Improving Parking Availability Maps using Information from Nearby Roads

Parking search traffic causes increased travel times and air pollution in many cities. Real-time parking availability maps are expected to help drivers to find a parking space faster and thus to reduce parking search traffic. A possibility to create such maps is the aggregation of parking availability information from crowdsourcing solutions like probe vehicles and mobile phone applications. Since these sources cannot sense the whole city at the same time, estimation methods are necessary to fill uncovered areas. This paper investigates the estimation of parking availability based on spatial methods using sensor data from San Francisco. First, spatial similarities in parking availability are evaluated for different aspects like time of day and number of parking spaces depending on the distance to reveal the parking characteristics. Then, interpolation methods are examined to estimate parking availability in unobserved road segments. Results show that relevant similarities mainly exist for short distances of less than hundred meters. Their similarity values are lower than the temporal similarity even for multiple hours of time gap. Nevertheless, spatial information is useful to interpolate parking availability. Investigated interpolation methods show significantly better results than random guess. Inverse distance weighting method outperforms a simple averaging by up to 5%.DFG/GRK/193

On-street Parking Availaibilty Data in San Francisco, from Stationary Sensors and High-Mileage Probe Vehicles

This dataset contains records of the measured on-street parking availability in San Francisco, obtained from the public API of the SFpark project. In 2011, the San Francisco Municipal Transportation Agency (SFMTA) started a project on smart parking, called SFpark, whose goal was the improvement of on-street parking management in San Francisco, mostly by means of demand-responsive price adjustments. One of the key points of the project was the collection of information about on-street parking availability. To this aim, about 8,000 parking spaces were equipped with specific sensors in the asphalt, periodically broadcasting availability information. The SFpark project made available a public REST API, returning the number of free parking spaces and total number of provided parking spaces per road segment, for 5,314 parking spaces on 579 road segments in the pilot area. We collected parking availability data from 2013/06/13 until 2013/07/24, by querying this API at approximately 5-minute intervals. As a result, we obtained in total about 7 million observations of parking availability on the road segments. These observations represent the first dataset we are providing. In addition, we simulated the achievable sensing coverage of on-street parking availability that could be achieved by a fleet of taxis, if they were equipped with sensors able to detect free parking spaces, like side-scanning ultrasonic sensors, or windshield-mounted cameras [4]. In particular, by exploiting real taxi trajectories in San Francisco from the Cabspotting project, we first computed the frequencies of taxi visits for each road segment covered by the SFpark sensors. Then, we downsampled the first dataset, in order to have a parking availability information for a road segment at a given time only in presence of a transit of a taxi on that segment at that time. This step was replicated for 5 different sizes of taxi fleets, namely 100, 200, 300, 400, and 486. Consequently, in total six datasets are available for further research in the field of on-street parking dynamics

Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data. In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index. Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters

On-street parking availaibilty data in San Francisco, from stationary sensors and high-mileage probe vehicles

This dataset contains records of the measured on-street parking availability in San Francisco, obtained from the public API of the SFpark project. In 2011, the San Francisco Municipal Transportation Agency (SFMTA) started a project on smart parking, called SFpark, whose goal was the improvement of on-street parking management in San Francisco, mostly by means of demand-responsive price adjustments [1]. One of the key points of the project was the collection of information about on-street parking availability. To this aim, about 8,000 parking spaces were equipped with specific sensors in the asphalt, periodically broadcasting availability information. The SFpark project made available a public REST API, returning the number of free parking spaces and total number of provided parking spaces per road segment, for 5,314 parking spaces on 579 road segments in the pilot area. We collected parking availability data from 2013/06/13 until 2013/07/24, by querying this API at approximately 5-min intervals. As a result, we obtained in total about 7 million observations of parking availability on the road segments. These observations represent the first dataset we are providing. In addition, we simulated the achievable sensing coverage of on-street parking availability that could be achieved by a fleet of taxis, if they were equipped with sensors able to detect free parking spaces, like side-scanning ultrasonic sensors [3], or windshield-mounted cameras [4]. In particular, by exploiting real taxi trajectories in San Francisco from the Cabspotting project [5], we first computed the frequencies of taxi visits for each road segment covered by the SFpark sensors. Then, we downsampled the first dataset, in order to have a parking availability information for a road segment at a given time only in presence of a transit of a taxi on that segment at that time. This step was replicated for 5 different sizes of taxi fleets, namely 100, 200, 300, 400, and 486. Consequently, in total six datasets are available for further research in the field of on-street parking dynamics. All these datasets can be downloaded at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YLWCSU

DLR Magazin 167: Beflügelnde Aussichten

Zukünftige Luftfahrzeuge müssen möglichst klimafreundlich und leise sein – trotzdem sollte der Komfort während der Reise nicht auf der Strecke bleiben. Neue Kabinenkonzepte könnten diese Anforderungen erfüllen. Am DLR-Institut für Systemarchitekturen in der Luftfahrt in Hamburg-Finkenwerder untersucht ein Team von Industriedesignerinnen und -designern, wie Menschen in Zukunft unterwegs sein möchten, wie sich ihr Reiseverhalten aufgrund der Pandemie ändern könnte und welche Auswirkungen dies auf die Gestaltung von Flugzeugen hat. Das Team erarbeitet neue Konzepte für eine modulare Flugzeugkabine, die an die Bedürfnisse der Menschen angepasst ist, und bezieht dafür auch die Passagiere in den Designprozess mit ein

Respiratory kinematics and the regulation of subglottic pressure for phonation of pitch jumps - a dynamic MRI study

The respiratory system is a central part of voice production as it contributes to the generation of subglottic pressure, which has an impact on voice parameters including fundamental frequency and sound pressure level. Both parameters need to be adjusted precisely during complex phonation tasks such as singing. In particular, the underlying functions of the diaphragm and rib cage in relation to the phonation of pitch jumps are not yet understood in detail. This study aims to analyse respiratory movements during phonation of pitch jumps using dynamic MRI of the lungs. Dynamic images of the breathing apparatus of 7 professional singers were acquired in the supine position during phonation of upwards and downwards pitch jumps in a high, medium, and low range of the singer's tessitura. Distances between characteristic anatomical landmarks in the lung were measured from the series of images obtained. During sustained phonation, the diaphragm elevates, and the rib cage is lowered in a monotonic manner. During downward pitch jumps the diaphragm suddenly changed its movement direction and presented with a short inspiratory activation which was predominant in the posterior part and was associated with a shift of the cupola in an anterior direction. The magnitude of this inspiratory movement was greater for jumps that started at higher compared to lower fundamental frequency. In contrast, expiratory movement of the rib cage and anterior diaphragm were simultaneous and continued constantly during the jump. The data underline the theory of a regulation of subglottic pressure via a sudden diaphragm contraction during phonation of pitch jumps downwards, while the rib cage is not involved in short term adaptations. This strengthens the idea of a differentiated control of rib cage and diaphragm as different functional units during singing phonation

Simulative Bewertung von Personenbewegungen in der Flugzeugkabine unter Berücksichtigung einer pandemischen Lage

Es ist davon auszugehen, dass die Covid-19 Pandemie den Luftverkehr weiterhin noch nachhaltig beeinflussen wird. Die Anzahl der angebotenen Sitzkapazitäten ist seit Pandemiebeginn um 50% eingebrochen und die ICAO-Prognose zeigt, dass vorpandemische Kapazitäten auch dieses Jahr noch nicht wieder erreicht werden, sondern etwa 20% darunter liegen. Weiterhin ist die Wiederaufnahme der Flugverbindungen stark von pandemischen Restriktionen geprägt. Neben der Vorlage von Impfzertifikaten oder Genesenennachweisen ist das Tragen von Masken und das Einhalten von Abständen erforderlich beziehungsweise wird empfohlen. In der Flugzeugkabine selber ist allerdings nur das Tragen einer Maske notwendig, andere Maßnahmen zur Ansteckungsreduzierung wie das Einhalten von Abständen werden für die Passagiere in der Regel nicht angewendet. Mit der vorliegenden Arbeit wird der Einfluss unterschiedlicher Konzepte beim Boarding und Deplaning der Passagiere auf ein mögliches Ansteckungsrisiko simulativ untersucht und bewertet, mit dem Ziel, ein leistungsfähiges Boardingkonzept zur Reduktion von Risiko-Begegnungen zu entwickeln. Durch die Modellierung und Simulation von Personenbewegungen kann wirksam untersucht werden, wie leistungsfähig frühe, neuartige und auch unkonventionelle Designkonzepte bezüglich der Schnittstellenprozesse des Boarding und Deplaning sind. Im Rahmen der Weiterentwicklung der Kabinenmodellierung und der dortigen Personenbewegungen wurde ein Bemessungswerkzeug zur Bewertung des Ansteckungsrisikos beim Boarding und Deplaning für die Passagiere in eine bestehende Simulationsumgebung integriert. Zur Anwendung kommt dabei der Algorithmus zur Bestimmung von Risikobegegnungen aus der Kombination von zu geringem Abstand und Dauer der Abstandsunterschreitung wie in der Corona-Warn-App angewendet

POST-PANDEMIC FLIGHT: ESTABLISHING THE MISSION OF THE AIRCRAFT CABIN OF THE FUTURE FROM THE PASSENGER’S POINT OF VIEW

As this paper is written, the world has been struck with a global pandemic, difficult to contain and very easy to spread. The most effective countermeasure so far is social distancing, to ensure no aerosols are exchanged. This poses a vast challenge in small, enclosed spaces, like an aircraft cabin. Unfortunately, such a countermeasure has had a great impact on the airlines and their business all over the globe. As the pandemic is not subsiding and scientists are predicting that similar situations will emerge more often in the future, it is highly necessary to take a look at the current state of the air travel and what it will have to offer to the passengers of the future. In the scope of InDiCaD (Innovative Digital Cabin Design), an internal project at German Aerospace Center (DLR), research has been done on the impact of the Covid-19 on the willingness of the passengers to fly under the given circumstances. The results of the research are threefold; firstly, a scenario where Covid-19 has left no traces, then a scenario where the consequences are enormous and the last one where the passengers are still willing to travel, albeit with an extra set of demands concerning health. These scenarios were used as a base to form mission definition for the cabin of the future as well as the fictive persona’s, depicting the passengers of the future. Through a series of workshops, there requirements have been used as foundation for building the morphological chart, consisting of partial design solutions. In this paper, the method of gathering and analysing the data will be shown as well as the resulting mission definition. The forth flowing list of requirements for designing an innovative cabin from a passenger’s point of view, able to cope with these unpreceded circumstances, will also be presented. The results of the workshop series will be shown, as well as an example of possible design outcome. To wrap up, an outlook into the future work during the project will be depicted, including the in-depth research as well as conceptual design solutions for the posed challenges

Cytoprotective Activated Protein C Averts Nlrp3 Inflammasome–Induced Ischemia-Reperfusion Injury Via Mtorc1 Inhibition

Cytoprotection by activated protein C (aPC) after ischemia-reperfusion injury (IRI) is associated with apoptosis inhibition. However, IRI is hallmarked by inflammation, and hence, cell-death forms disjunct from immunologically silent apoptosis are, in theory, more likely to be relevant. Because pyroptosis (ie, cell death resulting from inflammasome activation) is typically observed in IRI, we speculated that aPC ameliorates IRI by inhibiting inflammasome activation. Here we analyzed the impact of aPC on inflammasome activity in myocardial and renal IRIs. aPC treatment before or after myocardial IRI reduced infarct size and Nlrp3 inflammasome activation in mice. Kinetic in vivo analyses revealed that Nlrp3 inflammasome activation preceded myocardial injury and apoptosis, corroborating a pathogenic role of the Nlrp3 inflammasome. The constitutively active Nlrp3A350V mutation abolished the protective effect of aPC, demonstrating that Nlrp3 suppression is required for aPC-mediated protection from IRI. In vitro aPC inhibited inflammasome activation in macrophages, cardiomyocytes, and cardiac fibroblasts via proteinase-activated receptor 1 (PAR-1) and mammalian target of rapamycin complex 1 (mTORC1) signaling. Accordingly, inhibiting PAR-1 signaling, but not the anticoagulant properties of aPC, abolished the ability of aPC to restrict Nlrp3 inflammasome activity and tissue damage in myocardial IRI. Targeting biased PAR-1 signaling via parmodulin-2 restricted mTORC1 and Nlrp3 inflammasome activation and limited myocardial IRI as efficiently as aPC. The relevance of aPC-mediated Nlrp3 inflammasome suppression after IRI was corroborated in renal IRI, where the tissue protective effect of aPC was likewise dependent on Nlrp3 inflammasome suppression. These studies reveal that aPC protects from IRI by restricting mTORC1-dependent inflammasome activation and that mimicking biased aPC PAR-1 signaling using parmodulins may be a feasible therapeutic approach to combat IRI

The radio properties of a complete, X-ray selected sample of nearby, massive elliptical galaxies

We investigate the radio properties of a complete sample of nearby, massive, X-ray bright elliptical and S0 galaxies. Our sample contains 18 galaxies with ROSAT All-Sky Survey X-ray fluxes Fx_(0.1-2.4 keV) > 3 x 10^(-12) erg/s/cm^2, within a distance of 100 Mpc. For these galaxies, we have complete (18/18) VLA radio and Chandra X-ray coverage. Nuclear radio emission is detected from 17/18 of the galaxies. Ten of the galaxies exhibit extended radio emission; of these ten, all but one also exhibit clear evidence of interaction of the radio source with the surrounding, X-ray emitting gas. Among the seven galaxies with unresolved radio sources, one has clear, and one has small, cavity-like features in the Chandra X-ray images; a third has a disturbed X-ray morphology. Using a radio luminosity limit equivalent to L_(1.4 Ghz) > 10^(23) W/Hz to calculate the radio-loud fraction, we find that this misses the majority of the radio detected galaxies in the sample. We determine integrated radio-to-X-ray flux ratios for the galaxies, GRx, which are shown to span a large range (factor of 100). We calculate the mass-weighted cooling times within 1 kpc, and find hints for an anticorrelation with the radio luminosity. We also calculate limits on k/f, where k is the ratio of the total particle energy to that of relativistic electrons radiating in the range 10 MHz-10 GHz and f is the volume filling factor of the plasma in the cavity. The k/f distribution is also broad, reflecting previous results for larger galaxy clusters. Lowering the X-ray flux limit, at the expense of less complete VLA and Chandra coverage, increases the size of our sample to 42 galaxies. Nuclear radio activity is detected in at least 34/42 of this extended sample.Comment: Accepted for publication in MNRAS, 19 pages, 11 Figures and 7 Table