2,452 research outputs found
An Online Decision-Theoretic Pipeline for Responder Dispatch
The problem of dispatching emergency responders to service traffic accidents,
fire, distress calls and crimes plagues urban areas across the globe. While
such problems have been extensively looked at, most approaches are offline.
Such methodologies fail to capture the dynamically changing environments under
which critical emergency response occurs, and therefore, fail to be implemented
in practice. Any holistic approach towards creating a pipeline for effective
emergency response must also look at other challenges that it subsumes -
predicting when and where incidents happen and understanding the changing
environmental dynamics. We describe a system that collectively deals with all
these problems in an online manner, meaning that the models get updated with
streaming data sources. We highlight why such an approach is crucial to the
effectiveness of emergency response, and present an algorithmic framework that
can compute promising actions for a given decision-theoretic model for
responder dispatch. We argue that carefully crafted heuristic measures can
balance the trade-off between computational time and the quality of solutions
achieved and highlight why such an approach is more scalable and tractable than
traditional approaches. We also present an online mechanism for incident
prediction, as well as an approach based on recurrent neural networks for
learning and predicting environmental features that affect responder dispatch.
We compare our methodology with prior state-of-the-art and existing dispatch
strategies in the field, which show that our approach results in a reduction in
response time with a drastic reduction in computational time.Comment: Appeared in ICCPS 201
Preliminary Results of a Multiagent Traffic Simulation for Berlin
This paper provides an introduction to multi-agent traffic simulation. Metropolitan regions can consist of several million inhabitants, implying the simulation of several million travelers, which represents a considerable computational challenge. We reports on our recent case study of a real-world Berlin scenario. The paper explains computational techniques necessary to achieve results. It turns out that the difficulties there, because of data availability and because of the special situation of Berlin after the re-unification, are considerably larger than in previous scenarios that we have treated
Experiences with a simplified microsimulation for the Dallas/Fort Worth area
We describe a simple framework for micro simulation of city traffic. A medium
sized excerpt of Dallas was used to examine different levels of simulation
fidelity of a cellular automaton method for the traffic flow simulation and a
simple intersection model. We point out problems arising with the granular
structure of the underlying rules of motion.Comment: accepted by Int.J.Mod.Phys.C, 20 pages, 14 figure
Smart handoff technique for internet of vehicles communication using dynamic edge-backup node
© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin
Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time
Cooperative ITS is enabling vehicles to communicate with the infrastructure
to provide improvements in traffic control. A promising approach consists in
anticipating the road profile and the upcoming dynamic events like traffic
lights. This topic has been addressed in the French public project Co-Drive
through functions developed by Valeo named Green Light Optimal Speed Advisor
(GLOSA). The system advises the optimal speed to pass the next traffic light
without stopping. This paper presents results of its performance in different
scenarios through simulations and real driving measurements. A scaling is done
in an urban area, with different penetration rates in vehicle and
infrastructure equipment for vehicular communication. Our simulation results
indicate that GLOSA can reduce CO2 emissions, waiting time and travel time,
both in experimental conditions and in real traffic conditions.Comment: in 22nd ITS World Congress, Oct 2015, Bordeaux, France. 201
Methodological Notes on the Regional Level Validation of a Microscopic Traffic Simulation Model
Traffic simulation models have been increasingly used to evaluate and compare alternative complex real-world traffic problems. Simulation is safer, less expensive and faster than field testing. The past few years have witnessed substantial development of transportation network modeling tools and stronger emphasis on addressing the need to model large-scale networks more accurately and efficiently. While these simulation models can be helpful to transportation engineers, the models must be well calibrated and validated before they can provide credible results. However, simulation models have been often conducted under default parameters. This is mainly due to either the difficulties in field data collection or the lack of knowledge of the appropriate procedure to calibrate and validate traffic simulation models. This paper presents the results of a recent effort to microscopically simulate the regional evacuation plan for New Orleans Metropolitan Area during the hurricane Katrina. The model involved over 300,000 vehicles moving within a road network that covered several thousand square miles over a 48 hour period. Output statistics were generated on a second-by-second basis for each traveler in the system. Model validation was based upon a comparison of the TRANSIMS generated traffic volumes to the corresponding traffic volumes actually observed during the 2005 hurricane Katrina evacuation. The validation process included the percent error estimation and the regression analysis between the simulated and observed traffic volume data. This study was unique in that it is among the first to develop validation criteria for a regional model based on actual traffic data collected during a live regional mass evacuation. Analysis was performed utilizing percent errors estimation based on direct comparisons of the hourly volumes at each counting station. Also, an alternative validation approach was carried out using regression analysis between the cumulative observed and simulated volumes for the same stations by analyzing the fit for the regression line y =a + bx + ε. The error percentage and the fit were found to be reasonable with an error percentage less than 25 percent and an R-squared value of over 0.80. This indicated that the TRANSIMS simulation model was a realistic representation of the evacuation operations observed during the hurricane Katrina
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