Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping

Adversarial examples generated by a surrogate model typically exhibit limited transferability to unknown target systems. To address this problem, many transferability enhancement approaches (e.g., input transformation and model augmentation) have been proposed. However, they show poor performances in attacking systems having different model genera from the surrogate model. In this paper, we propose a novel and generic attacking strategy, called Deformation-Constrained Warping Attack (DeCoWA), that can be effectively applied to cross model genus attack. Specifically, DeCoWA firstly augments input examples via an elastic deformation, namely Deformation-Constrained Warping (DeCoW), to obtain rich local details of the augmented input. To avoid severe distortion of global semantics led by random deformation, DeCoW further constrains the strength and direction of the warping transformation by a novel adaptive control strategy. Extensive experiments demonstrate that the transferable examples crafted by our DeCoWA on CNN surrogates can significantly hinder the performance of Transformers (and vice versa) on various tasks, including image classification, video action recognition, and audio recognition. Code is made available at https://github.com/LinQinLiang/DeCoWA.Comment: AAAI 202

Modeling multi-modal network equilibrium with active transportation and shared mobility

The imbalance between increasing travel demand by passengers and the stagnant growth of transportation infrastructure capacity, particularly in urban areas, has caused dramatic impacts on traffic congestion, the environment, public health, and energy efficiency. Consequently, the development of sustainable and resilient transportation systems has become an increasingly challenging task. Travel demand management (TDM) is a set of strategies aimed at redistributing travel demand in time or space to alleviate the imbalance between travel demand and available infrastructure capacities. Active transportation (AT), which includes walking and cycling, has emerged as a popular TDM approach in modern urban areas, with the potential to reduce vehicular travel (VT) demand and alleviate traffic congestion. However, potential barriers such as longer commuting times and adverse health effects, including exposure to hazardous air pollution and traffic injuries, often dissuade travelers from choosing AT. Therefore, understanding the complex relationship between AT and VT demand is crucial, especially when considering the health effects associated with these modes of transportation, such as the negative impact of air pollution and the benefits of physical activity.Nevertheless, it is important to acknowledge that modeling active transportation in urban areas without considering the influence of Transportation Network Companies (TNCs), particularly the effects of enhancing vehicle occupancy through e-pooling and express pool services, can lead to biased findings. Hence, in this study, I model the AT and VT traveling modes in a multi-modal network problem taking into account TNC services, such as, e-hailing, e-pooling, and express pool. The objective is to analyze passengers' choices among active transportation, solo driving, and TNC services, considering various trade-offs related to health, monetary, time, and inconvenience costs, and their subsequent impacts on traffic network performance. Given the non-separable and asymmetric nature of the disutility functions associated with multi-modal travel modes, the problem is formulated as a mixed complementarity problem. Accordingly, the discussion the existence and uniqueness of solution(s) are conducted based on the properties of equilibrium models in my dissertation.By utilizing the proposed mathematical model, the study aims to assess the market share of active transportation, solo driving, and TNC modes at the equilibrium state, providing valuable insights for policymakers seeking to enhance mobility, energy efficiency, public health, and environmental outcomes. These components are integral to the establishment of a sustainable transportation system

A Comparative Analysis of Alternative Travel Time Data Sources on I-80 Freeway

Final ReportThis study evaluates the accuracy of the travel time data that are estimated by Dual loop, Waze, HERE, and INRIX against Bluetooth data on multiple segments of the I-80 freeway between Davis and Sacramento, CA. We conduct a simulation-based critical sampling rate analysis, which suggests that the Bluetooth travel time data qualifies for approximating the ground truth. Further, we apply evaluation methods and derived indices, Travel Time Error Bias (TEB), Average Absolute Travel Time Error (ATE), and Standard Error of Mean (SEM), to compare the travel time data reported by Waze, HERE, and INRIX with the benchmark (Bluetooth) data on the selected testing segments on I-80. The results show that the INRIX and HERE data closely match the Bluetooth data, both in the trends and values of reported travel time. Moreover, all three vendors’ data accuracy deteriorates when the traffic congestion intensifies.California Department of Transportation 69A355174711

Assessing the health impact of proposed congestion pricing plan for downtown San Francisco

Final ReportCongestion pricing (CP) is seen as a viable solution to urban traffic congestion, but its impact on public health also deserves to be evaluated before implementation. In this study, we assessed several congestion pricing schemes proposed for the San Francisco downtown area from a health perspective. We compare the eight proposed CP schemes with baseline scenario (no-action) to observe the health effects from physical activity (PA), fine inhalable particles matter (PM) exposure, and road traffic injuries (RTI) three pathways using the Integrated Transport and Health Impact Model (ITHIM). The results of the study show that these CP schemes all have a beneficial effect on the public health of San Francisco. Finally, we recommend further research on TNC travel fees in these CP schemes and explore the potential for health improvements on physical activity by encouraging people to use active modes of transport.U.S. Department of Transportation 69A355174711

Investigating the Health Effect of the Citi Bike Bike-sharing Program in New York City Using the ITHIM Health Assessment Tool

Final ReportBike travel is often considered as a healthy and environmentally friendly mode of travel and promoted by cities. Bike sharing, as a bike usage boosting program, invigorates these advantages. However, as usage of it rises, so do the adverse effects on cyclists’ physical well-being, such as hazardous air exposure and bicycle involved accidents. The net health benefits of bike-sharing programs are therefore not clear cut and are worthy of studying case by case. This paper focuses on the Citi Bike Bike-sharing program in New York City. We evaluate the health effect of it using a modified Integrated Transport Health Impact Model (ITHIM) by assessing and comparing the risks of two proposed scenarios: with-Citi bike scenario (baseline) and without-Citi bike scenario (hypothetical). The baseline scenario corresponds to the actual traffic and health condition in 2017, while we split the Citi Bike trips to other modes according to the NYC travel survey data to construct the hypothetical scenario. For each scenario, we investigate the overall health effects of the Citi Bike from three pathways: physical activity, hazardous air exposure, and road traffic injuries. The result indicates that the implementation of Citi Bike plays a positive role in improving the public health. By conducting a sensitivity study, we delve into the potential benefits of the Citi Bike under some possible policy outcomes. Finally, we discuss the strength and limitation of the study, and provide the future study directions.U.S. Department of Transportation 69A355174711