Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Towards airport passenger experience models

This paper reports on the study of passenger experiences and how passengers interact with services, technology and processes at an airport. As part of our research, we have followed people through the airport from check-in to security and from security to boarding. Data was collected by approaching passengers in the departures concourse of the airport and asking for their consent to be videotaped. Data was collected and coded and the analysis focused on both discretionary and process related passenger activities. Our findings show the interdependence between activities and passenger experiences. Within all activities, passengers interact with processes, domain dependent technology, services, personnel and artifacts. These levels of interaction impact on passenger experiences and are interdependent. The emerging taxonomy of activities consists of (i) ownership related activities, (ii) group activities, (iii) individual activities (such as activities at the domain interfaces) and (iv) concurrent activities. This classification is contributing to the development of descriptive models of passenger experiences and how these activities affect the facilitation and design of future airports.