published journal article
published journal article
Phd Dissertation
A typical urban traffic network is a very complicated large-scale stochastic system which consists of many interconnected signalized traffic intersections. Setting signals at intersections so that the traffic in such a network flows efficiently is a key goal in traffic management. The conventional traffic signal control algorithms assume the traffic system is deterministic; most of them use data aggregation, instead of a mathematical model, and apply off-line, heuristic control strategies which do not respond to the fluctuations of the traffic flows in the network. In this dissertation, the traffic signal control problem is formulated as a decision-making problem for a stochastic dynamical system. Based on Markovian decision theory, a new decentralized optimal control strategy with the embedded platoon dispersion model is developed to minimize the queue length and the steady state delay of traffic networks. A rolling horizon algorithm is also employed to achieve real-time adaptive traffic signal control. Statistical analysis of the computer simulation results for this approach indicates significant improvement over the traditional fully actuated control, especially under the conditions of high, but not saturated, traffic demand.
published journal article
This paper provides new evidence on the link between airline traffic and employment in US metropolitan areas. The evidence confirms the common view that good airline service is an important factor in urban economic development. Frequent service to a variety of destinations, reflected in a high level of passenger enplanements, facilitates easy face-to-face contact with businesses in other cities, attracting new firms to the metro area and stimulating employment at established enterprises. The empirical results show that a 10 per cent increase in passenger enplanements in a metro area leads approximately to a 1 per cent increase in employment in service-related industries. However, airline traffic has no effect on manufacturing and other goods-related employment, suggesting that air travel is less important for such firms than for service-related businesses. These estimates are generated controlling for reverse causality between employment and traffic. The results imply that expansion of Chicago’s O’Hare airport would raise service-related employment in the Chicago metro area by 185 000 jobs (this impact assumes that expansion raises traffic by 50 per cent). Thus, the expansion of O’Hare airport represents a powerful economic development tool, as argued by its proponents.
published journal article
working paper
This paper presents an analysis of the perceptions held by for-hire and private trucking company logistics and operations managers about the impacts of congestion on their operations and the feasibility and effectiveness of actual and potential congestion mitigation policies. Responses to an extensive survey of nearly 1200 California-based or large national carriers are examined using confirmatory factor analysis. The method applied facilitates both the grouping of congestion relief policies into classes and the identification of characteristics of companies which lead them to favor one set of policies over others. This research comes at a time when California government leaders and transportation policy analysts are struggling with key resource allocation issues that will impact the short and long term future of goods movement in the state. To the greatest extent possible, insights of CVO users of the transportation network should be included in the policy analysis process.
working paper |
Jan 2000
working paper |
Nov 1999
conference paper
conference paper
Working from home (WFH) increased tremendously after the outbreak of the COVID-19 pandemic. A critical research need is to understand the associated impacts on travel behavior in the post-pandemic era, particularly on Vehicle Miles Traveled (VMT). In this context, we conceptualized a causal structure to investigate the interrelationships between WFH and VMT by considering non-work trip rates and travel efficiency as mediator variables. Travel efficiency is introduced as a latent factor, defined as a sustainability measure consisting of four indicators: activity-trip ratio, proportion of short-distance trips, proportion of micro-mobility trips, and proportion of travel time in non-auto modes. By applying a Structural Regression model based on the 2022 National Household Travel Survey data, we derived both direct and indirect effects of WFH on VMT. The indirect effect of WFH on VMT via non-work trip rates suggests that the frequency of non-work trips increases with the frequency of WFH, leading to an increase in VMT. On the other hand, the indirect effect of WFH on VMT via travel efficiency revealed that more WFH days induced more sustainable travel choices and thus contributed to reductions in VMT. The direct effect of WFH on VMT appeared negative, and the summation of both direct and indirect effects also resulted in a negative total effect of WFH on VMT. The findings of this study will provide important insights into the WFH arrangements and their impacts on travel behavior from several demand and performance measure perspectives, which will help policymakers formulate relevant post-pandemic transportation policies.
Phd Dissertation
This dissertation research proposes the development and evaluation of a new concept for high-coverage point-to-point transit systems (HCPPT ). Overall, three major contributions can be identified as the core of this research: the proposed scheme design, the development of sophisticated routing rules that can be updated in real-time to implement and optimize the operation of such a design, and the implementation of a multi-purpose simulation platform in order to simulate and evaluate such a design under real network conditions. The design is based on Shuttle-style operations with a large number of deployed vehicles under a coordinated transit system that uses advanced information supply schemes with fast routing and optimization schemes. The system design is rather innovative and ensures that no more than one transfer is needed for the travelers, by using transfer hubs as well as reroutable and non-reroutable portions in the vehicles’ travel plans. It yields flexibility for demand-side benefits from options such as price incentives for time-bound “passenger-pooling” at the stops without destination constraints, by the users. A strict optimization formulation and solution for such a problem is computationally prohibitive in real-time. The design proposed in this dissertation is effectively geared towards a decomposed solution using detailed rules for achieving vehicle selection and route planning. If real-time update of probabilities based upon modeling the future dispatch decisions is included, then this scheme can be considered as a form of quasi-optimal predictive-adaptive control problem. Finally, a multi-purpose simulation platform is developed as part of this research in order to evaluate the performance of the system. The final simulations of HCPPT required point-to-point vehicle simulation, which is not possible with off-the-shelf simulators. The simulation framework uses a well-known microscopic traffic simulator that was significantly modified for demand-responsive vehicle movements and passenger tracking. A simulated case study in Orange County showed that with enough deployed vehicles, the system can be substantially better, even competitive with personal auto travel, compared to the often-unsuccessful traditional DRT systems and the existing fixed route public transit. Furthermore, HCPPT can be incrementally implemented by contracting out services to existing private operators.
published journal article
