1,355,242 research outputs found
StanfordASL/matsim-AMoD: AURO 2017
No full text<p>Simulation code as used in Rossi F, Zhang R, Hindy Y, Pavone M (2017) <em><a href="https://www.federico.io/pdf/Rossi.Zhang.Hindy.Pavone.AURO17.pdf">Routing Autonomous Vehicles in congested transportation networks: structural properties and coordination algorithms</a></em>, conditionally accepted to Autonomous Robots.</p>
Steganography for Invisible Communication: A Review
No full textSteganography is the science and art of embedding secret messages in innocuous looking carriers in such a way that it does not draw the attention of anyone other than the sender and the targeted recipient, thus a method for secret and invisible communication which provides security through obscurity. Its main purpose is to hide the occurrence of communication over a public channel. Steganography has been used since ancient times and has grown exponentially in the recent past because of the improvements in computing power. Earlier, steganography was implemented using some physical medium i.e. some tangible objects but now a days, it is implemented electronically by using several other intangible objects i.e. data can be hidden using any type of media, be it image in bmp, jpeg, gif format or some music file, video clip, text file, SMS etc. In this paper, different types of techniques used to hide data have been discussed with major focus on image based modern steg-anographic techniques
Data-driven Spatio-Temporal Scaling of Travel Times for AMoD Simulations
Get PDFWith the widespread adoption of mobility-on-demand (MoD) services and the
advancements in autonomous vehicle (AV) technology, the research interest into
the AVs based MoD (AMoD) services has grown immensely. Often agent-based
simulation frameworks are used to study the AMoD services using the trip data
of current Taxi or MoD services. For reliable results of AMoD simulations, a
realistic city network and travel times play a crucial part. However, many
times the researchers do not have access to the actual network state
corresponding to the trip data used for AMoD simulations reducing the
reliability of results. Therefore, this paper introduces a spatio-temporal
optimization strategy for scaling the link-level network travel times using the
simulated trip data without additional data sources on the network state. The
method is tested on the widely used New York City (NYC) Taxi data and shows
that the travel times produced using the scaled network are very close to the
recorded travel times in the original data. Additionally, the paper studies the
performance differences of AMoD simulation when the scaled network is used. The
results indicate that realistic travel times can significantly impact AMoD
simulation outcomes
A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems
Get PDFElectric vehicles (EVs) play critical roles in autonomous mobility-on-demand
(AMoD) systems, but their unique charging patterns increase the model
uncertainties in AMoD systems (e.g. state transition probability). Since there
usually exists a mismatch between the training and test/true environments,
incorporating model uncertainty into system design is of critical importance in
real-world applications. However, model uncertainties have not been considered
explicitly in EV AMoD system rebalancing by existing literature yet, and the
coexistence of model uncertainties and constraints that the decision should
satisfy makes the problem even more challenging. In this work, we design a
robust and constrained multi-agent reinforcement learning (MARL) framework with
state transition kernel uncertainty for EV AMoD systems. We then propose a
robust and constrained MARL algorithm (ROCOMA) with robust natural policy
gradients (RNPG) that trains a robust EV rebalancing policy to balance the
supply-demand ratio and the charging utilization rate across the city under
model uncertainty. Experiments show that the ROCOMA can learn an effective and
robust rebalancing policy. It outperforms non-robust MARL methods in the
presence of model uncertainties. It increases the system fairness by 19.6% and
decreases the rebalancing costs by 75.8%.Comment: 8 pages, accepted to IROS202
Darwin_Scientist
No full textThis image is one in a series used in a learning object. It is an original oil painting by Amod Damle inspired by a video biography on Darwin.This image represents Charles Darwin as a scientist committed to careful observation and maintaining his observations in his sketch books and personal journals.Ohio Learning Networ
Autonomous Mobility on-Demand in urban areas: A Rotterdam-Zuid case study
No full textDue to connectivity problems, the attractiveness of public transport is limited. Policymakers aim to increase the modal share of public transport to protect the accessibility, livability, safety, sustainability and efficiency in the cities of the future. Applying Autonomous Mobility on-Demand (AMoD) systems as a feeder service for public transport hubs can improve the first- and last-mile trip leg, increasing the attractivity of public transport. It is essential for the implementation of AMoD systems to predict the impacts of varying operational strategies on beforehand. From an operators perspective, especially the financial viability of AMoD operations is vital and yet unclear. An existing gravity-based travel demand estimation model built in OmniTRANS is used to predict the AMoD passenger demand. Besides, an agent-based simulation model is developed using the software Anylogic that is connected to the demand-model as an add-on module to simulate the behavior of passengers and AMoD vehicles within an urban environment. The agent-based simulation model is applied to the case study Rotterdam-Zuid, where Station Zuidplein and Station Lombardijen function as an AMoD hub. The simulation outputs show that activating dynamic ridesharing using wireless fast chargers at the stations results in the most financially viable operation. Activating automatic relocation results in the most costly operation. Compared to existing public transport services, carsharing systems and taxi systems, the AMoD system shows to save a large amount of expenses due to the absence of drivers.STADCivil Engineering | Transport and Plannin
Characterization of Two New Genes, amoR and amoD, in the amo Operon of the Marine Ammonia Oxidizer Nitrosococcus oceani ATCC 19707
Get PDFMolecular analysis of the
amo
gene cluster in
Nitrosococcus oceani
revealed that it consists of five genes, instead of the three known genes,
amoCAB
. The two additional genes,
orf1
and
orf5
, were introduced as
amoR
and
amoD
, respectively. Putative functions of the AmoR and AmoD proteins are discussed
Figure 2 in A new species of the enigmatic genus Chiromachetes Pocock, 1899 (Scorpiones: Hormuridae) from Western Ghats, India, with a key to the genus
No full textFigure 2: Chiromachetes sahyadriensis sp. nov. holotype male NCBS AG-873. (A) carapace and mesosoma; (B) genital operculum and pectines. Scale 10 mm.Published as part of Mirza, Zeeshan A., Sanap, Rajesh V. & Zambre, Amod M., 2015, A new species of the enigmatic genus Chiromachetes Pocock, 1899 (Scorpiones: Hormuridae) from Western Ghats, India, with a key to the genus, pp. 1-10 in Euscorpius 212 on page 3, DOI: 10.18590/euscorpius.2015.vol2015.iss212.1, http://zenodo.org/record/550810
Figure 3 in A new species of the enigmatic genus Chiromachetes Pocock, 1899 (Scorpiones: Hormuridae) from Western Ghats, India, with a key to the genus
No full textFigure 3: Chiromachetes sahyadriensis sp. nov. holotype male NCBS AG-873. (A) chelicerae; (B) lateral eyes; (C), dentition on movable finger, (D) tarsi IV.Published as part of Mirza, Zeeshan A., Sanap, Rajesh V. & Zambre, Amod M., 2015, A new species of the enigmatic genus Chiromachetes Pocock, 1899 (Scorpiones: Hormuridae) from Western Ghats, India, with a key to the genus, pp. 1-10 in Euscorpius 212 on page 5, DOI: 10.18590/euscorpius.2015.vol2015.iss212.1, http://zenodo.org/record/550810
SDG 12: A long way off from changing how we produce and consume
No full textAn outline of a study done on the formulation of Sustainable Development Goal 12, on sustainable consumption and production; done (as was this blog) by Des Gasper, Amod Shah and Sunil Tankha, as part of a broader study of SDGs formulation, led by the New School of Social Research in New York and the Centre for Development and Environment at the University of Oslo
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