Phd Dissertation

Physical layer key generation for wireless communication security in automotive cyber-physical systems

Abstract

Modern automotive Cyber-Physical Systems (CPS) are increasingly adopting a variety of wireless communications (Radio Frequency and Visible Light) as a promising solution for challenges such as the wire harnessing problem, collision detection and avoidance, traffic control, and environmental hazards. Regrettably, this new trend results in security challenges that can put the safety and privacy of the automotive CPS and passengers at great risk. Further, automotive wireless communication security is constrained by strict energy and performance limitations of electronic controller units and sensors. As a result, the key generation and management for secure automotive wireless communication is an open research challenge. This thesis aims to help solve these security challenges with a novel key management scheme built upon a physical layer key generation technique that exploits the reciprocity and high spatial and temporal variation properties of the automotive wireless communication channel. A key length optimization algorithm is also developed to help improve performance (in terms of time and energy) for safety-related applications. Channel models, simulations and real-world experiments with vehicles and remote-controlled cars were performed to validate the practicality and effectiveness of the scheme. Lastly, it is shown that generated keys may have high security strength (67% min-entropy for the Radio Frequency domain and high randomness according to NIST tests for the Visible Light domain) and that code size overhead is 20 times less than state-of-the-art security techniques.

Suggested Citation
ANTHONY LOPEZ (2020) Physical layer key generation for wireless communication security in automotive cyber-physical systems. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1gpb62p/alma991034991438504701.

published journal article

An empirical analysis and policy implications of work tours utilizing public transit

Transportation Research Part A: Policy and Practice

Publication Date

December 1, 2020

Abstract

We analyze the complex travel behavior of workers who utilize public transit as part of their work tours (“transit commuters”). Here, complex travel behavior is defined in terms of tours, where a tour is defined as a sequence of trips and activities that begins and ends at the same location and a work tour contains at least one non-home, work activity. The objective of this study is to investigate how transit commuters link non-work activities as part of work tours under transit operational constraints. In particular, we identify dominant patterns of work tours made by transit commuters and analyze these tours using a set of activity-travel analytics and data from the 2017 National Household Travel Survey (NHTS). The primary insights are: (1) about 80 percent of work tours consist of 7 dominant patterns whereas the remaining 20 percent of tours demonstrate a total of 106 diverse and more complicated patterns; (2) half of the transit work tours are complex; (3) most simple tours are transit-only tours whereas most complex tours are multi-modal tours; and (4) transit use is more complex than the traditional home to work commute with a diverse set of choices at various stages of activity scheduling. While policies associated with public transit typically focus only on the journey to work, this study considers the complete set of trips starting and ending at home including intermediate non-work activity, which can provide insights for land use and transit-related policies to better accommodate the complex travel behavior of commuters who utilize transit.

Suggested Citation
Rezwana Rafiq and Michael G. McNally (2020) “An empirical analysis and policy implications of work tours utilizing public transit”, Transportation Research Part A: Policy and Practice, 142, pp. 237–259. Available at: 10.1016/j.tra.2020.10.018.

published journal article

Bicycle streetscapes: a data driven approach to mapping streets based on bicycle usage

International Journal of Sustainable Transportation

Publication Date

August 1, 2023

Author(s)

Trisalyn A. Nelson, Colin Ferster, Avipsa Roy, Meghan Winters
Suggested Citation
Trisalyn A. Nelson, Colin Ferster, Avipsa Roy and Meghan Winters (2023) “Bicycle streetscapes: a data driven approach to mapping streets based on bicycle usage”, International Journal of Sustainable Transportation, 17(8), pp. 931–941. Available at: 10.1080/15568318.2022.2121670.

conference paper

Advancing Gross Vehicle Weight Rating Classification Through the Integration of Inductive Loop and Side Fire Camera System

Proceedings, 104th Annual Meeting of the Transportation Research Board

Publication Date

January 1, 2025

Abstract

Gross Vehicle Weight Rating (GVWR)-based vehicle activity data is widely used in freight planning, fuel efficiency evaluation, and on-road emission estimation. However, a vehicle’s GVWR remains challenging to obtain using existing highway sensor infrastructure. This paper describes a novel approach to acquire GVWR-based classification data through the fusion of two complementary infrastructure-based sensing technologies: inductive loop sensors and side-fire video cameras. While inductive loops are widely deployed in the U.S., they only provide single-dimensional data with limited information. Side-fire cameras can offer richer details to enhance vehicle classification. Accordingly, an open-source intelligence (OSINT) method was used to establish a GVWR-based vehicle dictionary, linking vehicle specifications from online data sources to GVWR classes. A dataset comprising 9,154 vehicle inductive loop signatures paired with images was then collected and annotated according to the pre-defined dictionary. Next, signature-based and image-based classification models were developed for GVWR classification. Each model was designed to function independently. A signature-based GVWR classification model was trained with a multi-layer perceptron (MLP) neural net architecture and optimized through the implementation of a weighted cross-entropy loss function. A two-stage image-based GVWR classification framework was designed to extract vehicle objects and classify them based on the GVWR scheme. Finally, a linear fusion model was implemented to combine the output of the signature- and image-based models to achieve an improvement over each standalone classification model. The sensor fusion framework significantly outperformed each individual sensing technology, achieving an average correct classification rate of 0.97 and an score of 0.96, which surpasses state-of-the-art methods.

Suggested Citation
Guoliang Feng, Yiqiao Li, Andre Tok and Stephen G. Ritchie (2025) “Advancing Gross Vehicle Weight Rating Classification Through the Integration of Inductive Loop and Side Fire Camera System”, in Proceedings, 104th Annual Meeting of the Transportation Research Board. Washington, D.C..

published journal article

Applied decision-analysis - Bunn,Dw

INTERFACES

Publication Date

January 1, 1986

Author(s)

Suggested Citation
L Robin Keller (1986) “Applied decision-analysis - Bunn,Dw”, INTERFACES, 16(5), pp. 119–120.

research report

CARMEN Project 5: Resilience and Validation of GNSS PNT Solutions

Publication Date

November 20, 2023

Author(s)

Todd Humphreys, Qi Alfred Chen, Umit Ozguner, Charles Toth

Areas of Expertise

Suggested Citation
Todd Humphreys, Qi Alfred Chen, Umit Ozguner and Charles Toth (2023) CARMEN Project 5: Resilience and Validation of GNSS PNT Solutions. Final Report. CARMEN UTC. Available at: https://zenodo.org/doi/10.5281/zenodo.10246488 (Accessed: October 10, 2025).

conference paper

HRV: Hybrid routing in vehicular networks

Proceedings of the 92nd annual meeting of the transportation research board

Publication Date

January 1, 2013

Author(s)

Abstract

To improve the quality of wireless communication and extend the application of emerging networking paradigms in Vehicular Ad Hoc Networks (VANETs), we design a hybrid routing scheme for VANETs, called HRV. It presents a holistic solution for inter-vehicle, vehicle-to-roadside, and inter-roadside communications in hybrid urban networks. The combination of roadside unit (RSU) resources and ad hoc networks involves a network coding based multicast routing for dense VANETs, using maximum distance separation (MDS) code and local topology information from the forwarding set to achieve robust communication and max-flow min-cut data transmission; an application of opportunistic routing, using a carry and forward scheme, to solve the forwarding disconnection problem in sparse VANETs; and a routing switch mechanism to guarantee quality of service (QoS) in HRV under various vehicular network connectivity and roadside deployment configurations. The performance of our hybrid routing schemes is evaluated using reliable VANET experiments.

Suggested Citation
Di Wu and Amelia Regan (2013) “HRV: Hybrid routing in vehicular networks”, in Proceedings of the 92nd annual meeting of the transportation research board, p. 18p.

published journal article

Breathing Room: Industrial Zoning and Asthma Incidence Using School District Health Records in the City of Santa Ana, California

International Journal of Environmental Research and Public Health

Publication Date

January 1, 2022

Author(s)

Kelton Mock, Anton M. Palma, Jun Wu, John Billimek, Kim D. Lu

Abstract

Background: Traffic and industrial emissions are associated with increased pediatric asthma morbidity. However, few studies have examined the influence of city industrial zoning on pediatric asthma outcomes among minoritized communities with limited access to air monitoring. Methods: In this cross-sectional analysis of 39,974 school-aged students in Santa Ana, CA, we investigated the effect of proximity to areas zoned for industrial use on pediatric asthma prevalence, physical fitness, school attendance, and standardized test scores. Results: The study population was 80.6% Hispanic, with 88.2% qualifying for free/reduced lunch. Compared to students living more than 1 km away from industrial zones, those living within 0.5 km had greater odds of having asthma (adjusted OR 1.21, 95% CI 1.09 to 1.34, p < 0.001). Among children with asthma, those living between 0.5–1.0 km had greater odds of being overweight or obese (aOR 1.47, 95% CI 1.00, 2.15, p = 0.047). Industrial zone proximity was not significantly associated with worse fitness and academic outcomes for students with asthma. Conclusion: These findings suggest that industrial zone proximity is associated with increased pediatric asthma in a predominantly Latino community in Southern California.

Suggested Citation
Kelton Mock, Anton M. Palma, Jun Wu, John Billimek and Kim D. Lu (2022) “Breathing Room: Industrial Zoning and Asthma Incidence Using School District Health Records in the City of Santa Ana, California”, International Journal of Environmental Research and Public Health, 19(8), p. 4820. Available at: 10.3390/ijerph19084820.

published journal article

An assessment of the political acceptability of congestion pricing

Transportation

Publication Date

December 1, 1992

Abstract

There is renewed interest in implementing congestion pricing in metropolitan areas throughout the US. This paper reviews changes in the transportation policy environment that have led to this renewed interest and identifies the major interest groups that support congestion pricing. A case study is used to demonstrate that significant barriers to congestion pricing implementation continue to exist. The paper concludes with some suggestions for developing politically acceptable pricing alternatives.

Suggested Citation
Genevieve Giuliano (1992) “An assessment of the political acceptability of congestion pricing”, Transportation, 19(4), pp. 335–358. Available at: 10.1007/BF01098638.

conference paper

Learning from Land Use Reforms

2022 APPAM Fall Research Conference

Publication Date

January 1, 2022

Author(s)

Nicholas Marantz, Ingrid Gould Ellen, Betty Xiao Wang, Jenny Schuetz
Suggested Citation
Nicholas Marantz, Ingrid Gould Ellen, Betty Xiao Wang and Jenny Schuetz (2022) “Learning from Land Use Reforms”, in 2022 APPAM Fall Research Conference. APPAM. Available at: https://appam.confex.com/appam/2022/meetingapp.cgi/Session/16706 (Accessed: August 21, 2025).