research report

Cartesius and CTNET Integration and Field Operational Test

Abstract

This report describes the results of PATH Task Order 5324—the first year of a multi-year project to integrate the Cartesius incident management system with Cal-trans CTNET traffic signal management system. The results of this research are a set of software requirements for reimplementing the Cartesius to interoperate with CTNET. An analysis of the existing Cartesius prototype explains how the need to focus the system on deployment and technical shortcomings of the existing system justifies a reimplementation of the software. From here, we describe the problem to be solved by the new software implementation, including general use cases, the expected users, the systems that Cartesius will interoperate with, and the constraints that will be placed on the system. The problem statement is followed by a detailed discussion of the functional requirements, database requirements, the user interface requirements, and other external interface requirements. The report concludes with a discussion the reimplementation work to be completed under PATHTask Order 6324. This reimplementation will serve the more general purpose of making Cartesius capable of working with existing traffic management subsystems to provide multi-jurisdictional incident mitigation, thus improving its deployability and subsequent value for Caltrans.

Suggested Citation
Craig R. Rindt and Michael G. McNally (2009) Cartesius and CTNET Integration and Field Operational Test. Final Report UCB-ITS-PRR-2009-2. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/1qn7q6zf.

Phd Dissertation

State-Led Housing Planning: Rule Complexity and Implementation Trade-offs

Publication Date

August 1, 2021

Abstract

California’s housing planning system seeks to address housing shortages and promote housing development in areas accessible to transit, jobs, and socioeconomic opportunities. Since 2017, the state Legislature has enacted a set of laws seeking to strengthen the housing planning system through a complex array of standards, requirements, and procedures. California’s current housing planning system is comprised of a complex housing target allocation mechanism and enforcement mechanisms to ensure that local governments effectively accommodate the development of the allocated housing units. However, the complexity of the rules will likely lead to numerous implementation challenges. This dissertation, consisting of three studies, examines the implementation of California’s current housing planning system at different levels of government and highlights the trade-offs related to the complexity of the system. The first essay draws on interview data and observations of public events and underscores the ways in which the complexity of the state’s planning rules has posed implementation challenges related to administrative efficiency, inclusive decision-making, flexibility, legal uncertainty, and legitimacy perceived by different stakeholders. The second essay compares the mechanism that the Southern California Association of Governments (SCAG) uses to allocate housing units to local governments with two simpler alternatives. Through the assessment of different allocation scenarios in the SCAG region, this essay finds evidence that a simpler allocation mechanism could potentially guide housing development to transit- or jobs- rich areas more equitably and with lower administrative burdens. The third essay turns to planning implementation at the local level and examines the trade-offs involved in directing new housing opportunities, especially subsidized housing, away from relatively poor neighborhoods. Focusing on the City of Los Angeles, this essay finds evidence that newly subsidized housing would alleviate residential crowding in single-family neighborhoods but not in relatively crowded, high poverty neighborhoods. The empirical results, however, may be driven by the growing demands for affordable housing units with the appropriate size in these neighborhoods. This dissertation reveals implementation trade-offs that are at least in part due to the complexity of the planning processes and techniques that are required by state law or promoted by government agencies. Current complex rules in place may not necessarily achieve the goal of promoting housing development equitably. Possible directions for improving state-led housing planning efforts involve simplifying the system in a way that reduces the use of administratively complex procedures and the reliance on overly technical approaches. Decision-makers should be aware of the potential trade-offs among different policy objectives and, in some cases, need to recognize that important objectives may conflict.

Suggested Citation
Huixin (Echo) Zheng (2021) State-Led Housing Planning: Rule Complexity and Implementation Trade-offs. PhD Dissertation. UC Irvine. Available at: https://escholarship.org/uc/item/1539m2jf.

published journal article

Travel Probability Fields and Urban Spatial Structure: 2. Empirical Tests

Environment and Planning A: Economy and Space

Publication Date

June 1, 1983

Author(s)

M J Beckmann, Thomas Golob, Y Zahavi

Abstract

The research presented here is a continuation of the work published in a previous issue of this journal. The overall objective was to relate travel patterns and urban structure using continuous spatial distributions and urban-economic concepts of residential location choice. In the present paper, model hypotheses are tested using data from a transportation planning study in Washington.

Suggested Citation
M J Beckmann, T F Golob and Y Zahavi (1983) “Travel Probability Fields and Urban Spatial Structure: 2. Empirical Tests”, Environment and Planning A: Economy and Space, 15(6), pp. 727–738. Available at: 10.1068/a150727.

working paper

A Conflict Model and Interactive Simulator (FASTCARS) for Predicting Enroute Driver Behavior in Response to Real-Time Traffic Condition Information

Abstract

This paper proposes a theoretical methodology and practical data collection approach for modeling enroute driver behavioral choice under Advanced Traveler Information Systems (ATIS). The theoretical framework is based on conflict assessment and resolution theories popularized in psychology and applied to models of individual consumer behavior. It is posed that enroute assessment and adjustment is a reactionary process influenced by increased conflict arousal and motivation to change. When conflict rises to a level at which conflict exceeds a personal threshold of tolerance, drivers are likely to alter enroute behavior to alleviate conflict through either route diversion or goal revision. Assessment and response to conflict arousal directly relate to the driver’s abilities to perceive and predict network conditions in conjunction with familiarity of network configurations and accessible alternate routes.Data collection is accomplished through FASTCARS (Freeway and Arterial Street Traffic Conflict Arousal and Resolution Simulator), an interactive microcomputer-based driving simulator. Limited real-world implementation of ATIS has made it difficult to study or predict individual driver reaction to these technologies. It is contended here that in-laboratory experimentation with interactive route choice simulators can substitute for the lack of real-world applications and provide an alternate approach to data collection and driver behavior analysis. This paper will explain how FASTCARS is useful for collecting data and testing theories of driver behavior.

Suggested Citation
Jeffrey L. Adler, Wilfred W. Recker and Michael G. McNally (1992) A Conflict Model and Interactive Simulator (FASTCARS) for Predicting Enroute Driver Behavior in Response to Real-Time Traffic Condition Information. Working Paper No. 127. Institute of Transportation Studies, UC Irvine: University of California Transportation Center. Available at: https://escholarship.org/uc/item/5044j167.

presentation

Qualitative Assessment of Transit Agencies and Transportation Network Companies in Public-Private Partnership

Suggested Citation
Dylan Ando (2022) “Qualitative Assessment of Transit Agencies and Transportation Network Companies in Public-Private Partnership”. 2022 ITS-Irvine Emerging Scholars Transportation Research Showcase, ITS-Irvine, 28 October. Available at: https://youtu.be/Rpdf6-T_fCk?t=541.

working paper

On-line Traffic Signal Control Scheme with Real-time Delay Estimation Technology

Abstract

This paper presents an on-line signal control scheme integrated with the real-time intersection delay estimation technology. The primary goal of this study is to design a complementary optimization module to the existing controller to minimize the total delay experienced by traffic and improve the system performance at the signalized intersections. This paper proposes a feedback control algorithm that optimizes the signal timing plan based on delay estimated via vehicle re-identification technology. Main thrust of the algorithm is on-line control capability utilizing direct delay measures. A description of overall signal control system architecture and optimization algorithm is given in this paper. Extensive simulation experiments are preformed with a high-performance microscopic traffic simulation program, Paramics, and the preliminary results have proved the promising properties of our proposed system.

conference paper

DOMINO: Domain-Invariant Hyperdimensional Classification for Multi-Sensor Time Series Data

2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)

Publication Date

October 1, 2023

Author(s)

Abstract

With the rapid evolution of the Internet of Things, many real-world applications utilize heterogeneously connected sensors to capture time-series information. Edge-based machine learning (ML) methodologies are often employed to analyze locally collected data. However, a fundamental issue across data-driven ML approaches is distribution shift. It occurs when a model is deployed on a data distribution different from what it was trained on, and can substantially degrade model performance. Additionally, increasingly sophisticated deep neural networks (DNNs) have been proposed to capture spatial and temporal dependencies in multi-sensor time series data, requiring intensive computational resources beyond the capacity of today’s edge devices. While brain-inspired hyperdimensional computing (HDC) has been introduced as a lightweight solution for edge-based learning, existing HDCs are also vulnerable to the distribution shift challenge. In this paper, we propose DOMINO, a novel HDC learning framework addressing the distribution shift problem in noisy multi-sensor time-series data. DOMINO leverages efficient and parallel matrix operations on high-dimensional space to dynamically identify and filter out domain-variant dimensions. Our evaluation on a wide range of multi-sensor time series classification tasks shows that DOMINO achieves on average 2.04% higher accuracy than state-of-the-art (SOTA) DNN-based domain generalization techniques, and delivers 16.34times faster training and 2.89times faster inference. More importantly, DOMINO exhibits notably better performance when learning from partially labeled data and highly imbalanced data, and provides 10.93times higher robustness against hardware noises than SOTA DNNs.

Suggested Citation
Junyao Wang, Luke Chen and Mohammad Abdullah Al Faruque (2023) “DOMINO: Domain-Invariant Hyperdimensional Classification for Multi-Sensor Time Series Data”, in 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD). 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), pp. 1–9. Available at: 10.1109/ICCAD57390.2023.10323848.

published journal article

A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem

Transportation Research Part B: Methodological

Publication Date

May 1, 2017

Abstract

In this paper, the authors mathematically model the multi-hop Peer-to-Peer (P2P) ride-matching problem as a binary program. The authors formulate this problem as a many-to-many problem in which a rider can travel by transferring between multiple drivers, and a driver can carry multiple riders. The authors propose a pre-processing procedure to reduce the size of the problem, and devise a decomposition algorithm to solve the original ride-matching problem to optimality by means of solving multiple smaller problems. The authors conduct extensive numerical experiments to demonstrate the computational efficiency of the proposed algorithm and show its practical applicability to reasonably-sized dynamic ride-matching contexts. Finally, in the interest of even lower solution times, the authors propose heuristic solution methods, and investigate the trade-offs between solution time and accuracy.

Suggested Citation
Neda Masoud and R. Jayakrishnan (2017) “A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem”, Transportation Research Part B: Methodological, 99, pp. 1–29. Available at: 10.1016/j.trb.2017.01.004.

research report

Methodology for generating individual vehicle speed profile for estimating freeway emissions

Publication Date

January 1, 2013
Suggested Citation
Jinheoun Choi, Stephen G Ritchie and Cheol Oh (2013) Methodology for generating individual vehicle speed profile for estimating freeway emissions.

working paper

A Model of Activity Participation Between Household Heads

Publication Date

January 1, 1997

Associated Project

Abstract

A structural model is used to explain activity interactions between heads of households and, in so doing, to explain household demand for travel. The model attempts to capture links between activity participation and associated derived travel, links between activities performed by male and female heads, links between types of travel, and time-budget feedbacks from travel to activity participation. Data for pairs of opposite gender heads of households are o=from the 1994 Portland Activity and Travel Survey. The results suggest that a feedback mechanism should be introduced in trip generation models to reflect the effect of activity frequency and duration on the level of associated travel.