MS Thesis
This study will evaluate the real causes of phantom traffic jam by evaluating different continuous car-following models under different conditions. Finding the origins of these instabilities would lead to apply some control measures which may solve or minimize the stop and go traffic patterns and improve the whole road performance.
conference paper
The San Pedro Bay Ports (SPBP) of Los Angeles and Long Beach in Southern California is one of the largest port container complexes in the world, and the largest one is the United States. To decrease the air pollution associated with port operations, a number of measures have been adopted, including the Clean Trucks Program, which was introduced in 2008 to modernizing and clean up the fleet of drayage trucks serving the SPBP. The objective of this paper is to quantify the reduction in emissions attributable to the Clean Trucks Program, with a focus on Nitrogen Oxide (NOx) and Particulate Matter (PM2.5). The authors approach is innovative as it relies on micro-simulation (TransModeler) to capture the link between congestion and pollutant emissions. The authors find that the Clean Trucks Program could contribute significantly to the emissions of NOx (~27%) and PM2.5 (~25%) for all the freeway traffic in the study area. These preliminary results suggest that the Clean Trucks Program is promising, but its cost-effectiveness should be analyzed.
published journal article
A study was conducted to determine how demand for clean-fuel vehicles and their fuels is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles. For the purposes of the study, clean-fuel vehicles are defined to encompass both electric vehicles and unspecified (methanol, ethanol, compressed natural gas or propane) liquid and gaseous fuel vehicles, in both dedicated or multiple-fuel versions. The attributes include vehicle purchase price, fuel operating cost, vehicle range between refueling, availability of fuel, dedicated versus multiple-fuel capability and the level of reduction in emissions (compared to current vehicles). In a mail-back stated preference survey, approximately 700 respondents in the California South Coast Air Basin gave their choices among sets of hypothetical future vehicles, as well as their choices between alternative fuel versus gasoline for hypothetical multiple-fuel vehicles. Estimates of attribute importance and segment differences are made using discrete-choice nested multinomial logit models for vehicle choice and binomial logit models for fuel choice. These estimates can be used to modify present vehicle-type choice and utilization models to accommodate clean-fuel vehicles; they can also be used to evaluate scenarios for alternative clean-fuel vehicle and fuel supply configurations. Results indicate that range between refueling is an important attribute, particularly if range for an alternative fuel is substantially less than that for gasoline. For fuel choice, the most important attributes are range and fuel cost, but the predicted probability of choosing alternative fuel is also affected by emissions levels, which can compensate for differences in fuel prices.
published journal article
book/book chapter
published journal article
We analyze the impact of population uncertainty on the socially optimum timing of a congestion-relief project in a linear monocentric city with fixed boundaries, where congestion pricing cannot be implemented. This project requires time to bear fruit but no urban land. Under certainty, we show that utility maximization is roughly equivalent to a standard benefit-cost analysis (BCA). Under Uncertainty, we derive an explicit optimal threshold for relieving congestion when the urban population follows a geometric Brownian motion. If the time to implement the project is short, we show analytically that deciding on the timing of congestion relief based on a BCA could lead to acting prematurely; the reverse holds if project implementation is long and uncertainty is large enough. (c) 2005 Elsevier Inc. All rights reserved.
published journal article
published journal article
Fundamental to many transportation network studies, traffic flow models can be used to describe traffic dynamics determined by drivers’ car-following, lane-changing, merging, and diverging behaviors. In this study, we develop a deterministic queueing model of network traffic flow, in which traffic on each link is considered as a queue. In the link queue model (LQM), the demand and supply of a link queue are defined in the queue size (number of vehicles), and its in- and out-flows are computed from junction flux functions corresponding to macroscopic merging and diverging rules. The new model is a system of ordinary differential equations that is mathematically tractable and computationally efficient and can capture queue spillbacks and interactions among links. We further demonstrate that the LQM is fundamentally different from the cell transmission model (CTM) and link transmission model (LTM) for a road segment, a signalized ring road, and a diverge-merge network, with respect to the shock and rarefaction waves, network fundamental diagram, and stability property. In a sense, the new model is a space-continuous approximation of the kinematic wave model and can be a useful addition to the multiscale modeling framework of network traffic flow. The model has been applied to formulate and solve network traffic control and observation problems.
conference paper
