published journal article
book/book chapter
conference paper
Vehicle classification is the process of separating vehicles according to various predefined classes. Vehicle-classification information can be used in many transportation applications, including road maintenance, emissions/pollution estimation, traffic modeling and simulation, traffic safety, and toll setting. An example of a classification scheme using the following seven vehicle classes is presented: cars, sport-utility vehicles/pickups, vans, limousines, buses, two-axle trucks, and trucks with more than two axles. This system uses vehicle inductive signatures collected from existing loop-detector infrastructure. It also uses a heuristic-discriminant algorithm for classification and a multi-objective optimization for training the heuristic algorithm. Feature vectors obtained by processing inductive signatures are used as inputs into the classification algorithm. Three different heuristic algorithms were developed, yielding encouraging results of 81 to 91 percent overall classification rates. The results demonstrate the potential of collecting network-wide vehicle-classification data from inductive loops. The availability of vehicle-classification data helps to improve traffic surveillance and better defines dynamic traffic networks.
research report
Data from the second year (1979-80) of the Section 15 statistics are used, first to test the validity of a small set of performance indicators for fixed route bus operations, and second to define relatively homogeneous groups of operators (peer groups) that can be compared. Agencies operating 304 bus systems are included. Rail operations were excluded, as were exclusive, demand-responsive operations. The second year data is both more complete and accurate than that reported for the inaugural year. However, data from the magnetic tape had to be reorganized before it could be used with any of the major statistical software packages . A large set of performance variables are analysed with factor analysis to establish seven dimensions of transit performance. Seven marker indicators were chosen rather than the nine proposed in previous research. Cluster analysis is used to create a typology for transit based upon characteristics of operations that are available in the Section 15 statistics. Agency size (measured by total vehicle miles and number of peak vehicles operated), peak to base demand and average bus speed are used to create 12 peer groups. Results from this research confirm the validity of using a small set of indicators to ^represent dimensions of transit performance. They will also allow meanlQ||fuX comparisons between similar systems.
working paper
research report
This study comprises the second year's effort in a research project investigating the impact of labor-management relatfons on productivity and efficiency in urban mass transit. Overall focus of the research is on the impact of four controllable aspects of the labor-management situation (i.e., the legal framework, bargaining structure, the labor-management relationship pattern, and the collective agreement) on four components of transit performance: service effectiveness; service efficiency; employee withdrawal (1.e., turnover, absenteeism and tardiness); and organizational adaptability. The second year's research focused on three topics: (1) the causes and impacts of organizational commitment in lower-level transit employees; (2) the causes and impacts of turnover and absenteeism; and (3) the relationship between bargaining unit structure andi transit performance. Employee commitment to transit organizations had beneficial impacts on service efficiency, organizational adaptability and turnover. The extent of employees' commitment was related, in turn, to satisfaction with several aspects of treatment by the organization. Turnover, in moderate amounts and under appropriate organizational policies, was found to be cost-beneficial. Absenteeism, on the other hand, was found to be costly--an expense that could be reduced by suggested changes in polÃcy. Several common beliefs about the impact of bargaining structure on organizational effectiveness were unsupported.
Phd Dissertation
Organizational scholars usually treat commitment either as a calculative or a moral form of organizational involvement. There has been a parallel schism with respect to etiology, with commitment being seen either as the result of investments in the organizational role or as reciprocation with the organization for the fulfillment of important needs. The latter view implies that individual differences in need structure will act as a moderator. The research is based, in part, on a theory which holds that the saliency of different needs varies with job tenure. Questionnaire data were collected from 881 employees in two hospitals and 28 bank branches to determine whether job tenure moderates the relative impacts of existence, relatedness and growth need fulfillment on organizational commitment. The study also compared the relative utility of the investments and reciprocation models of etiology, vis-a-vis both calculative and moral commitment. Both etiological models accounted for non-redundant variance in organizational commitment. While support was stronger for the reciprocation model, there was a relative gain in support for the investments model when calculative commitment was the dependent variable. No support was found for the hypothesized job-tenure phased differences in the impacts of needs on commitment. Subsidiary analyses of job satisfaction, role stress and manifest need strengths indicated basic patterns in the participant sample at variance with the underlying model of time and work. Non-supportive results were discussed in this context.
published journal article
Analyzing LA Metro’s GoPass fareless pilot program [Saphores], improving transit and complete street operations [Jin], equity-focused modeling and optimization [Jayakrishnan], bicycle ridership modeling [Roy], analyzing urban freeways [DiMento], and analyzing transportation infrastructure and equity [DiMento] align the most with my research interests
