Autonomous Vehicle Public Transportation System: Scheduling and Admission Control

Technology of autonomous vehicles (AVs) is getting mature and many AVs will appear on the roads in the near future. AVs become connected with the support of various vehicular communication technologies and they possess high degree of control to respond to instantaneous situations cooperatively with high efficiency and flexibility. In this paper, we propose a new public transportation system based on AVs. It manages a fleet of AVs to accommodate transportation requests, offering point-to-point services with ride sharing. We focus on the two major problems of the system: scheduling and admission control. The former is to configure the most economical schedules and routes for the AVs to satisfy the admissible requests while the latter is to determine the set of admissible requests among all requests to produce maximum profit. The scheduling problem is formulated as a mixed-integer linear program and the admission control problem is cast as a bilevel optimization, which embeds the scheduling problem as the major constraint. By utilizing the analytical properties of the problem, we develop an effective genetic-algorithm-based method to tackle the admission control problem. We validate the performance of the algorithm with real-world transportation service data.Comment: 16 pages, 10 figure

A Study of the Relationship Between Antivirus Regressions and Label Changes

AntiVirus (AV) products use multiple components to detect malware. A component which is found in virtually all AVs is the signature-based detection engine: this component assigns a particular signature label to a malware that the AV detects. In previous analysis [1-3], we observed cases of regressions in several different AVs: i.e. cases where on a particular date a given AV detects a given malware but on a later date the same AV fails to detect the same malware. We studied this aspect further by analyzing the only externally observable behaviors from these AVs, namely whether AV engines detect a malware and what labels they assign to the detected malware. In this paper we present the results of the analysis about the relationship between the changing of the labels with which AV vendors recognize malware and the AV regressions

Source localization using acoustic vector sensors: a music approach

Traditionally, a large array of microphones is used to localize multiple far field sources in acoustics. We present a sound source localization technique that requires far less channels and measurement locations (affecting data channels, setup times and cabling issues). This is achieved by using an acoustic vector sensor (AVS) in air that consists of four collocated sensors: three orthogonally placed acoustic particle velocity sensors and an omnidirectional sound pressure transducer. Experimental evidence is presented demonstrating that a single 4 channel AVS based approach accurately localizes two uncorrelated sources. The method is extended to multiple AVS, increasing the number of sources that can be identified. Theory and measurement results are presented. Attention is paid to the theoretical possibilities and limitations of this approach, as well as the signal processing techniques based on the MUSIC method

Asymptotic vibrational states of the H-3(+) molecular ion

Vibrational calculations for H-3(+) are performed using an accurate global ab initio potential energy surface. Fourteen bound states close to dissociation are found to have interesting long-range dynamics. These asymptotic vibrational states (AVS) are studied graphically by cuts through their wave functions and by calculating a rotational constant. These AVS, which overlap open system classical trajectories that form half-tori, should lead to an increased density of states near dissociation. Their influence on the infrared near-dissociation spectrum of H-3(+) remains to be determined