working paper
Archives: Research Products
published journal article
A new methodology for incident detection and characterization on surface streets
Transportation Research Part C: Emerging Technologies
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conference paper
Design and modeling of real-time shared-taxi dispatch algorithms
Proceedings of the 92nd annual meeting of the transportation research board
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Author(s)
Abstract
Taxicabs are certainly the most popular type of on-demand transportation service in urban areas because taxi dispatching systems offer more and better services in terms of shorter wait times and travel convenience. However, a shortage of taxicabs has always been critical in many urban contexts especially during peak hours and taxis have great potential to maximize their efficiency by employing shared-ride concept. There are recent successes in real-time ridesharing projects that are expected to bring substantial benefits on energy consumption and operation efficiency, and thus it is essential to develop advanced vehicle dispatch algorithms to maximize occupancy and minimize travel times in real-time. This paper investigates how taxi services can be improved by proposing shared-taxi algorithms and what type of objective functions and constraints could be employed to prevent excessive passenger detours. Hybrid Simulated Annealing (HSA) is applied to dynamically assign passenger requests efficiently and a series of simulations are conducted with two different taxi operation strategies. The simulation results reveal that allowing ride-sharing for taxicabs increases productivity over the various demand levels and HSA can be considered as a suitable solution to maximize the system efficiency of real-time ride sharing.
Suggested Citation
Jaeyoung Jung, R. Jayakrishnan and Ji Young Park (2013) “Design and modeling of real-time shared-taxi dispatch algorithms”, in Proceedings of the 92nd annual meeting of the transportation research board, p. 20p.conference paper
Battery-aware energy-optimal Electric Vehicle driving management
2015 IEEE/ACM international symposium on low power electronics and design (ISLPED)
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Author(s)
Suggested Citation
Korosh Vatanparvar, Jiang Wan and Mohammad Abdullah Al Faruque (2015) “Battery-aware energy-optimal Electric Vehicle driving management”, in 2015 IEEE/ACM international symposium on low power electronics and design (ISLPED). IEEE, pp. 353–358. Available at: 10.1109/islped.2015.7273539.published journal article
Delayed Deceleration Approach Noise Impact and Modeling Validation
Journal of Aircraft
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Author(s)
Suggested Citation
Jacqueline L. Huynh, Ara Mahseredjian and R. John Hansman (2022) “Delayed Deceleration Approach Noise Impact and Modeling Validation”, Journal of Aircraft, 59(4), pp. 992–1004. Available at: 10.2514/1.C036631.published journal article
GPU architecture aware instruction scheduling for improving soft-error reliability
IEEE Trans. Multi-Scale Comp. Syst.
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Author(s)
Suggested Citation
Haeseung Lee and Mohammad Abdullah Al Faruque (2017) “GPU architecture aware instruction scheduling for improving soft-error reliability”, IEEE Trans. Multi-Scale Comp. Syst., 3(2), pp. 86–99. Available at: 10.1109/tmscs.2017.2667661.Phd Dissertation
House prices, housing tenure, and happiness: Three essays in applied econometrics
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Author(s)
Suggested Citation
Steven John Carter (2009) House prices, housing tenure, and happiness: Three essays in applied econometrics. PhD Dissertation. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_304843706.policy brief
New Tool from UC Irvine Could Save the State Millions while Providing Better Data on Truck Activity in California
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Areas of Expertise
Abstract
The U.S. population is expected to increase to 389 million by 2045 compared to 321 million in 2015, with economic growth doubling in size. Consequently, freight movements are expected to increase by approximately 42 percent by 2040. Among all freight modes, trucks show the largest expected increase in flows by 2040. However, the ability for transportation agencies to understand and adequately plan for increased truck movement and related impacts is extremely limited due to a lack of data on truck travel patterns.The main sources of truck data are truck surveys and truck counts collected by infrastructure-based detectors. Surveys provide detailed information (i.e., truck type, Origin-Destination, weight, and vehicle miles traveled) useful for understanding truck activity pattern by industry or associating freight commodities with specific truck types, but because of low response rates, surveys cannot be utilized to provide the actual quantification of truck activity at the geographical level. In-pavement sensor technologies, such as Weigh-in-Motion (WIM) or Automated Vehicle Classifiers (AVCs), provide point observations, such as truck volumes. These existing data sources are used to model and generate truck path flows (i.e., travel routes) and/or travel time estimations.
Suggested Citation
Andre Tok, Stephen Ritchie and Craig Rindt (2019) New Tool from UC Irvine Could Save the State Millions while Providing Better Data on Truck Activity in California. Policy Brief. UC ITS. Available at: https://doi.org/10.7922/g21834r1.conference paper
Comparative results for positioning with secondary synchronization signal versus cell specific reference signal in LTE systems
Proceedings of the 2017 international technical meeting of the institute of navigation
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Author(s)
Suggested Citation
Kimia Shamaei, Joe Khalife and Zaher M. Kassas (2017) “Comparative results for positioning with secondary synchronization signal versus cell specific reference signal in LTE systems”, in Proceedings of the 2017 international technical meeting of the institute of navigation. Institute of Navigation, pp. 1256–1268. Available at: 10.33012/2017.14885.Phd Dissertation
Transportation and the environment: Essays on technology, infrastructure, and policy
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Associated Project
Author(s)
Abstract
With soaring oil prices and growing concerns for global warming, there is increasing interest in the environmental performance of transportation systems. This dissertation contributes to this growing literature through three independent yet related projects essays that deal with transportation technology, infrastructure, and policy. My first essay analyzes the increasing interest for hybrid cars by Californians based on a statewide phone survey conducted in July of 2004 by the Public Policy Institute of California (PPIC) using discrete choice models. Results suggest that the possibility for single drivers to use hybrid vehicles in HOV lanes is more important than short term concerns for air pollution, support for energy efficiency policies, long term concerns for global warming, education, and income. This suggests that programs designed to improve the environmental performance of individual vehicles need to rely on tangible benefits for drivers; to make a difference, they cannot rely on environmental beliefs alone. The second essay is concerned with assessments of Travel Demand Management (TDM) policies, which have been used to deal with congestion, air pollution, and now global warming. I compare two TDM programs: Rule 2202 (the on-road motor vehicle mitigation options in southern California) and the Commute Trip Reduction Program (CTR) in Washington State. My results show that after 2002, the impacts of Rule 2202 are mixed. Commuters’ modal choices are affected by worksite characteristics but only two (out of six) basic strategies affect the change in average vehicle ridership (AVR). Moreover, the level of subsidies appears to play an important role in commuting behavior. In Washington State, location has an impact on AVR and combinations of location and employee duties influence the single occupancy vehicle index. Details of the CTR and its relative success suggest that there is room for improving Rule 2202 by making it friendlier to businesses and more effective. Finally, I examine the health impacts of NOx (nitrogen oxides) and PM (particulate matter) generated by trains moving freight through the Alameda Corridor to and from the Ports of Los Angeles and Long Beach. After estimating baseline emissions for 2005, I examine two scenarios: in the first one, I assume that all long-haul and switching locomotives are upgraded to Tier 2 (from Tier I); in the second scenario, all Tier 2 locomotives operating in the study area are replaced with cleaner, Tier 3 locomotives. I find that mortality from PM exposure accounts for the largest component of health impacts, with 2005 annual costs from excess mortality in excess of $40 million. A shift to Tier 2 locomotives would save approximately half of these costs while the benefits of shifting from Tier 2 to Tier 3 locomotives would be much smaller. To my knowledge, this is the first comprehensive assessment of the health impacts of freight train transportation in a busy freight corridor.