A framework for travel time variability analysis using urban traffic incident data

This study aims to develop a framework to estimate travel time variability caused by traffic incidents using integrated traffic, road geometry, incident, and weather data. We develop a series of robust regression models based on the data from a stretch in California's highway system during a two-year period. The models estimate highway clearance time and percent changes in speed for both downstream and upstream sections of the incident bottleneck. The results indicate that highway shoulder and lane width factor adversely impact downstream highway clearance time. Next, travel time variability is estimated based on the proposed speed change models. The results of the split-sample validation show the effectiveness of the proposed models in estimating the travel time variability. Application of the model is examined using a micro-simulation, which demonstrates that equipping travelers with the estimated travel time variability in case of an incident can improve the total travel time by almost 60%. The contribution of this research is to bring several datasets together, which can be advantageous to Traffic Incident Management.     

Sizing parking facilities at airports

Established rules-of-thumb and industry guidelines for estimating the supply of parking at airports are based on uncertain quantities such as design year enplanements and number of airport employees, and are independent of cost. In the presence of continued uncertainty and increasing competition for limited space in and around airports, it is important that facilities are sized in relation to cost of providing and using them. A probabilistic model based on the classical “newsboy” problem is proposed to determine the optimal supply of parking in relation to expected total cost while treating demand as a random quantity. Empirical data are used to demonstrate the application of the proposed model for decision making. In addition to construction and maintenance costs, and user costs, decisions are shown to be sensitive to the level of uncertainty of design year enplanements.     

Cost-based approach for sizing of pedestrian facilities

Pedestrian facility size is currently determined in direct relationship to the design level of service. However, the design level of service is chosen arbitrarily from the six levels of service, which are assumed to represent the freedom available for movement at different levels of pedestrian flow. This direct and simple approach to facility sizing is shown to have two fundamental deficiencies that contribute to wasteful over capacity. In this article, a cost-based approach is introduced to overcome the deficiencies. Two analytical models, one for determining optimal design density and another for determining optimal design flow, are presented. The optimum design parameters minimize the total cost of the facility defined as the sum of construction cost and user cost. The sensitivity of the optimum parameters to the cost and pedestrian flow parameters is demonstrated using a numerical example.