scholarly journals A Flexible Framework for Developing Integrated Models of Transportation Systems Using an Agent-based Approach

2012 ◽  
Vol 10 ◽  
pp. 854-859 ◽  
Author(s):  
Vadim Sokolov ◽  
Joshua Auld ◽  
Michael Hope
Keyword(s):  
Transportation Systems ◽  
Integrated Models ◽  
Agent Based ◽  
Flexible Framework

Autonomous Ship Navigation Under Deep Learning and the Challenges in COLREGs

2018 ◽  
Author(s):  
Lokukaluge P. Perera
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Collision Avoidance ◽  
Situation Awareness ◽  
Type System ◽  
Performance Standards ◽  
Transportation Systems ◽  
Agent Based ◽  
Distributed Intelligence ◽  
System Intelligence

A general framework to support the navigation side of autonomous ships is discussed in this study. That consists of various maritime technologies to achieve the required level of ocean autonomy. Decision-making processes in autonomous vessels will play an important role under such ocean autonomy, therefore the same technologies should consist of adequate system intelligence. Each onboard application in autonomous vessels may require localized decision-making modules, therefore that will introduce a distributed intelligence type strategy. Hence, future ships will be agent-based systems with distributed intelligence throughout vessels. The main core of this agent should consist of deep learning type technology that has presented promising results in other transportation systems, i.e. self-driving cars. Deep learning can capture helmsman behavior, therefore that type system intelligence can be used to navigate autonomous vessels. Furthermore, an additional decision support layer should also be developed to facilitate deep learning type technology including situation awareness and collision avoidance. Ship collision avoidance is regulated by the Convention on the International Regulations for Preventing Collisions at Sea, 1972 (COLREGs) under open sea areas. Hence, a general overview of the COLREGs and its implementation challenges, i.e. regulatory failures and violations, under autonomous ships are also discussed with the possible solutions as the main contribution of this study. Furthermore, additional considerations, i.e. performance standards with the applicable limits of liability, terms, expectations and conditions, towards evaluating ship behavior as an agent-based system on collision avoidance situations are also illustrated in this study.

scholarly journals Improving Driver Assistance in Intelligent Transportation Systems: An Agent-Based Evidential Reasoning Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
M. Benalla ◽  
B. Achchab ◽  
H. Hrimech
Keyword(s):  
Intelligent Transportation Systems ◽  
Contextual Information ◽  
Sensory Information ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Evidential Reasoning ◽  
Traffic Information ◽  
Driver Assistance ◽  
Agent Based ◽  
Reasoning System

Providing accurate real-time traffic information is an inherent problem for intelligent transportation systems (ITS). In order to improve the knowledge base of advanced driver assistance systems (ADAS), ITS are strongly concerned with data fusion techniques of all kinds of sensors deployed over the traffic network. Driver assistance is devoid of a comprehensive evidential reasoning system on contextual information, more specifically when a combination involves inside and outside sensory information of the driving environment. In this paper, we propose a novel agent-based evidential reasoning system using contextual information. Based on a series of information handling techniques, specifically, the belief functions theory and heuristic inference operations to achieve a consensus about daily driving activity in automatically inferring. That is quite different from other existing proposals, as it deals jointly with the driving behavior and the driving environment conditions. A case study including various scenarios of experiments is introduced to estimate behavioral information based on synthetic data for prediction, prescription, and policy analysis. Our experiments show promising, thought-provoking results encouraging further research.

Agent Recommendation for Agent-Based Urban-Transportation Systems

2011 ◽  
Vol 26 (6) ◽  
pp. 77-81 ◽  
Author(s):  
Cheng Chen ◽  
Shuang Shuang Li ◽  
Bo Chen ◽  
Ding Wen
Keyword(s):  
Urban Transportation ◽  
Transportation Systems ◽  
Agent Based

Cloud Computing for Agent-Based Urban Transportation Systems

2011 ◽  
Vol 26 (1) ◽  
pp. 73-79 ◽  
Author(s):  
ZhenJiang Li ◽  
Cheng Chen ◽  
Kai Wang
Keyword(s):  
Cloud Computing ◽  
Urban Transportation ◽  
Transportation Systems ◽  
Agent Based

On Modeling and Verification of Agent-Based Traffic Simulation Properties in Alloy

2012 ◽  
Vol 4 (4) ◽  
pp. 38-60 ◽  
Author(s):  
Junia Valente ◽  
Frederico Araujo ◽  
Rym Z. Wenkstern
Keyword(s):  
Intelligent Transportation Systems ◽  
Large Scale ◽  
Traffic Simulation ◽  
Simulation Models ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Agent Based ◽  
Traffic Models ◽  
First Order ◽  
New Generation

The advances in Intelligent Transportation Systems (ITS) call for a new generation of traffic simulation models that support connectivity and collaboration among simulated vehicles and traffic infrastructure. In this paper we introduce MATISSE, a complex, large scale agent-based framework for the modeling and simulation of ITS and discuss how Alloy, a modeling language based on set theory and first order logic, was used to specify, verify, and analyze MATISSE’s traffic models.

scholarly journals Simulating an Impact of Road Network Improvements on the Performance of Transportation Systems under Critical Load: Agent-based Approach

2016 ◽  
Vol 101 ◽  
pp. 253-261 ◽  
Author(s):  
Dmitrii Milevich ◽  
Valentin Melnikov ◽  
Vladislav Karbovskii ◽  
Valeria Krzhizhanovskaya
Keyword(s):  
Critical Load ◽  
Road Network ◽  
Transportation Systems ◽  
Agent Based

Agent-Based Approach in Roadway Traffic and Transportation Systems: State of the Art

2007 ◽  
Author(s):  
Bo Chen ◽  
Harry H. Cheng ◽  
Joe Palen
Keyword(s):  
Large Scale ◽  
Dynamic Environment ◽  
Congestion Management ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Agent Technology ◽  
Future Research ◽  
Traffic Signal Control ◽  
Multi Agent Systems ◽  
Agent Based

Agent technology is rapidly emerging as one of the powerful technologies for the development of large-scale distributed systems to deal with the uncertainty in a dynamic environment. The domain of traffic and transportation systems is well suited for an agent-based approach because systems are usually geographically distributed in dynamic changing environments. Our literature survey shows that the techniques and methods resulted from the field of agent and multi-agent systems have been applied to many aspects of traffic and transportation systems, including modeling and simulation, dynamic routing and congestion management, intelligent traffic management, and urban traffic signal control. This paper examines agent-based approach and its applications in roadway traffic and transportation systems, and discusses several future research directions towards successful deployment of agent technology in traffic and transportation systems.

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