Mahmoud T. Khasawneh

An IntelliDrive application for reducing traffic congestions using agent-based approach

Traffic congestion on highways has increased dramatically in the last two decades. As more and more cars are put on the road each year, traffic congestion is becoming more complex and unpredictable than ever before as people try to avoid it by changing their schedules and routes. IntelliDriveSM is a suite of technologies and applications that use wireless communications to provide connectivity that can deliver transformational safety, mobility, and environmental improvements in surface transportation [11]. This paper will present an IntelliDrive agent-based model of traffic congestion and examine the impact of one vehicle on a system limited to a single traffic lane. The cars interaction is based on IntelliDrive vehicle-to-infrastructure communications. The mean speed of the cars is analyzed and the evolution of traffic congestion is observed with the passage of time. Can a single agent influence the dynamics of traffic flow on a complex network? Furthermore, can an “Intelligent-car” annul the oscillatory behavior (stop and go) resulting from the acceleration and deceleration of the other vehicles? Theoretical results are presented and a solution to reduce traffic congestions and also minimize accidents is also proposed, based on implementing one IntelliDrive-equipped vehicle, among a certain number of cars in a single-lane circuit. The approach that was finally selected and several other schemes that were considered are described.

Sensitivity analysis framework for large-scale system-of-systems applications

Sensitivity analysis (SA) is studying the impact input changes (nature and magnitude) have on outputs. The objective of this paper is to present a methodology to perform sensitivity analysis on a system dynamics simulation model that was developed in support of the Secure Border Initiative (SBI). Specifically the analysis will investigate Section 287(g) of The Illegal Immigration Reform and Immigrant Responsibility Act (1996). Due to the fact that the systems dynamics model used is a deterministic model, there was a need to induce variability using random sampling. The variability was propagated through the outputs and allowed the researchers to identify not only point estimates of what increases are required to bring the 287(g) policy to baseline values, but also calculate confidence bands. Implementing the 287(g) policy with no other system adjustments has a detrimental impact on performance in terms of fugitives and non-criminal removals.

Gender change in certain species - an agent-based modeling study

Biologists have found that certain creatures like frogs, orchids, and shrimp change their gender. Some research is proposing that species somehow know there is a gender imbalance and adjust the gender ratio accordingly. The mechanism in which the species change gender is unknown. Some scientists are suggesting that hormones are released which causes one type of reproductive organs to disappear and another type to appear. For organisms which display this phenomenon, apparently there are chemical triggers that respond to the number of members in a population. This will activate the gene(s) that will allow for the disintegration of one set of reproductive organs and the development of the other. The purpose of this paper is not to study how species technically change gender, but to explore how each individual in the population know the gender ratio and who decides who will change gender and who will not. This paper will build an agent-based model, using Netlogo©, to test the following hypothesis, “each individual in the collective does not have to know the gender ratio of the entire population in order to make decisions that will positively impact the collective.” Results show that individuals change their gender in accordance with their own needs. Regardless of the initial gender ratio and despite the fact that the individuals do not possess knowledge about the whole population, there will always be almost-equal number of males and females after a certain time.

Gender change in certain species: an agent-based modeling study

Biologists have found that certain creatures like frogs, orchids, and shrimp change their gender. Some research is proposing that species somehow know there is a gender imbalance and adjust the gender ratio accordingly. The mechanism in which the species change gender is unknown. Some scientists are suggesting that hormones are released which causes one type of reproductive organs to disappear and another type to appear. For organisms which display this phenomenon, apparently there are chemical triggers that respond to the number of members in a population. This will activate the gene(s) that will allow for the disintegration of one set of reproductive organs and the development of the other. The purpose of this paper is not to study how species technically change gender, but to explore how each individual in the population know the gender ratio and who decides who will change gender and who will not. This paper will build an agent-based model, using Netlogo©, to test the following hypothesis, “each individual in the collective does not have to know the gender ratio of the entire population in order to make decisions that will positively impact the collective.” Results show that individuals change their gender in accordance with their own needs. Regardless of the initial gender ratio and despite the fact that the individuals do not possess knowledge about the whole population, there will always be almost-equal number of males and females after a certain time.

Initiative mapping methodology for system-of- systems applications

In this paper, we propose developing a generic approach to handle different system-of-systems applications, including (1) a framework to map or classify initiatives based on their contribution to different capabilities and (2) introduce an optimisation-based methodology that selects combinations of initiatives that will maximise the contribution to the capabilities, and ultimately maximises the yield or benefit of the entire system. The approach will focus on using subject matter experts to obtain rankings of capabilities. The optimisation of initiative selection will utilise binary integer programming and desirability mapping to ascertain the overall effectiveness of the combined initiatives. After conducting multiple simulation runs at various budget constraints, the ‘heavy hitters’ are dominant and the ‘big losers’ time and time again are not chosen. The resulting selection is a subset of the total number of initiatives, and can be subsequently evaluated in greater detail than trying to evaluate the entire selection and all of the possible combinations.

The information age combat model: a vision for a discrete event simulation approach

Network centric operations (NCO) has been dubbed the most significant revolution in military affairs (RMA) in the past 200 years. The promise of NCO is based on the notion that information sharing and connectivity is fundamental to the effectiveness of a combat force. This is due to the ability of a properly networked force to self-synchronise itself as it engages enemy forces. The information age combat model (IACM) is a popular representation of NCO. Previous research at modelling the IACM has so far focused solely at using agent-based modelling. That work produced significant contributions to the IACM literature. However, it has proven to be computationally expensive. IACM simulations must be sustainable as research into IACM evolves and more NCO complexities are introduced. This research will propose a discrete-event simulation (DES) approach to model the IACM. The paper will present the basis upon which DES was selected for this purpose and will illustrate how the DES approach can provide significant improvements in terms of the time and computational power needed to run IACM simulations.

Using integer partitioning to determine unique configurations for the information age combat model

This paper addresses the number partitioning problem as it relates to the modelling of distributed network operations, as envisioned in the information age combat model (IACM). The approach proposed in this paper is an automated integer partitioning framework implemented using Mathematica and visual basic. This methodology allows the formation of unique configurations by implementing a matrix-based approach proposed by Fidanci (2010). Finding the unique combination is extremely helpful because it aids IACM simulation attempts by eliminating the significant redundancy associated with combat configurations, and therefore, making simulations much more computationally efficient. The results of the integer partitioning and the formation of unique combinations are subsequently used in a combat simulation model of the IACM. Most importantly, the methodology proposed is generalisable and can be adapted to partition any number of distributed networks, symmetric or asymmetric, for systems applications, within the boundaries of current computing technology and time constraints.