conference paper
published journal article
Demand for electric vehicles (EVs), and thus EV charging, has steadily increased over the last decade. Studies suggest that fast-charging facilities are crucial for the EV market. However, there is limited fast-charging infrastructure in most parts of the world to support EV travel, especially long-distance trips. The goal of this study is to develop a stochastic dynamic simulation modeling framework of a regional system of EV fast-charging stations for real-time management and strategic planning (i.e., capacity allocation) purposes. To model EV user behavior, specifically fast-charging station choices, the framework incorporates a multinomial logit station choice model that considers station charging prices, expected wait times, and detour distances. To capture the dynamics of supply and demand at each EV fast-charging station, the framework incorporates a multi-server queueing model in the simulation. The study assumes that multiple fast-charging stations are managed by a single entity (public or private) and that the demand for these stations are interrelated (through the station choice model). To manage the system of stations, this study proposes and tests dynamic demand-responsive price adjustment (DDRPA) schemes based on station queue lengths. The study applies the modeling framework to a system of EV fast-charging stations in Southern California. The computational results indicate that DDRPA strategies are an effective mechanism to balance charging demand across fast-charging stations. Specifically, compared to the no DDRPA scheme case, the quadratic DDRPA scheme reduces average wait time by 26%, increases charging station revenue (and user costs) by 5.8%, while, most importantly, increasing social welfare by 2.7% in the base scenario. Moreover, the study also illustrates that the modeling framework can evaluate the allocation of EV fast-charging station capacity, to identify stations that require additional chargers and areas that would benefit from additional fast-charging stations.
published journal article
conference paper
Off-path packet injection attacks are still serious threats to the Internet and network security. In recent years, a number of studies have discovered new variations of packet injection attacks, targeting critical protocols such as TCP. We argue that such recurring problems need a systematic solution. In this paper, we design and implement PacketGuardian, a precise static taint analysis tool that comprehensively checks the packet handling logic of various network protocol implementations. The analysis operates in two steps. First, it identifies the critical paths and constraints that lead to accepting an incoming packet. If paths with weak constraints exist, a vulnerability may be revealed immediately. Otherwise, based on “secret” protocol states in the constraints, a subsequent analysis is performed to check whether such states can be leaked to an attacker. In the second step, observing that all previously reported leaks are through implicit flows, our tool supports implicit flow tainting, which is a commonly excluded feature due to high volumes of false alarms caused by it. To address this challenge, we propose the concept of attacker-controlled implicit information leaks, and prioritize our tool to detect them, which effectively reduces false alarms without compromising tool effectiveness. We use PacketGuardian on 6 popular protocol implementations of TCP, SCTP, DCCP, and RTP, and uncover new vulnerabilities in Linux kernel TCP as well as 2 out of 3 R’I’P implementations. We validate these vulnerabilities and confirm that they are indeed highly exploitable.
working paper
This paper examines the relationship between urban structure and commuting behavior. Analyzing the 1980 journey-to-work data for the Los Angeles region, this paper has shown that polycenteric density functions fit the actual urban structure better than the conventional monocentric model. This finding indicates the preeminence of accessibilty to major employment centers in location choices.This paper also estimates commute flows implied by the polycentric and monocentric functions. It finds the monocentric model very poor at explaining commuting behavior. The empirical results show that polycentric urban structure increases the urban commute. This finding helps to preserve the assumption that urban workers economize on commuting, and suggests that efforts to promote more efficient urban form, such as the jobs-housing balance policy, have the potential to succeed.
working paper |
Jan 1999
book/book chapter |
Oct 1998
working paper |
Sep 1994
working paper |
Dec 1994
book/book chapter
published journal article
PM2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM2.5 varied by region, time of day, and month. In general, concentrations were higher near the city’s industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.
published journal article
published journal article
With newer technologies, the embedded hardware and software in traditional vehicles and traffic control infrastructure continue to become more interconnected and more vulnerable. To assist in dealing with existing and potential vulnerabilities, we present a novel attack modeling methodology, taxonomy, and metrics (relative average waiting time, average network flow, impacts and rate of changes) to model, simulate, and meaningfully evaluate the security of Intelligent Transportation Systems. We implement our work in two different architectures: 1) Newell’s Car-Following Model with Bounded Acceleration (the BA-Newell Model) in Matlab and 2) Intelligent Driver Model in Veins. Our code is entirely open-sourced and will be maintained so that the ITS community may use it as a tool. We observe that the architectural-related metric values for sample attack simulation results are similar and transferable; where, for example, the rate of change values have range of average distances 1.8-3.5% for network flow impact and 3.3-9.6% for wait time impact.
published journal article
Previous studies using different exposure methods to assess air pollution and breast cancer risk among primarily whites have been inconclusive. Air pollutant exposures of particulate matter and oxides of nitrogen were estimated by kriging (NOx, NO2, PM10, PM2.5), land use regression (LUR, NOx, NO2) and California Line Source Dispersion model (CALINE4, NOx, PM2.5) for 57,589 females from the Multiethnic Cohort, residing largely in Los Angeles County from recruitment (1993–1996) through 2010. Cox proportional hazards models were used to examine the associations between time-varying air pollution and breast cancer incidence adjusting for confounding factors. Stratified analyses were conducted by race/ethnicity and distance to major roads. Among all women, breast cancer risk was positively but not significantly associated with NOx (per 50 parts per billion [ppb]) and NO2 (per 20 ppb) determined by kriging and LUR and with PM2.5 and PM10 (per 10 μg/m3) determined by kriging. However, among women who lived within 500 m of major roads, significantly increased risks were observed with NOx (hazard ratio [HR] = 1.35, 95% confidence interval [95% CI]: 1.02–1.79), NO2 (HR = 1.44, 95% CI: 1.04–1.99), PM10 (HR = 1.29, 95% CI: 1.07–1.55) and PM2.5 (HR = 1.85, 95% CI: 1.15–2.99) determined by kriging and NOx (HR = 1.21, 95% CI:1.01–1.45) and NO2 (HR = 1.26, 95% CI: 1.00–1.59) determined by LUR. No overall associations were observed with exposures assessed by CALINE4. Subgroup analyses suggested stronger associations of NOx and NO2 among African Americans and Japanese Americans. Further studies of multiethnic populations to confirm the effects of air pollution, particularly near-roadway exposures, on the risk of breast cancer is warranted.
