journals Emulating Software-Defined Disaggregated Optical Networks in a Containerized Framework

2021 ◽  
Vol 11 (5) ◽  
pp. 2081
Author(s):  
Francisco-Javier Moreno-Muro ◽  
Miquel Garrich ◽  
Ignacio Iglesias-Castreño ◽  
Safaa Zahir ◽  
Pablo Pavón-Mariño
Keyword(s):  
Optical Networks ◽  
Transport Infrastructure ◽  
Optical Systems ◽  
Traffic Demand ◽  
Novel Approach ◽  
Infrastructure Project ◽  
Optical Layer ◽  
Optical Domain ◽  
Control And Management ◽  
Remote Communications

Telecom operators’ infrastructure is undergoing high pressure to keep the pace with the traffic demand generated by the societal need of remote communications, bandwidth-hungry applications, and the fulfilment of 5G requirements. Software-defined networking (SDN) entered in scene decoupling the data-plane forwarding actions from the control-plane decisions, hence boosting network programmability and innovation. Optical networks are also capitalizing on SDN benefits jointly with a disaggregation trend that holds the promise of overcoming traditional vendor-locked island limitations. In this work, we present our framework for disaggregated optical networks that leverages on SDN and container-based management for a realistic emulation of deployment scenarios. Our proposal relies on Kubernetes for the containers’ control and management, while employing the NETCONF protocol for the interaction with the light-weight software entities, i.e., agents, which govern the emulated optical devices. Remarkably, our agents’ structure relies on components that offer high versatility for accommodating the wide variety of components and systems in the optical domain. We showcase our proposal with the emulation of an 18-node European topology employing Cassini-compliant optical models, i.e., a state-of-the-art optical transponder proposed in the Telecom Infrastructure Project. The combination of our versatile framework based on containerized entities, the automatic creation of agents and the optical-layer characteristics represents a novel approach suitable for operationally complex carrier-grade transport infrastructure with SDN-based disaggregated optical systems.

scholarly journals Variable Speed Limit and Ramp Metering for Mixed Traffic Flows: A Review and Open Questions

2021 ◽  
Vol 11 (6) ◽  
pp. 2574
Author(s):  
Filip Vrbanić ◽  
Edouard Ivanjko ◽  
Krešimir Kušić ◽  
Dino Čakija
Keyword(s):  
Traffic Control ◽  
Ramp Metering ◽  
Transport Infrastructure ◽  
Control Algorithms ◽  
Speed Limit ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Demand

The trend of increasing traffic demand is causing congestion on existing urban roads, including urban motorways, resulting in a decrease in Level of Service (LoS) and safety, and an increase in fuel consumption. Lack of space and non-compliance with cities’ sustainable urban plans prevent the expansion of new transport infrastructure in some urban areas. To alleviate the aforementioned problems, appropriate solutions come from the domain of Intelligent Transportation Systems by implementing traffic control services. Those services include Variable Speed Limit (VSL) and Ramp Metering (RM) for urban motorways. VSL reduces the speed of incoming vehicles to a bottleneck area, and RM limits the inflow through on-ramps. In addition, with the increasing development of Autonomous Vehicles (AVs) and Connected AVs (CAVs), new opportunities for traffic control are emerging. VSL and RM can reduce traffic congestion on urban motorways, especially so in the case of mixed traffic flows where AVs and CAVs can fully comply with the control system output. Currently, there is no existing overview of control algorithms and applications for VSL and RM in mixed traffic flows. Therefore, we present a comprehensive survey of VSL and RM control algorithms including the most recent reinforcement learning-based approaches. Best practices for mixed traffic flow control are summarized and new viewpoints and future research directions are presented, including an overview of the currently open research questions.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

Reconfigurable Transport Networks to Accommodate Much More Traffic Demand

2021 ◽  
Author(s):  
Kazuya Anazawa ◽  
Toru Mano ◽  
Takeru Inoue ◽  
Atsushi Taniguchi ◽  
Kohei Mizuno
Keyword(s):  
Transport Networks ◽  
Traffic Demand
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