Rural Intelligent Transportation System for Snow Avalanche Detection and Warning

2000 ◽  
Vol 1700 (1) ◽  
pp. 17-23
Author(s):  
Robert Rice ◽  
Rand Decker ◽  
Newel Jensen ◽  
Ralph Patterson ◽  
Stanford Singer
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Cost Effective ◽  
Warning Systems ◽  
Rural Highways ◽  
Winter Maintenance ◽  
Hazard Reduction ◽  
Maintenance Personnel ◽  
Remaining Time

The growth of winter travel on alpine roads in the western United States, a result of the demand for reliable winter access, has increased the hazard to motorists and highway maintenance personnel from snow avalanches. Configurations are presented for systems that can detect and provide, in real time, warnings to motorists and highway maintainers of roadway avalanches. These warnings include on-site traffic control signing, in-vehicle audio alarms for winter maintenance vehicles, and notifying maintenance facilities or centralized agency dispatchers. These avalanche detection and warning systems can detect an existing avalanche and use the avalanche’s remaining time of descent to initiate on-site alarms. Alternatively, real-time knowledge and notification of the onset of avalanching may be used to proactively manage the evolving hazard over an affected length or corridor of highway. These corridors can be several tens of kilometers in length and may be very remote, low-volume rural highways. As a consequence, these detection and warning systems must be cost-effective alternatives to existing avalanche hazard reduction technology. Results and experiences from the winters of 1997–1998 and 1998–1999 are presented, along with recommendations and criteria for future deployment of these automated natural hazard reduction systems for rural transportation corridors.

scholarly journals A Safety Resource Allocation Mechanism against Connection Fault for Vehicular Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Tianpeng Ye ◽  
Zhou Su ◽  
Jun Wu ◽  
Longhua Guo ◽  
Jianhua Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Probability Model ◽  
Allocation Mechanism ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Resource Allocation Mechanism

The Intelligent Transportation System (ITS) becomes an important component of the smart city toward safer roads, better traffic control, and on-demand service by utilizing and processing the information collected from sensors of vehicles and road side infrastructure. In ITS, Vehicular Cloud Computing (VCC) is a novel technology balancing the requirement of complex services and the limited capability of on-board computers. However, the behaviors of the vehicles in VCC are dynamic, random, and complex. Thus, one of the key safety issues is the frequent disconnections between the vehicle and the Vehicular Cloud (VC) when this vehicle is computing for a service. More important, the connection fault will disturb seriously the normal services of VCC and impact the safety works of the transportation. In this paper, a safety resource allocation mechanism is proposed against connection fault in VCC by using a modified workflow with prediction capability. We firstly propose the probability model for the vehicle movement which satisfies the high dynamics and real-time requirements of VCC. And then we propose a Prediction-based Reliability Maximization Algorithm (PRMA) to realize the safety resource allocation for VCC. The evaluation shows that our mechanism can improve the reliability and guarantee the real-time performance of the VCC.

Rural Intelligent Transportation System Natural-Hazard Management on Low-Volume Roads

2003 ◽  
Vol 1819 (1) ◽  
pp. 255-259
Author(s):  
Rand Decker ◽  
Robert Rice ◽  
Steve Putnam ◽  
Stanford Singer
Keyword(s):  
Natural Hazards ◽  
Traffic Control ◽  
Natural Hazard ◽  
Intelligent Transportation System ◽  
Cost Effective ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Hazard Management ◽  
Low Volume ◽  
Road Closure

The growth of winter travel on alpine roads in the western United States has increased the risk to motorists and highway maintenance personnel owing to a variety of natural hazards. Hazards include snow and ice, avalanching snow, and blowing and drifting snow. The conditions call for attendant need for incident response. A substantial number of affected routes are low-volume rural winter roads. Configurations have been developed for rural intelligent transportation system (ITS) technology that can detect hazards and provide, autonomously and in real time, warnings to and traffic control actions for motorists, highway maintainers, and incident responders for roadway natural hazards. These warnings include on-site traffic control signing and road closure gates, in-vehicle audio alarms for agency maintenance and patrol vehicles, and notification to highway agency maintenance facilities or centralized multiagency dispatchers. These actions and notifications are initiated automatically from the remote rural sites and via manual intervention from off-site personnel, well removed from the rural roadway corridor itself. About 5 years of experience have been accumulated in using these rural ITS natural-hazard reduction systems, including snow avalanche detection and warning systems on Loveland Pass, Colorado; Hoback Canyon, Wyoming; and Banner Summit, Idaho. Automated road closure gates on the Teton Pass in Idaho and Wyoming now allow for remote road closure during heavy snow events. These cost-effective ITS natural-hazard systems are highly exportable for other processes that affect rural low-volume roadways, including landslide, flooding, high surf, high winds, loss of visibility, wildlife, and other natural hazards of this type.

scholarly journals Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

2018 ◽  
Vol 7 (2.18) ◽  
pp. 7 ◽  
Author(s):  
Venkata Ramana N ◽  
Seravana Kumar P. V. M ◽  
Puvvada Nagesh
Keyword(s):  
Big Data ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Control Logic ◽  
Systematic Analysis ◽  
Real Time Traffic

Big data is a term that describes the large volume of data – both structured and unstructuredthat includes a business on a day-to-day basis including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation. 

Implications of Changing Dynamics for Metered On-Street Parking

2015 ◽  
Vol 2500 (1) ◽  
pp. 17-25
Author(s):  
Soumya S. Dey ◽  
Stephanie Dock ◽  
Evian Patterson
Keyword(s):  
Real Time ◽  
New Technology ◽  
Cost Effective ◽  
Program Outcomes ◽  
Economic Implications ◽  
Dynamic Congestion Pricing ◽  
The Cost ◽  
Maintenance Personnel ◽  
Real Time Information ◽  
The Impact

The parking industry has seen significant changes over the past decade with the infusion of new technology and smart assets. The introduction of networked meters, virtual payment methods (such as pay-by-cell and credit–debit cards at meters), and technology for real-time detection of space occupancy has resulted in better system uptime, proactive maintenance strategies, multiple payment options, real-time information on parking availability, and better use of spaces through dynamic congestion pricing. The new parking assets and payment options have implications for municipalities and vendors supporting their parking programs. Instead of a significant portion of revenue from coins, virtual transactions account for a predominant share of the parking revenue stream. Focusing on Washington, D.C., as a case study, this paper discusses the economic implications of the changes in the context of overall parking revenue and the cost of different revenue streams for parking. The paper also discusses the impact of these changes on program management (such as maintenance, personnel, and contracting models) and program outcomes (such as customer satisfaction and continued innovation). The paper provides agencies with a framework for taking a holistic look at their parking programs and assessing the impacts of various alternative, cost-effective approaches.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

scholarly journals Privacy-Preserving Smart Road-Pricing System with Trustworthiness Evaluation in VANETs

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3658
Author(s):  
Qingfeng Zhu ◽  
Sai Ji ◽  
Jian Shen ◽  
Yongjun Ren
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Location Privacy ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Security Analysis ◽  
Geographical Location ◽  
Experimental Simulation ◽  
Control Center

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.

scholarly journals An Augmented Warning System for Pedestrians: User Interface Design and Algorithm Development

2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Interface Design ◽  
Situational Awareness ◽  
Warning System ◽  
User Interface Design ◽  
Warning Systems ◽  
Projection Algorithms ◽  
Time Projection ◽  
Timely Warning

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.

scholarly journals Cost-Effective Real-Time Metabolic Profiling of Cancer Cell Lines for Plate-Based Assays

Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 139
Author(s):  
Wiktoria Blaszczak ◽  
Zhengchu Tan ◽  
Pawel Swietach
Keyword(s):  
Real Time ◽  
Cell Lines ◽  
Acid Production ◽  
Metabolic Regulation ◽  
Cost Effective ◽  
Culture Conditions ◽  
Metabolic Inhibitors ◽  
Metabolic Phenotype ◽  
Ductal Adenocarcinoma ◽  
Oxygen Utilization

A fundamental phenotype of cancer cells is their metabolic profile, which is routinely described in terms of glycolytic and respiratory rates. Various devices and protocols have been designed to quantify glycolysis and respiration from the rates of acid production and oxygen utilization, respectively, but many of these approaches have limitations, including concerns about their cost-ineffectiveness, inadequate normalization procedures, or short probing time-frames. As a result, many methods for measuring metabolism are incompatible with cell culture conditions, particularly in the context of high-throughput applications. Here, we present a simple plate-based approach for real-time measurements of acid production and oxygen depletion under typical culture conditions that enable metabolic monitoring for extended periods of time. Using this approach, it is possible to calculate metabolic fluxes and, uniquely, describe the system at steady-state. By controlling the conditions with respect to pH buffering, O2 diffusion, medium volume, and cell numbers, our workflow can accurately describe the metabolic phenotype of cells in terms of molar fluxes. This direct measure of glycolysis and respiration is conducive for between-runs and even between-laboratory comparisons. To illustrate the utility of this approach, we characterize the phenotype of pancreatic ductal adenocarcinoma cell lines and measure their response to a switch of metabolic substrate and the presence of metabolic inhibitors. In summary, the method can deliver a robust appraisal of metabolism in cell lines, with applications in drug screening and in quantitative studies of metabolic regulation.

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