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Open Access Publications from the University of California

The Institute of Transportation Studies at the University of California, Irvine (ITS Irvine) specializes in the application of advanced analytical techniques and technologies to contemporary transportation problems. Established in 1974, ITS Irvine's programs currently involve nearly 75 faculty members, professional researchers and graduate students from a variety of disciplines.

Research at ITS Irvine covers a broad spectrum of transportation issues including:

  • energy and the environment
  • alternative-fueled vehicles
  • transportation pricing and demand management
  • transportation/land use relationships
  • transportation safety
  • freight and logistics
  • advanced transportation management systems
  • advanced traveler information systems
  • transportation network optimization
  • real-time simulation of intelligent transportation systems
  • microsimulation models for transportation planning
  • activity-based approaches to travel behavior
  • GPS/GIS for transportation data collection and analysis

ITS Irvine is part of a University of California (UC) multicampus organized research unit with branches on the Berkeley, Davis, Irvine and Los Angeles campuses, and the University of California Transportation Center (UCTC), a federally-designated center for research on transportation systems and policy. The Institute also plays a major role in the intelligent transportation and telematics research component of the California Institute for Telecommunications and Information Technology (Cal IT2) and in the ZEVNET hybrid-vehicle station car demonstration program of UCI's National Fuel Cell Research Center.

Cover page of Lidar Based Reconstruction framework for Truck Surveillance

Lidar Based Reconstruction framework for Truck Surveillance


Monitoring Commerical Vehicle Activities is very important for developing and  maintaining efficient freight transport systems. In the existing Literature this is broadly done through vehicle classification and reidentification problems using various sensing technologies. Lidar is an emerging traffic sensing technology which could potentially serve as a multi functional sensor for transport systems. In out current work we mainly focused on developing and qualitatively assessing a Lidar based Reconstruction framework for Truck surveillance purpose. We proposed a two stage Truck body reconstruction framework and found the results of reconstructed Truck bodies are quite promising for several truck-trailer configurations. For certain types of Truck-Trialer configurations such as containers due to the sparsity of scanned points in lateral direction, the wheel portion of reconstructed body still has noticeable deformations. We would like to address the same in our future work.

Cover page of The influence of emissions specific characteristics on vehicle operation: A micro-simulation analysis

The influence of emissions specific characteristics on vehicle operation: A micro-simulation analysis


The goal of this paper is to predict the fraction of time vehicles spend in different operating conditions from readily observable emission specific characteristics (ESC), which include geometric design, roadway environment, traffic characteristics, and driver behavior. We rely on a calibrated micro-simulation model to generate second-by-second vehicle trajectory data and use structural equation modeling to understand the influence of observed link ESC on vehicle operation. Our results reveal that 67 percent of link speed variance is explained by emission specific characteristics. At the aggregate level, geometric design elements exert a greater influence on link speed than traffic characteristics, the roadside environment, and driving style. Moreover, the speed limit has the strongest influence on vehicle operation, followed by facility type and driving style. This promising approach can be used to predict vehicle operation for models like MOVES, which was recently released by the Environmental Protection Agency.

Cover page of The Impact of Residential Density on Vehicle Usage and Energy Consumption

The Impact of Residential Density on Vehicle Usage and Energy Consumption


The debate concerning the impacts of urban land use density on travel in general, and on residential vehicle use and fuel consumption in particular, lacks reliable quantitative evidence. The 2001 U.S. National Household Transportation Survey (NHTS) provides information on vehicle miles of travel (VMT) based on odometer data, as well as annual fuel usage computations based on information about the make, model and vintage of all household vehicles. In addition, the 2001 NHTS has been augmented with land use variables in the form of densities of population and residences at the census tract and block level for each of the more than 69,000 households in the dataset. In order to obtain unbiased estimates of the effects of any of these land use variables on annual VMT and fuel consumption the authors present a model system that accounts for both self selection effects and missing data that are related to the endogenous variables.

Results for the State of California show that the residential density effects are substantial and precisely estimated. Comparing two households that are similar in all respects except residential density, a lower density of 1,000 housing units per square mile implies a positive difference of almost 1,200 miles per year and about 65 more gallons of fuel per household. This total effect of residential density on fuel usage is decomposed into to two paths of influence. Increased mileage leads to a difference of 45 gallons, but there is an additional direct effect of density through lower fleet fuel economy of 20 gallons per year, a result of vehicle type choice.