40,010 research outputs found
Evaluation of the Overheight Detection System Effectiveness at Eklutna Bridge
The Eklutna River/Glenn Highway bridge has sustained repeated impacts from overheight trucks. In 2006, ADOT&PF installed an overheight vehicle warning system. The system includes laser detectors, alarms, and message boards. Since installation, personnel have
seen no new damage, and no sign that the alarm system has been triggered. Although this is good news, the particulars are a mystery: Is the system working? Is the presence of the equipment enough to deter drivers from gambling with a vehicle that might be over the
height limit? Is it worth installing similar systems at other overpasses? This project is examining the bridge for any evidence of damage, and is fitting the system with a datalogger to record and video any events that trigger the warning system. Finally, just to be sure, researchers will test the system with (officially) overheight vehicles. Project results will help ADOT&PF determine if this system is functioning, and if a similar system installed at other bridges would be cost-effective.Fairbanks North Star Boroug
Map++: A Crowd-sensing System for Automatic Map Semantics Identification
Digital maps have become a part of our daily life with a number of commercial
and free map services. These services have still a huge potential for
enhancement with rich semantic information to support a large class of mapping
applications. In this paper, we present Map++, a system that leverages standard
cell-phone sensors in a crowdsensing approach to automatically enrich digital
maps with different road semantics like tunnels, bumps, bridges, footbridges,
crosswalks, road capacity, among others. Our analysis shows that cell-phones
sensors with humans in vehicles or walking get affected by the different road
features, which can be mined to extend the features of both free and commercial
mapping services. We present the design and implementation of Map++ and
evaluate it in a large city. Our evaluation shows that we can detect the
different semantics accurately with at most 3% false positive rate and 6% false
negative rate for both vehicle and pedestrian-based features. Moreover, we show
that Map++ has a small energy footprint on the cell-phones, highlighting its
promise as a ubiquitous digital maps enriching service.Comment: Published in the Eleventh Annual IEEE International Conference on
Sensing, Communication, and Networking (IEEE SECON 2014
Examining the potential of floating car data for dynamic traffic management
Traditional traffic monitoring systems are mostly based on road side equipment (RSE) measuring traffic conditions throughout the day. With more and more GPS-enabled connected devices, floating car data (FCD) has become an interesting source of traffic information, requiring only a fraction of the RSE infrastructure investment. While FCD is commonly used to derive historic travel times on individual roads and to evaluate other traffic data and algorithms, it could also be used in traffic management systems directly. However, as live systems only capture a small percentage of all traffic, its use in live operating systems needs to be examined. Here, the authors investigate the potential of FCD to be used as input data for live automated traffic management systems. The FCD in this study is collected by a live country-wide FCD system in the Netherlands covering 6-8% of all vehicles. The (anonymised) data is first compared to available road side measurements to show the current quality of FCD. It is then used in a dynamic speed management system and compared to the installed system on the studied highway. Results indicate the FCD set-up can approximate the installed system, showing the feasibility of a live system
Image Parsing with a Wide Range of Classes and Scene-Level Context
This paper presents a nonparametric scene parsing approach that improves the
overall accuracy, as well as the coverage of foreground classes in scene
images. We first improve the label likelihood estimates at superpixels by
merging likelihood scores from different probabilistic classifiers. This boosts
the classification performance and enriches the representation of
less-represented classes. Our second contribution consists of incorporating
semantic context in the parsing process through global label costs. Our method
does not rely on image retrieval sets but rather assigns a global likelihood
estimate to each label, which is plugged into the overall energy function. We
evaluate our system on two large-scale datasets, SIFTflow and LMSun. We achieve
state-of-the-art performance on the SIFTflow dataset and near-record results on
LMSun.Comment: Published at CVPR 2015, Computer Vision and Pattern Recognition
(CVPR), 2015 IEEE Conference o
Springs of Florida
bulletin
which documented the major and important springs in the state (Ferguson et al., 1947).
This publication was revised in 1977, with many previously undocumented springs and
many new water-quality analyses being added (Rosenau et al., 1977). The Florida
Geological Survey's report on first magnitude springs (Scott et al., 2002) was the initial step
in once again updating and revising the Springs of Florida bulletin. The new bulletin
includes the spring descriptions and water-quality analyses from Scott et al. (2002). Nearly
300 springs were described in 1977. As of 2004, more than 700 springs have been recognized
in the state and more are reported each year. To date, 33 first magnitude springs (with a
flow greater than 100 cubic feet per second or approximately 64.6 million gallons of water
per day) have been recognized in Florida, more than any other state or country (Rosenau et
al., 1977). Our springs are a unique and invaluable natural resource. A comprehensive
understanding of the spring systems will provide the basis for their protection and wise use.
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