Haoqiang Fu

Modeling the Hurricane Evacuation Response Curve

The objective of this study is to develop a hurricane evacuation response curve that is sensitive to the characteristics of the hurricane, the time of day, and the type and timing of evacuation notice issued. Two data sets from past hurricanes, Floyd in South Carolina and Andrew in southeastern Louisiana, were used for model development and testing. A model developed on the Hurricane Floyd data set produced plausible results when it was tested with a series of storm scenarios and different evacuation notice policies. The same model predicted evacuation response behavior for Hurricane Andrew that was similar to observed behavior.

Survival Analysis-Based Dynamic Travel Demand Models for Hurricane Evacuation

Two dynamic travel demand models for hurricane evacuation based on survival analysis are presented: a Cox proportional hazards model and a piecewise exponential model. These models were used to estimate the probability of a households evacuating within discrete time intervals before hurricane landfall as a function of the households socioeconomic characteristics, the characteristics of the hurricane, and management practice in terms of the issuance of an evacuation order. Data from southeast Louisiana collected following Hurricane Andrew were applied. Both models reproduced the evacuation behavior satisfactorily, although the piecewise exponential model was slightly more accurate. Both appear capable of modeling dynamic hurricane evacuation travel demand. However, the Cox model cannot accommodate certain time-dependent variables because of its structure. The piecewise exponential model does not have such a limitation. The piecewise exponential model also has the advantage of estimating the baseline haza...

Sequential Logit Dynamic Travel Demand Model and Its Transferability

A dynamic hurricane evacuation travel demand model was estimated by using sequential logit with the data from Hurricane Floyd in South Carolina. The model was estimated on a random sample of 75% of the observations and applied to the remaining 25% as a test. In the test data, a total of 241 evacuations were predicted when 246 were observed, and the model estimated the number of evacuations in each 2-h period over 4 days with a root-mean-square error of 2.79 evacuations. Evacuation orders were modeled as a time-dependent variable. This significantly enhanced model performance over that achieved with evacuation orders as a stationary variable in previous work and provided the capability to analyze the impact of the type and timing of evacuation orders. That capability permits analyzing staged evacuation, in which areas are directed to evacuate in a sequence that optimizes network use. A model estimated on Hurricane Floyd evacuation data was transferred to Southeast Louisiana; its predictions were similar to evacuation behavior observed during Hurricane Andrew. With updating of the alternative specific constant of the transferred model to ensure the correct prediction of the total number of evacuations, the model predicted evacuation with a root-mean-square error of 4.53 evacuations per 6-h period. It was discovered that applying the same distance function to the two different hurricanes was a major source of error in model transfer. The representation of distance and its interactions with other variables need to be investigated further. The procedures and the information needed for model update warrant further study.

Effect of Passenger Age and Gender on Fatal Crash Risks of Young Drivers

The effect of passenger age and gender on young driver fatal crash risk was studied with police-reported crash data in Louisiana from 1999 to 2004. Young drivers were divided into three age groups—16, 17, and 18 to 20 years of age—by gender. Passengers were grouped into 15 to 17 and 18 to 20 years of age by gender. A series of analyses of young drivers and young passengers was conducted to study their risks of being involved in fatal crashes. Relative risks and crash rates were used to measure crash risk. The analyses followed step-by-step disaggregation of driver and passenger characteristics, including the number of passengers, passenger age, and passenger age and gender for each driver age and gender group. It was found that young drivers are negatively affected by young passengers, especially from their own peer age groups. However, the presence of adult passengers reduces their fatal crash risks. Sixteen-and 17-year-old drivers have similar fatal risk patterns that are much higher than and different from those of 18- to 20-year-old drivers; 16- and 17-year-old drivers are associated with the highest fatal crash risks when driving with their same gender and age group passengers, with male-to-male driver–passenger combination having higher fatal crash risk than female-to-female driver–passenger combination. As age progresses, fatal crash risk differences between male and female young drivers also increase.

Evaluating Alternative Pavement Marking Materials

On federally funded projects, the Federal Highway Administration wants state highway maintenance engineers to justify their choice of pavement marking material and show how it is better than alternative materials in the application environment in which it is being proposed. However, a convenient method of conducting such a comparison is not available. In this study, a model is described which allows comparison of the relative value of alternative pavement marking materials given the existing conditions at the application site such as pavement surface type, remaining pavement service life, traffic volume, line type, and line color. The model compares alternative pavement marking materials in terms of their benefit-cost ratio over the useful life of the material. The model was developed from approximately 3,500 readings of retroreflectivity on 40 mil and 90 mil thermoplastic, tape, and inverted profile pavement marking material on Interstate highways in Louisiana. Its use is demonstrated in sample applications.