published journal article
published journal article
published journal article
Conceptual design and preliminary feasibility simulation results are presented for a flexible transit system for travel from any point to any point based on real-time personalized travel desires, which is now possible because of advances in communications and computing technologies. Although it is demand-responsive, the concept is significantly different from older demand-responsive transit systems, which were often failures. The proposed system requires high coverage, referring to the availability of a large number of transit vehicles (often minibuses or vans), which could also operate in conjunction with private transit and paratransit systems. The design strictly eliminates more than one transfer for any passenger. The system could potentially provide a transit alternative that is much more competitive with personal automobile travel than are conventional transit systems because of significantly lower waiting times. The passenger demand for such a system is uncertain, but preliminary simulations show that under a variety of acceptable demand levels, the system can operate with high cost-effectiveness. The focus is on describing the details of the concept and providing arguments in favor of the system based on simulations. The system essentially attempts to solve a stochastic real-time passenger pickup-and-delivery problem with a large number of vehicles. A strict optimization formulation and solution for such a problem are computationally prohibitive in real time. The design proposed is effectively geared toward a decomposed solution using detailed rules that achieve vehicle selection and route planning. If real-time update of probabilities is included, this scheme could be considered as a form of quasi-optimal stochastic control.
conference paper
research report
The research was undertaken to develop a tool for assessing the impacts of changes in freeway traffic flow on the level of traffic safety. Safety is measured in terms of the probability of a reportable accident, and the tool is so far restricted to urban freeway mainlines with substantial traffic levels. The tool will: (1) monitor the safety level of freeway operations (2) aid in freeway planning. The tool was calibrated by applying advanced statistical models to actual data combined from two sources: Vehicle Detector Station (VDS) data for freeways in Orange County (District 12), and data on all reported accidents in Orange County from the Traffic Surveillance and Analysis System (TASAS). The analytical engine that drives the safety tool is based on models that are highly effective in identifying those myriad aspects of traffic flow that are statistically related to accident probabilities. It is recommended that Caltrans invest in projects that will validate the current work, and subsequently: (1) improve the accuracy of the safety predictions; (2) extend the applicability of the modeling approach to other Caltrans districts; and (3) evaluate the dissemination of safety predictions in real time.
published journal article
working paper
The objective of the research described in this paper is to determine how the use of specific modes of travel affects the relationships between out-of-home activity duration and the travel required for such activities. We proceed by constructing a model that interrelates classes of out-of-home activities and the travel required to participate in these activities, all as a function of population sociodemographic characteristics and the modes of travel used by the population.
working paper |
Jan 1997
book/book chapter |
Oct 1998
working paper |
Sep 1995
working paper |
Jul 1997
book/book chapter
published journal article
The primary strategy for addressing environmental concerns related to global aviation emissions is transitioning to low-carbon propulsion technologies. Hydrogen (H2) offers significant potential as a sustainable fuel, with anticipated zero to low carbon emissions. This study develops a methodological framework that integrates on-site electrolytic H2 production, storage, and transportation for airport applications. For the first time, the techno-economic feasibility of supplying clean liquid hydrogen (LH2) to Los Angeles International Airport (LAX) to support its transition toward sustainable operations by 2050 is comprehensively analyzed. The results underscore the critical role of integrating long-term H2 storage and short-term battery storage solutions to establish a reliable, self-sustained microgrid system at LAX. The estimated levelized cost of hydrogen (LCOH) ranges from $6.77 to $7.10 per kilogram of H2 in 2030, decreasing significantly to approximately $3.78 per kilogram of H2 by 2050, showing the viability of deploying clean H2 at LAX. Additionally, this study, for the first time, quantifies the global warming potential (GWP) of clean H2 supply pathways for airport applications, revealing a range of 0.29 to 0.35 kg CO2-eq/kg H2 by 2050, with H2 venting from electrolysis identified as the dominant contributor. The findings emphasize the feasibility of H2 as a sustainable aviation fuel and provide actionable strategies for its implementation at LAX. This work advances the hydrogen aviation field by bridging the gap between the general clean H2 supply chain strategies and the specific needs of the aviation sector, thereby contributing to California’s ambitious climate goals. Future research is recommended to address limitations in cost optimization, lifecycle impacts, policy incentives, and safety innovations, enabling the scalable and practical implementation of H2 as a sustainable aviation fuel at airports.
published journal article
An approach to real-time control of a network of signalized intersections is proposed based on a discrete time, stationary, Markov control model (also known as Markov decision process or Markov dynamic programming). The approach incorporates microscopic simulation of actuated controller output signals in response to probabilistic forecasts of individual vehicle actuations at downstream inductance loop detectors derived from a macroscopic link transfer function. An Artificial Neural Network representation of vehicle delay estimations is proposed and tested for approximate real-time evaluation of potential traffic signal transitions at three-second evaluation intervals. A series of off-line tests of the developed procedures are applied to a simplified network of five intersections; these tests provide promising indications of this approach.
