scholarly journals Agent Based Resilient Transportation Infrastructure With Surrogate Adaptive Networks

2021 ◽  
Author(s):  
Cameron Turner ◽  
Andre Apostol
Keyword(s):  
Transportation Infrastructure ◽  
Adaptive Networks ◽  
Agent Based

scholarly journals Agent Based Resilient Transportation Infrastructure With Surrogate Adaptive Networks

2020 ◽  
Author(s):  
Andre A. Apostol ◽  
Cameron J. Turner
Keyword(s):  
Decision Making ◽  
Traffic Flow ◽  
Intelligent Agents ◽  
Autonomous Vehicle ◽  
Transportation Infrastructure ◽  
Adaptive Networks ◽  
Agent Based ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Vehicle Technology

Abstract Connected autonomous intelligent agents (AIA) can improve intersection performance and resilience for the transportation infrastructure. An agent is an autonomous decision maker whose decision making is determined internally but may be altered by interactions with the environment or with other agents. Implementing agent-based modeling techniques to advance communication for more appropriate decision making can benefit autonomous vehicle technology. This research examines vehicle to vehicle (V2V), vehicle to infrastructure (V2I), and infrastructure to infrastructure (I2I) communication strategies that use gathered data to ensure these agents make appropriate decisions under operational circumstances. These vehicles and signals are modeled to adapt to the common traffic flow of the intersection to ultimately find an traffic flow that will minimizes average vehicle transit time to improve intersection efficiency. By considering each light and vehicle as an agent and providing for communication between agents, additional decision-making data can be transmitted. Improving agent based I2I communication and decision making will provide performance benefits to traffic flow capacities.

Agent-Based Modeling for Carpooling

2015 ◽  
pp. 662-688
Author(s):  
Luk Knapen ◽  
Ansar-Ul-Haque Yasar ◽  
Sungjin Cho ◽  
Tom Bellemans
Keyword(s):  
Network Structure ◽  
Large Scale ◽  
Agent Based Modeling ◽  
Transportation Infrastructure ◽  
Problem Size ◽  
Agent Based ◽  
Traffic Demand ◽  
Software Structure ◽  
Large Scale Simulations ◽  
Mutually Independent

Modeling activities and travel for individuals in order to estimate traffic demand leads to large scale simulations. Most current models simulate individuals acting in a mutually independent way except for the use of the shared transportation infrastructure. As soon as cooperation between autonomous individuals is accounted for, the individuals are linked to each other in a network structure and interact with their neighbours in the network while trying to achieve their own goals. In concrete traffic-related problems, those networks can grow very large. Optimization over such networks typically leads to combinatorially explosive problems. In this chapter, the case of providing optimal advice to combine carpooling candidates is considered. First, the advisor software structure is explained; then, the characteristics for the carpooling candidates network derived for Flanders (Belgium) are calculated in order to estimate the problem size.

Agent-Based Modeling for Carpooling

2014 ◽  
pp. 232-258
Author(s):  
Luk Knapen ◽  
Ansar-Ul-Haque Yasar ◽  
Sungjin Cho ◽  
Tom Bellemans
Keyword(s):  
Network Structure ◽  
Large Scale ◽  
Agent Based Modeling ◽  
Transportation Infrastructure ◽  
Problem Size ◽  
Agent Based ◽  
Traffic Demand ◽  
Software Structure ◽  
Large Scale Simulations ◽  
Mutually Independent

Modeling activities and travel for individuals in order to estimate traffic demand leads to large scale simulations. Most current models simulate individuals acting in a mutually independent way except for the use of the shared transportation infrastructure. As soon as cooperation between autonomous individuals is accounted for, the individuals are linked to each other in a network structure and interact with their neighbours in the network while trying to achieve their own goals. In concrete traffic-related problems, those networks can grow very large. Optimization over such networks typically leads to combinatorially explosive problems. In this chapter, the case of providing optimal advice to combine carpooling candidates is considered. First, the advisor software structure is explained; then, the characteristics for the carpooling candidates network derived for Flanders (Belgium) are calculated in order to estimate the problem size.

Total etch dentin bonding systems: scanning electron microscopy of the resin-dentin hybrid layer

1992 ◽  
Vol 50 (2) ◽  
pp. 1092-1093
Author(s):  
Jorge Perdigao
Keyword(s):  
Composite Resin ◽  
Mechanical Interlocking ◽  
Hybrid Layer ◽  
Agent Based ◽  
Dentin Bonding ◽  
Acid Agent ◽  
Bond Strengths ◽  
Main Component ◽  
Bonding Systems ◽  
New Generation

In 1955, Buonocore introduced the etching of enamel with phosphoric acid. Bonding to enamel was created by mechanical interlocking of resin tags with enamel prisms. Enamel is an inert tissue whose main component is hydroxyapatite (98% by weight). Conversely, dentin is a wet living tissue crossed by tubules containing cellular extensions of the dental pulp. Dentin consists of 18% of organic material, primarily collagen. Several generations of dentin bonding systems (DBS) have been studied in the last 20 years. The dentin bond strengths associated with these DBS have been constantly lower than the enamel bond strengths. Recently, a new generation of DBS has been described. They are applied in three steps: an acid agent on enamel and dentin (total etch technique), two mixed primers and a bonding agent based on a methacrylate resin. They are supposed to bond composite resin to wet dentin through dentin organic component, forming a peculiar blended structure that is part tooth and part resin: the hybrid layer.

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