published journal article
Real-time estimation of accident likelihood for safety enhancement
Journal of transportation engineering
Publication Date
January 1, 2005
Archives: Research Products
working paper
State and National VMT Estimates: It Ain't Necessarily So
Publication Date
September 5, 1994
Associated Project
Author(s)
Working Paper
UCI-ITS-WP-94-3, UCTC 231
Areas of Expertise
Abstract
The enormous jump in vehicle miles traveled (VMT) reported by the 1990 U.S. Nationwide Personal Transportation Survey (NPTS) caused a great deal of concern among planners and policy analysts. Such a jump seemed to portend an era of ever increasing travel, pollution and energy consumption.This paper re-analyses the NPTS data and shows that the VMT jump was a statistical error. The 1990 NPTS oversampled new vehicles and undersampled old ones. Since new vehicles are driven two to three times as much as old one, the sampling bias will overestimate VMT. And the result may have been intensified by an underestimate of VMT in the 1983 NPTS, thus increasing the apparent jump form 1983 to 1990.I also calculate alternative VMT estimates using data from two other national surveys and a massive odometer-based California study. The three new estimates are in close agreement with each other. I conclude that VMT per vehicle actually grew at only half the rate estimated by the NPTS.
Suggested Citation
Charles Lave (1994) State and National VMT Estimates: It Ain't Necessarily So. Working Paper UCI-ITS-WP-94-3, UCTC 231. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/5527j8dj.Related Publications
working paper |
Dec 1994
Hazard Models of Changing Household Demographics
working paper |
Sep 1994
Population and Employment Densities: Structure and Change
working paper |
Oct 1993
Ameliorating Congestion by Income Redistribution
working paper |
Jan 1997
Economics and Urban Transportation Policy in the United States
book/book chapter |
Oct 1998
Project Evaluation
Preprint Journal Article
SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving
Publication Date
July 19, 2024
Author(s)
Chen Ma, Ningfei Wang, Zhengyu Zhao, Qi Alfred Chen, Chao Shen
Abstract
Autonomous Driving (AD) systems critically depend on visual perception for real-time object detection and multiple object tracking (MOT) to ensure safe driving. However, high latency in these visual perception components can lead to significant safety risks, such as vehicle collisions. While previous research has extensively explored latency attacks within the digital realm, translating these methods effectively to the physical world presents challenges. For instance, existing attacks rely on perturbations that are unrealistic or impractical for AD, such as adversarial perturbations affecting areas like the sky, or requiring large patches that obscure most of a camera’s view, thus making them impossible to be conducted effectively in the real world. In this paper, we introduce SlowPerception, the first physical-world latency attack against AD perception, via generating projector-based universal perturbations. SlowPerception strategically creates numerous phantom objects on various surfaces in the environment, significantly increasing the computational load of Non-Maximum Suppression (NMS) and MOT, thereby inducing substantial latency. Our SlowPerception achieves second-level latency in physical-world settings, with an average latency of 2.5 seconds across different AD perception systems, scenarios, and hardware configurations. This performance significantly outperforms existing state-of-the-art latency attacks. Additionally, we conduct AD system-level impact assessments, such as vehicle collisions, using industry-grade AD systems with production-grade AD simulators with a 97% average rate. We hope that our analyses can inspire further research in this critical domain, enhancing the robustness of AD systems against emerging vulnerabilities.
Suggested Citation
Chen Ma, Ningfei Wang, Zhengyu Zhao, Qi Alfred Chen and Chao Shen (2024) “SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving”. arXiv. Available at: 10.48550/arXiv.2406.05800. published journal article
Performance indicators for transit management
Transportation
Publication Date
December 1, 1978
Associated Project
Author(s)
Areas of Expertise
Suggested Citation
Gordon J. Fielding, Roy E. Glauthier and Charles A. Lave (1978) “Performance indicators for transit management”, Transportation, 7(4), pp. 365–379. Available at: 10.1007/BF00168037.Related Publications
working paper |
Sep 1978
Performance Indicators for Transit Management
research report |
Dec 1977
Development of performance indicators for transit
conference paper
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Publication Date
January 1, 2022
Author(s)
Qingzhao Zhang, Shengtuo Hu, Zhe (Jared) Sun, Qi Alfred Chen, Z. Morley Mao
Suggested Citation
Qingzhao Zhang, Shengtuo Hu, Jiachen Sun, Qi Alfred Chen and Z. Morley Mao (2022) “On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles”. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 15159–15168. Available at: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_On_Adversarial_Robustness_of_Trajectory_Prediction_for_Autonomous_Vehicles_CVPR_2022_paper.html (Accessed: October 5, 2023). Phd Dissertation
Dynamic discrete demand modeling of commuter behavior
Publication Date
January 1, 1994
Author(s)
Areas of Expertise
Abstract
The level and extent of demand for a transportation service, including the determinants of the demand, can be meaningfully analyzed only by incorporating their evolution over time. Since most travel demand models are based on cross-sectional data, longitudinal analytic methods need to be developed for the study of travel behavior. Heterogeneity and non-stationarity of behavior, lagged effects, and effect of time varying variables are other factors that require using dynamic modeling techniques. A dynamic beta-logistic model using a panel data set of approximately 2,200 Southern California commuters was developed to fulfill this need. Waves 1, 5, and 8 of this panel, which encompasses a period beginning February, 1990 to February, 1993 was used. Seventy five percent of Waves 1 and 5 data were randomly sampled for model development. The remaining 25 percent as well as the data from Wave 8 were used in model validation. The model had a successful prediction rate of about 98.6% for the two two-wave periods between Waves 1 and 5 and between Waves 5 and 8. Policy simulations were carried with Waves 5 and 8 data. For policy simulation, the impact on ride-sharing of reserved parking, cost subsidy, and guaranteed ride home incentives were studied. An increase of over 100% in the usage of shared-ride mode in Waves 5 and 8 was predicted when all respondents were simulated to have perceived a set of three incentives in both waves. This increase in the shared-ride alternative corresponded to a decrease of over 42% in the usage of the drive-alone modes in both waves. There was a decrease of about 35% in the drive-alone alternative when the three incentives were perceived by all commuters only in Wave 5. If the three incentives were perceived by all commuters in Wave 8 only, the drop in solo-driving in the two-wave period was only 7.1%, which demonstrates the existence of lagged and delayed effects in travel behavior. Of the three incentives guaranteed ride home induces the biggest reduction in the use of the drive-alone alternative.
Suggested Citation
Mandar Khanal (1994) Dynamic discrete demand modeling of commuter behavior. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1go3t9q/alma991035092932604701. conference paper
Resource-Sharing Behavior During Flooding Events: A Latent Class Analysis to Guide Community-Based Relief Distribution
Transportation Research Board 103rd Annual Meeting
Publication Date
January 1, 2024
Author(s)
C. Y. Chou, Elisa Borowski, A Stathopolous
Suggested Citation
C. Y. Chou, Elisa Borowski and A Stathopolous (2024) “Resource-Sharing Behavior During Flooding Events: A Latent Class Analysis to Guide Community-Based Relief Distribution”. Transportation Research Board 103rd Annual Meeting.
presentation
Spatial Equity of Electric Vehicle Charging Station Placements in Orange County, CA
Publication Date
March 7, 2023
Associated Project
Author(s)
Suggested Citation
Mankin Law (2023) “Spatial Equity of Electric Vehicle Charging Station Placements in Orange County, CA”. 2023 ITS-Irvine Emerging Scholars Transportation Research Showcase, ITS-Irvine, 7 March. Available at: https://youtu.be/OCt7zCBv5nk?t=4620.Related Publications
conference paper |
Jan 2023
Spatial Equity of Electric Vehicle Charging Station Placements in Orange County, CA
102nd Transportation Research Board Annual Meeting 2023
published journal article |
Aug 2022
Examining spatial disparities in electric vehicle charging station placements using machine learning
Sustainable Cities and Society
published journal article
Data-Driven Methodology Characterizing CO2 Emission Discrepancies Between Actual and Optimum Operations
Journal of Air Transportation
Publication Date
June 2, 2025
Author(s)
Eva Cobos-Cuesta, Trinity Lee, Jacqueline (Jacquie) Huynh
Abstract
This paper presents a data-driven methodology for estimating and comparing fuel consumption inefficiencies and CO2 emissions in the aviation sector, with a focus on improving environmental sustainability from the Air Navigation Service Provider (ANSP) perspective and contributing to decarbonization goals by emphasizing the establishment of new performance indicators for assessing the environmental impact of ANSPs. The methodology involves predicting the fuel consumption of actual flight trajectories from publicly available historical surveillance and weather data and comparing it to that of each flight’s respective performance-optimal trajectory using a multivariate regression factor weighting analysis. A case study of Airbus A320 flights between LAX and SFO is used to demonstrate the methodology’s effectiveness, including the development of a representative performance indicator for this aircraft type and flight route. The results show a significant relationship between predictor variables such as differences in altitude, distance, time, and wind between actual and optimal trajectories, with differences in distance, which ANSPs can control, being identified as the most influential factor. The methodology has the potential to enhance aviation efficiency and reduce CO2 emissions by providing a framework for evaluating the impact of ANSPs on environmental performance and offering insights for optimizing operational trajectories.
Suggested Citation
Eva Cobos-Cuesta, Trinity Lee and Jacqueline Huynh (2025) “Data-Driven Methodology Characterizing CO2 Emission Discrepancies Between Actual and Optimum Operations”, Journal of Air Transportation, pp. 1–13. Available at: 10.2514/1.D0460. published journal article
Greenhouse Gas Emission Targets and Mass Transit: Can the Government Successfully Accomplish Both without a Conflict
Santa Clara Law Review
Publication Date
January 1, 2011
Author(s)
Darren A Prum, Sarah Catz