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.

FPGA Based Vehicle to Vehicle Communication in Spartan 3E

2020 ◽  
Vol 8 ◽  
pp. 14-21
Author(s):  
Surya Man Koju ◽  
Nikil Thapa
Keyword(s):  
Signal Processing ◽  
Autonomous Vehicle ◽  
Processing Unit ◽  
Warning Signals ◽  
Vehicle Communication ◽  
Digital Vlsi ◽  
Vehicle To Vehicle ◽  
Vehicle Operation ◽  
Vehicle Technology ◽  
The Voice

This paper presents economic and reconfigurable RF based wireless communication at 2.4 GHz between two vehicles. It implements digital VLSI using two Spartan 3E FPGAs, where one vehicle receives the information of another vehicle and shares its own information to another vehicle. The information includes vehicle’s speed, location, heading and its operation, such as braking status and turning status. It implements autonomous vehicle technology. In this work, FPGA is used as central signal processing unit which is interfaced with two microcontrollers (ATmega328P). Microcontroller-1 is interfaced with compass module, GPS module, DF Player mini and nRF24L01 module. This microcontroller determines the relative position and the relative heading as seen from one vehicle to another. Microcontroller-2 is used to measure the speed of vehicle digitally. The resulting data from these microcontrollers are transmitted separately and serially through UART interface to FPGA. At FPGA, different signal processing such as speed comparison, turn comparison, distance range measurement and vehicle operation processing, are carried out to generate the voice announcement command, warning signals, event signals, and such outputs are utilized to warn drivers about potential accidents and prevent crashes before event happens.

scholarly journals Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1221
Author(s):  
Anum Mushtaq ◽  
Irfan ul Haq ◽  
Wajih un Nabi ◽  
Asifullah Khan ◽  
Omair Shafiq
Keyword(s):  
Traffic Flow ◽  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Flow Management ◽  
V2v Communication ◽  
Cooperative Strategies ◽  
Vehicle To Vehicle ◽  
Traffic Flow Management ◽  
Vehicle To Infrastructure ◽  
Formation And Evolution

Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.

Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming

2018 ◽  
Author(s):  
R. Austin Dollar ◽  
Ardalan Vahidi
Keyword(s):  
Autonomous Vehicle ◽  
Mixed Integer ◽  
Quadratic Program ◽  
Vehicle To Vehicle ◽  
Trip Time ◽  
Induced Travel ◽  
Vehicle Acceleration ◽  
Vehicle Technology ◽  
Rule Based Approach ◽  
Integer Quadratic Program

Autonomous vehicle technology provides the means to optimize motion planning beyond human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip time, energy efficiency, and collision avoidance presents challenges beyond those of single-lane roadways. For example, the host vehicle must simultaneously track multiple obstacles, the drivable region is non-convex, and automated vehicles must obey social expectations. Furthermore, reactive decision-making may result in becoming stuck in an undesirable traffic position. This paper presents a fundamental approach to these problems using model predictive control with a mixed integer quadratic program at its core. Lateral and longitudinal movements are coordinated to avoid collisions, track a velocity and lane, and minimize acceleration. Vehicle-to-vehicle connectivity provides a preview of surrounding vehicles’ motion. Simulation results show a 79% reduction in congestion-induced travel time and an 80% decrease in congestion-induced fuel consumption compared to a rule-based approach.

scholarly journals Agent based model

2020 ◽  
Vol 55 ◽  
pp. S187-S191 ◽  
Author(s):  
S. Bai ◽  
W. Raskob ◽  
T. Müller
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Intelligent Agents ◽  
Decision Making Process ◽  
Agent Based Model ◽  
Radiological Emergency ◽  
Agent Based ◽  
Computational Implementation ◽  
Protection Strategies ◽  
Decision Making Processes

In the CONFIDENCE project, we developed an agent based model (ABM) to simulate the decision making process involving stakeholders of different interests. Our model aims to support decisions on the most suitable protection strategies in different accident phases. The intelligent agents and the models of the negotiation/voting process are described in the paper. Given five scenarios, the numerical results from the computational implementation of the ABM are visualized and analysed in order to better understand the negotiation and voting processes. Our ABM can be expanded in order to support the decision making processes of many different stakeholders of various types of risk management apart from nuclear and radiological emergency management.

Witness of Things

2019 ◽  
Vol 7 (2) ◽  
pp. 72-87 ◽  
Author(s):  
Serkan Ayvaz ◽  
Salih Cemil Cetin
Keyword(s):  
Autonomous Vehicles ◽  
Vehicular Networks ◽  
Autonomous Vehicle ◽  
Content Type ◽  
Record Keeping ◽  
Vehicle To Vehicle ◽  
Autonomous Cars ◽  
Vehicle To Infrastructure ◽  
Governmental Institutions ◽  
Self Driving Cars

Purpose The purpose of this paper is to develop a model for autonomous cars to establish trusted parties by combining distributed ledgers and self-driving cars in the traffic to provide single version of the truth and thus build public trust. Design/methodology/approach The model, which the authors call Witness of Things, is based on keeping decision logs of autonomous vehicles in distributed ledgers through the use of vehicular networks and vehicle-to-vehicle/vehicle-to-infrastructure (or vice versa) communications. The model provides a single version of the truth and thus helps enable the autonomous vehicle industry, related organizations and governmental institutions to discover the true causes of road accidents and their consequences in investigations. Findings In this paper, the authors explored one of the potential effects of blockchain protocol on autonomous vehicles. The framework provides a solution for operating autonomous cars in an untrusted environment without needing a central authority. The model can also be generalized and applied to other intelligent unmanned systems. Originality/value This study proposes a blockchain protocol-based record-keeping model for autonomous cars to establish trusted parties in the traffic and protect single version of the truth.

scholarly journals Agent based Decision Support System for Travelers

2020 ◽  
pp. 293-298
Author(s):  
Thi Thi Tun ◽  
Prof Thwe
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Intelligent Agents ◽  
Decision Making Process ◽  
Agent Based ◽  
Travel Planning

Nowadays, management of the travelers to support their recreation or holiday planning is increasingly becoming important and popular. Planning a trip needs to assemble a wide variety of information from a large number of sources, such as car schedule and prices, hotel locations, the map of traveled places, etc. Now, this information is available in this system and it can be used to decide a better plan traveler. Decision support systems are the type of information systems expressly developed to support the decision making process and to assist a decision maker. So, this system is implemented as the decision support system for travelling. Moreover, this system describes the use of intelligent agents for extracting and integrating data to improve the ability to plan a travel. These agents can extract data, integrate this data to support travel planning and monitor all aspects of a trip. Therefore, a traveler decision support system by using intelligent agents will develop to support travelers in making their decision on a suitable track when they are faced with a number of alternative track options.

Supporting Mobility and Negotiation in Agent-Based E-Commerce

2011 ◽  
pp. 226-244
Author(s):  
Ryszard Kowalczyk ◽  
Leila Alem
Keyword(s):  
Decision Making ◽  
Coalition Formation ◽  
Intelligent Agents ◽  
Mobile Agents ◽  
Formation Processes ◽  
Trade Off ◽  
Agent Based ◽  
Recent Advances

This chapter presents recent advances in agent-based e-commerce, addressing the issues of mobility and negotiation. It reports on selected research efforts, focusing on developing intelligent agents for automating the e-commerce negotiation and coalition formation processes and mobile agents for supporting deployment of intelligent e-commerce agents and enabling mobile e-commerce applications. Issues such as trade-off between decision-making in negotiation and mobility capabilities of the agents are also discussed in this paper.

scholarly journals Agent-Based Dispatching Enables Autonomous Groupage Traffic

2013 ◽  
Vol 3 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Max Gath ◽  
Stefan Edelkamp ◽  
Otthein Herzog
Keyword(s):  
Decision Making ◽  
Intelligent Agents ◽  
Time Windows ◽  
Reactive System ◽  
Adaptive Planning ◽  
Routing Problem ◽  
Agent Based ◽  
Practical Applications ◽  
Planning And Control ◽  
The Individual

Abstract The complexity and dynamics in groupage traffic require flexible, efficient, and adaptive planning and control processes. The general problem of allocating orders to vehicles can be mapped into the Vehicle Routing Problem (VRP). However, in practical applications additional requirements complicate the dispatching processes and require a proactive and reactive system behavior. To enable automated dispatching processes, this article presents a multiagent system where the decision making is shifted to autonomous, interacting, intelligent agents. Beside the communication protocols and the agent architecture, the focus is on the individual decision making of the agents which meets the specific requirements in groupage traffic. To evaluate the approach we apply multiagent-based simulation and model several scenarios of real world infrastructures with orders provided by our industrial partner. Moreover, a case study is conducted which covers the autonomous groupage traffic in the current processes of our industrial parter. The results reveal that agent-based dispatching meets the sophisticated requirements of groupage traffic. Furthermore, the decision making supports the combination of pickup and delivery tours efficiently while satisfying logistic request priorities, time windows, and capacity constraints.

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