Gunwoo Lee

Environmental Impacts of a Major Freight Corridor: A Study of I-710 in California

The San Pedro Bay Ports (SPBP) complex of Los Angeles and Long Beach in Southern California is one of the largest container port complexes in the world. This complex contributes significantly to both regional and national economies in California and the United States, respectively. However, the ongoing growth and economic benefits of the SPBP are threatened by negative externalities associated with port operations, particularly increasing congestion and air pollution. The objective of this paper is to explore a new approach to estimating vehicle emission impacts of freight corridor operations related to the port area, particularly those associated with heavy-duty diesel trucks. The paper combines a microscopic traffic simulation model to capture detailed vehicle trajectories (speeds and accelerations) and congestion effects, with an emission model and a spatial dispersion model to facilitate the estimation of the health and environmental justice impacts of freight corridor operations. Focus is on the I-710 freeway in the Alameda Corridor from the SPBP area up to downtown Los Angeles, California, some 20 mi north. Several scenarios were evaluated in addition to the 2005 base scenario: replacement of the current fleet of port heavy-duty diesel trucks with zero-emission vehicles, elimination of port heavy-duty diesel truck trips that would correspond to shifting more containers to other modes such as rail, and implementation of a truck-restricted lane, preventing trucks from using the leftmost lanes. The results show that fleet replacement with cleaner trucks yields the most emission reductions both quantitatively and spatially.

Genetic Algorithm to Estimate Cumulative Prospect Theory Parameters for Selection of High-Occupancy-Vehicle Lane

Recent literature suggests a need for a more realistic representation of driver behavior. In an effort to integrate prospect theory as a potential descriptive method into traveler behavior, it is important to determine the validity of previous estimated parameters obtained from empirical studies and interviews of people who are not in the same fast-paced, dynamic, travel time disutility setting as real drivers. A genetic algorithm is used to simultaneously estimate the parameters of the cumulated prospect theory (CPT) value and weight functions as well as the coefficients of the random utility model; this procedure leads to estimates that have a higher likelihood value and statistical significance than an equivalent expected utility–based logit model or a CPT-based logit model using the empirical values developed earlier. The value function parameters generally conform to conclusions from previous literature. The weight function parameters, however, suggest that drivers in a fast-paced changing environment with multiple subjects for prospect evaluation may become overwhelmed by the certainty effect.

Estimation of the shore excursion expenditure function during cruise tourism in Korea

ABSTRACT Recently, the number of foreign tourists to Korea via cruise ships has increased dramatically. We attempted to estimate the shore excursion expenditure function during cruise tourism in Korea. To this end, we collected data from a survey of foreign tourists who visited Korea via cruise ships and conducted the ordered probit model with sample selection to correct for the sample selection bias. Statistical tests indicate that the sample selection model provides unbiased estimates of the ordered probit model. The estimation results reveal that the coefficients of the experience of visiting Korea, job status, annual income, and nationality have statistically significant relationships with shopping expenditure. Further, it is likely that Chinese and Japanese passengers spend more money on shopping than passengers from other countries. This study is expected to provide the Korean government and port authorities with useful information for targeting passengers with high shore excursion expenditure. From a management perspective, the results of this analysis will enable cruise operators to design shore excursion programs that meet travelers’ needs.

Safety Impacts of Intervehicle Warning Information Systems for Moving Hazards in Connected Vehicle Environments

Driver inattentiveness is one of the critical factors that contribute to vehicle crashes. The intervehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards under the connected vehicle environments. A novel feature of the proposed ISWS is its capability to detect hazardous driving events, which are defined as moving hazards with a high potential to cause crashes. The study presented in this paper evaluated the potential effectiveness of the ISWS to reduce crashes and to mitigate traffic congestion. The study included a field experiment that documented actual vehicle maneuvering patterns of accelerations and lane changes, which were used to enhance the realism of simulation evaluations. Probe vehicles equipped with customized onboard units, which consisted of a GPS device, accelerometer, and gyro sensor, were used. A microscopic simulator, VISSIM, was used to simulate a drivers responsive behavior after warning messages were delivered. A surrogate safety assessment model was used to derive surrogate safety measures to evaluate the effectiveness of ISWS in terms of traffic safety. The results showed a reduced number of rear-end conflicts when the ISWSs market penetration rate (MPR) and the congestion level of the traffic conditions increased. The reduced number of rear-end conflicts was approximately 84.3%, with a 100% MPR under Level of Service D traffic conditions. Analysis of the standard deviation of speed showed that a reduction of 39.9% was achieved. The outcomes of this study could be valuable to derive smarter operational strategies for ISWS.