Dashboard

About: Dashboard is a research topic. Over the lifetime, 1933 publications have been published within this topic receiving 14928 citations. The topic is also known as: control panel (engineering) & dash.

Multi-purpose plug-in monitor for vehicles

Abstract: Modem passenger vehicles have many electronic control modules linked by a serial data bus. The control modules provide a large, continuous stream of driving and vehicle parameters which are available at a federally mandated data port located under the dashboard. With no other circuitry or sensors, the new electronic monitor is plugged into the data port to obtain real-time driving and vehicle data. This real-time data can be used to instruct and improve safety related driving behavior, improve fuel efficiency related driving behavior, aid in diagnosing vehicle problems, fleet use monitoring, and customized monitoring. The specific software programmed into the monitor is tailored to the specific desires of the vehicle owner, vehicle operator, vehicle driver or possible future governmental regulations. Also, with an optional key-fob like device, certain other software can be engaged or disengaged during use of the vehicle.

The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned

Abstract: On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served the global audience for more than 30 consecutive months, totalling over 226 billion feature layer requests and 3·6 billion page views. The highest daily record was set on March 29, 2020, with more than 4·6 billion requests and over 69 million views. This Personal View reveals the fundamental technical details of the entire data system underlying the dashboard, including data collection, data fusion logic, data curation and sharing, anomaly detection, data corrections, and the human resources required to support such an effort. The Personal View also covers the challenges, ranging from data visualisation to reporting standardisation. The details presented here help develop a framework for future, large-scale public health-related data collection and reporting.

System for minimizing automobile collision damage

Abstract: A system for minimizing automobile collision damage using radiant energy detectors and externally deployed air bags for aiding in damage reduction of automobile collisions. This system includes radiant energy detectors, such as radars, with transmitters and receivers, a computer, and energy absorbing inflation devices, air bags. Optionally, the system may be adapted to provide warnings and control vehicle functions, such as braking and disengaging the drive train. A dashboard link allows the computer to determine speed, steering and other conditions of the automobile, while the radiant energy detectors provide the computer with information of the object (e.g., another vehicle, pedestrian, or inanimate item) of imminent collision. The computer, using the information provided will determine at what time a ensuing collision will occur, and establish a minimal allowable time window to deploy the inflation device. The inflation device or air bag provides an energy absorbing and diverting buffer between the automobile and the object of imminent collision. The computer uses minimal allowable time window to deploy the air bag automatically, allowing the control of the automobile to remain with the driver such that necessary evasive measures can be taken. Once the imminent collision reaches the minimal allowable time window, the computer initiates a control signal deploying the external air bag. Once deployed, the external air bag reduces the amount of physical damage to the automobile, resulting in less injury, and repair costs.

Interface design considerations for an in-vehicle eco-driving assistance system

Abstract: This high-fidelity driving simulator study used a paired comparison design to investigate the effectiveness of 12 potential eco-driving interfaces. Previous work has demonstrated fuel economy improvements through the provision of in-vehicle eco-driving guidance using a visual or haptic interface. This study uses an eco-driving assistance system that advises the driver of the most fuel efficient accelerator pedal angle, in real time. Assistance was provided to drivers through a visual dashboard display, a multimodal visual dashboard and auditory tone combination, or a haptic accelerator pedal. The style of advice delivery was varied within each modality. The effectiveness of the eco-driving guidance was assessed via subjective feedback, and objectively through the pedal angle error between system-requested and participant-selected accelerator pedal angle. Comparisons amongst the six haptic systems suggest that drivers are guided best by a force feedback system, where a driver experiences a step change in force applied against their foot when they accelerate inefficiently. Subjective impressions also identified this system as more effective than a stiffness feedback system involving a more gradual change in pedal feedback. For interfaces with a visual component, drivers produced smaller pedal errors with an in-vehicle visual display containing second order information on the required rate of change of pedal angle, in addition to current fuel economy information. This was supported by subjective feedback. The presence of complementary audio alerts improved eco-driving performance and reduced visual distraction from the roadway. The results of this study can inform the further development of an in-vehicle assistance system that supports ‘green’ driving.