published journal article

Arterial bus lane warrants

Australian Road Research

Publication Date

January 1, 1978

Author(s)

Suggested Citation
S.G. Ritchie (1978) “Arterial bus lane warrants”, Australian Road Research, 8(4), pp. 63–67.

conference paper

An approximate least-square Monte-Carlo algorithm for solving the multi-period continuous network design problem

Proceedings of the 97th annual meeting of the transportation research board

Publication Date

January 1, 2018

Abstract

This paper proposes a new algorithm to solve the Multi-period Continuous Network Design Problem (MPCNDP) in a real options framework. The MPCNDP aims to find the long-term optimal highway expansion plan for a road network with stochastic demand. Analytical methods, finite difference methods or Least Square Monte Carlo simulation (LSMC) are not applicable for solving the MPCNDP because of the high dimension of the stochastic demand variables and the complexity of the intrinsic complexity of the network design problem. The authors propose an algorithm, which they call â??Approximate Least Square Monte Carlo simulationâ?? (ALSMC). This algorithm applies least square regression to estimate the value of the termination payoff function without knowing the optimal capacity improvement plan. During each iteration, only a multi-period CNDP with deterministic demand needs to be solved, which dramatically reduces the computing time of each termination payoff function. The authors first test the ALSMC method on a simple example for which the exact solution is known, and show that it converges quickly to the solution. They then test the ALSMC method on a small network with 6 centroids and 16 links, which has been used as a benchmark in dozens of papers. The authors find that the ALSMC method gives quick and reasonably accurate estimates of the termination payoff function.

Suggested Citation
Ke Wang and Jean-Daniel M. Saphores (2018) “An approximate least-square Monte-Carlo algorithm for solving the multi-period continuous network design problem”, in Proceedings of the 97th annual meeting of the transportation research board, p. 18p.

Phd Dissertation

Disaggregate Control of Vehicles Using In-Vehicle Advisories and Peer-to-Peer Negotiations

Abstract

Traffic advisories to travelers are based upon traffic state information at the link level. This is due to existing infrastructure which sometimes can only provide link-level information. However, the primary justification for providing link-level data is the reluctance of Traffic Management Agencies to consider more detailed traffic state data for operational and safety reasons. However, with the advances in automotive technology, sensing equipment, and the Internet of Things (IoT), we can do better. Research shows that faster and more accurate travel paths can be obtained by using lane data rather than link data. Our contention is that for vehicles to be able to change lanes to improve their travel times, operationally, they would need to enter into Peer-to-Peer negotiations with surrounding vehicles, where they can trade their position in time and space in accordance to their own perceptions of their values of time and satisfaction and possibly in exchange for monetary benefits. Our work is an exploration of this idea. We begin with a simple in-vehicle advisory control policy, partially inspired by the Kinetic theory of traffic. We then move towards an individual-level Peer-to-Peer negotiated lane change framework by first investigating its efficacy by means of microsimulation studies. We then propose an agent-based optimization framework for this system, which minimizes both travel time and the ”envy” induced among drivers when they are assigned paths that are inferior to their peers. Numerical results from running our optimization on an illustrative network show that the proposed model converges to both envy-free and system optimum traffic states, even at a net zero budget, meaning this system can be used by transportation agencies without exacting tolls or giving subsidies. Our proposed framework of routing vehicles on a lane to lane basis can only be realized in the field if the mediating agency (TMC, or a mobility service) has accurate information about traffic conditions. We propose multiple algorithms, including a LSTM (Long Short Term Memory) neural network architecture-based framework to estimate traffic states solely using information collected from sensor-equipped probe vehicles, without the need for any other data such as those obtained from traditional embedded loop detectors.

Suggested Citation
Riju Lavanya (2021) Disaggregate Control of Vehicles Using In-Vehicle Advisories and Peer-to-Peer Negotiations. Ph.D.. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991035329679004701 (Accessed: October 12, 2023).

conference paper

A Practical Method to Adjust Bus Routes Based on Transfer Penalties Using Trip-Chain Data and SP Survey

100th Transportation Research Board (TRB) Annual Meeting

Publication Date

January 1, 2021

Author(s)

Younghun Bahk, Kwangho Baek, Jin-Hyuk Chung
Suggested Citation
Younghun Bahk, Kwangho Baek and Jin-Hyuk Chung (2021) “A Practical Method to Adjust Bus Routes Based on Transfer Penalties Using Trip-Chain Data and SP Survey”. 100th Transportation Research Board (TRB) Annual Meeting, Washington, DC.

conference paper

1 Dual-Horizon Forecasts and Repositioning Strategies for Operating Shared 2 Autonomous Mobility Fleets

99th Annual Meeting of the Transportation Research Board

Publication Date

August 1, 2019

Author(s)

Florian Dandl, Michael Hyland, Klaus Bogenberger, Hani Mahmassani
Suggested Citation
Florian Dandl, Michael F. Hyland, Klaus Bogenberger and Hani S Mahmassani (2019) “1 Dual-Horizon Forecasts and Repositioning Strategies for Operating Shared 2 Autonomous Mobility Fleets”. 99th Annual Meeting of the Transportation Research Board. Available at: https://mediatum.ub.tum.de/doc/1543181/document.pdf.

published journal article

Comments

Brookings-Wharton Papers on Urban Affairs

Publication Date

January 1, 2000

Author(s)

Jan Brueckner, Douglas Holtz-Eakin
Suggested Citation
Jan K. Brueckner and Douglas Holtz-Eakin (2000) “Comments”, Brookings-Wharton Papers on Urban Affairs, 2000(1), pp. 267–273. Available at: 10.1353/urb.2000.0014.

working paper

Structural Models of the Effects of the Commute Trip on Travel and Activity Participation

Publication Date

November 1, 1991

Associated Project

Author(s)

Thomas Golob, Ram Pendyala

Working Paper

UCI-ITS-WP-91-15, UCI-ITS-AS-WP-91-1

Areas of Expertise

Abstract

Travel demand is viewed as being derived from the demand for out-of-home activities. The journey to work can have a significant impact on the travel and activity patterns of workers and other household members. The objective of this research is to model the relationships between travel and activity participation and examine how these relationships are influenced by the time a worker spends commuting between home and his or her worksite. Causal hypotheses are tested using data from approximately 140 workers who responded to two waves of a panel survey collected as part of the State of California Telecommuting Pilot Project. These data contain detailed descriptions of all travel by the survey respondents over three working days in each of two years, 1988 and 1989. A structural equations model is specified in which the durations of four exhaustive categories of out-of-home activities – work, personal business, shopping and social/recreation -generate needs for time spent traveling, and durations and travel times are interrelated in a complex causal structure. The effects of the reduction in travel times for work by telecommuters in the second wave of the panel are captured in terms of additional structural parameters. Results indicate that telecommuting leads directly to increases in shopping activities and decreases in travel for social/recreational activities, and leads indirectly to changes in travel for all purposes. A general modeling framework in which activities and travel relationships can be studied is also discussed.

Suggested Citation
Thomas F. Golob and Ram M. Pendyala (1991) Structural Models of the Effects of the Commute Trip on Travel and Activity Participation. Working Paper UCI-ITS-WP-91-15, UCI-ITS-AS-WP-91-1. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/3hq9m5hp.

published journal article

Associations between green space and preterm birth: Windows of susceptibility and interaction with air pollution

Environment International

Publication Date

September 1, 2020

Author(s)

Yi Sun, Paige Sheridan, Olivier Laurent, Jia Li, David A. Sacks, Heidi Fischer, Yang Qiu, Yu Jiang, Ilona S. Yim, Luo-Hua Jiang, John Molitor, Jiu-Chiuan Chen, Tarik Benmarhnia, Jean M. Lawrence, Jun Wu

Abstract

Background Recent studies have reported inconsistent associations between maternal residential green space and preterm birth (PTB, born < 37 completed gestational weeks). In addition, windows of susceptibility during pregnancy have not been explored and potential interactions of green space with air pollution exposures during pregnancy are still unclear. Objectives To evaluate the relationships between green space and PTB, identify windows of susceptibility, and explore potential interactions between green space and air pollution. Methods Birth certificate records for all births in California (2001–2008) were obtained. The Normalized Difference Vegetation Index (NDVI) was used to characterized green space exposure. Gestational age was treated as a time-to-event outcome; Cox proportional hazard models were applied to estimate the association between green space exposure and PTB, moderately PTB (MPTB, gestational age < 35 weeks), and very PTB (VPTB, gestational age < 30 weeks), after controlling for maternal age, race/ethnicity, education, and median household income. Month-specific green space exposure was used to identify potential windows of susceptibility. Potential interactions between green space and air pollution [fine particulate matter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3)] were examined on both additive and multiplicative scales. Results In total, 3,753,799 eligible births were identified, including 341,123 (9.09%) PTBs, 124,631 (3.32%) MPTBs, and 22,313 (0.59%) VPTBs. A reduced risk of PTB was associated with increases in residential NDVI exposure in 250 m, 500 m, 1000 m, and 2000 m buffers. In the 2000 m buffer, the association was strongest for VPTB [adjusted hazard ratio (HR) per interquartile range increase in NDVI: 0.959, 95% confidence interval (CI): 0.942–0.976)], followed by MPTB (HR = 0.970, 95% CI: 0.962–0.978) and overall PTB (HR = 0.972, 95% CI: 0.966–0.978). For PTB, green space during the 3rd − 5th gestational months had stronger associations than those in the other time periods, especially during the 4th gestational month (NDVI 2000 m: HR = 0.970, 95% CI: 0.965–0.975). We identified consistent positive additive and multiplicative interactions between decreasing green space and higher air pollution. Conclusion This large study found that maternal exposure to residential green space was associated with decreased risk of PTB, MPTB, and VPTB, especially in the second trimester. There is a synergistic effect between low green space and high air pollution levels on PTB, indicating that increasing exposure to green space may be more beneficial for women with higher air pollution exposures during pregnancy.

Suggested Citation
Yi Sun, Paige Sheridan, Olivier Laurent, Jia Li, David A. Sacks, Heidi Fischer, Yang Qiu, Yu Jiang, Ilona S. Yim, Luo-Hua Jiang, John Molitor, Jiu-Chiuan Chen, Tarik Benmarhnia, Jean M. Lawrence and Jun Wu (2020) “Associations between green space and preterm birth: Windows of susceptibility and interaction with air pollution”, Environment International, 142, p. 105804. Available at: 10.1016/j.envint.2020.105804.

published journal article

Household activity pattern problem with automated vehicle-enabled intermodal trips

Transportation Research Part C: Emerging Technologies

Abstract

Driverless or fully automated vehicles (AVs) are expected to fundamentally change how individuals and households travel and how vehicles use roadway infrastructure. The first goal of this study is to develop a modeling framework of activity-constrained household travel in a future multi-modal network with private AVs, shared-use AVs, transit, and intermodal AV-transit travel options. The second goal is to analyze the potential impacts of AVs—including intermodal AV-transit travel—on (a) household-level travel behavior, (b) household travel costs, (c) demand for transport modes, including transit, and (d) vehicle kilometers traveled or VKT. To meet the first goal, we propose and formulate the Household Activity Pattern Problem with AV-enabled Intermodal Trips (HAPP-AV-IT) that incorporates AV deadheading and intermodal AV-transit trips. The modeling framework extends prior HAPP-based formulations that model household-level travel decisions as vehicle (and person) routing and scheduling problems, similar to the pickup and delivery problem with time-windows. To meet the second goal, we apply the HAPP-AV-IT to two case studies and conduct many computational experiments. We use synthetic activity location data for synthetic households and a fictitious medium-size network with a road network, transit network, residential locations, activity locations, and parking locations. The computational results illustrate (a) the critical role that household AV ownership plays in terms of household travel decisions, modal demand, and VKT, (b) that with AVs, deadheading accounts for 30–40 % of vehicle operating distances, (c) that around 10 % of households in the study region benefit from AV-based intermodal trips, and (d) that those 10 % of households see 5 % reductions in household travel costs and 25 % reductions in VKT on average in the most transit friendly scenario. This last finding suggests that intermodal AV-transit trips may exist in a driverless vehicle future, and therefore, transit agencies and transportation planners should consider how to serve this market. We also propose and test a simple heuristic algorithm that quickly solves HAPP-AV-IT problem instances.

Suggested Citation
Younghun Bahk and Michael Hyland (2025) “Household activity pattern problem with automated vehicle-enabled intermodal trips”, Transportation Research Part C: Emerging Technologies, 170, p. 104930. Available at: 10.1016/j.trc.2024.104930.