Exploring the Effects of Cooperative Adaptive Cruise Control in Mitigating Traffic Congestion

The aim of this research is to examine the impact of CACC (Cooperative Adaptive Cruise Control) equipped vehicles on traffic-flow characteristics of a multilane highway system. The research identifies how CACC vehicles affect the dynamics of traffic flow on a road network and demonstrates the potential benefits of reducing traffic congestion due to stop-and-go traffic conditions. An agent-based traffic simulation model is developed specifically to examine the effect of these intelligent vehicles on the traffic flow dynamics. Traffic performance metrics characterizing the evolution of traffic congestion throughout the road network, are analyzed. Different CACC penetration levels are studied. The positive impact of the CACC technology is demonstrated and shown that it has an impact of increasing the highway capacity and mitigating traffic congestions. This effect is sensitive to the market penetration and the traffic arrival rate. In addition, a progressive deployment strategy for CACC is proposed and validated

Improving Customer Waiting Time at a DMV Center Using Discrete-Event Simulation

Virginia's Department of Motor Vehicles (DMV) serves a customer base of approximately 5.6 million licensed drivers and ID card holders and 7 million registered vehicle owners. DMV has more daily face-to-face contact with Virginia's citizens than any other state agency [1]. The DMV faces a major difficulty in keeping up with the excessively large customers' arrival rate. The consequences are queues building up, stretching out to the entrance doors (and sometimes even outside) and customers complaining. While the DMV state employees are trying to serve at their fastest pace, the remarkably large queues indicate that there is a serious problem that the DMV faces in its services, which must be dealt with rapidly. Simulation is considered as one of the best tools for evaluating and improving complex systems. In this paper, we use it to model one of the DMV centers located in Norfolk, VA. The simulation model is modeled in Arena 10.0 from Rockwell systems. The data used is collected from experts of the DMV Virginia headquarter located in Richmond. The model created was verified and validated. The intent of this study is to identify key problems causing the delays at the DMV centers and suggest possible solutions to minimize the customers' waiting time. In addition, two tentative hypotheses aiming to improve the model's design are tested and validated

Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles

Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem

This study proposes a novel methodology towards using ant colony optimization (ACO) with stochastic demand. In particular, an optimization-simulation-optimization approach is used to solve the Stochastic uncapacitated location-allocation problem with an unknown number of facilities, and an objective of minimizing the fixed and transportation costs. ACO is modeled using discrete event simulation to capture the randomness of customers' demand, and its objective is to optimize the costs. On the other hand, the simulated ACO's parameters are also optimized to guarantee superior solutions. This approach's performance is evaluated by comparing its solutions to the ones obtained using deterministic data. The results show that simulation was able to identify better facility allocations where the deterministic solutions would have been inadequate due to the real randomness of customers' demands.PublishedN/

Non-familial cardiomyopathies in Lebanon: exome sequencing results for five idiopathic cases

Abstract Background Cardiomyopathies affect more than 0.5% of the general population. They are associated with high risk of sudden cardiac death, which can result from either heart failure or electrical abnormalities. Although different mechanisms underlie the various types of cardiomyopathies, a principal pathology is common to all and is usually at the level of the cardiac muscle. With a relatively high incidence rate in most countries, and a subsequent major health burden on both the families and governments, cardiomyopathies are gaining more attention by researchers and pharmaceutical companies as well as health government bodies. In Lebanon, there is no official data about the spectrum of the diseases in terms of their respective prevalence, clinical, or genetic profiles. Methods We used exome sequencing to unravel the genetic basis of idiopathic cases of cardiomyopathies in Lebanon, a relatively small country with high rates of consanguineous marriages. Results Five cases were diagnosed with different forms of cardiomyopathies, and exome sequencing revealed the presence of already documented or novel mutations in known genes in three cases: LMNA for an Emery Dreifuss Muscular Dystrophy case, PKP2 for an arrhythmogenic right ventricle dysplasia case, and MYPN for a dilated cardiomyopathy case. Interestingly two brothers with hypertrophic cardiomyopathy have a novel missense variation in NPR1, the gene encoding the natriuretic peptides receptor type I, not reported previously to be causing cardiomyopathies. Conclusion Our results unravel novel mutations in known genes implicated in cardiomyopathies in Lebanon. Changes in clinical management however, require genetic profiling of a larger cohort of patients