Browsing by Author "Billy M. Williams, Committee Member"

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Collision Models for Multilane Highway Segments Incorporating the Effects of Curbs
(2008-05-16) Baek, Jongdae; Jason A. Osborne, Committee Member; Billy M. Williams, Committee Member; Nagui M. Rouphail, Committee Member; Joseph E. Hummer, Committee Chair
The main objective of this study was to develop valid statistical collision models for multilane highway segments with or without curbs. For this, road geometric data, traffic data, and collision data for the three years were collected. The data include 2,274 collisions and 885 injury collisions that occurred on 191.85 miles of 199 directional segments. A new modeling method of introducing variables into the model one by one in a multiplicative form was applied. A nonlinear optimizing algorithm for estimating parameters using a negative binomial log likelihood function was adopted for the modeling. The functional form of the variable to be introduced was determined based on the relationship between the recorded number of collisions and the number of collisions predicted by the current model without the variable. The integrate-differentiate method was applied to find candidate functional forms for each variable. Model selections were based on the -2 log likelihood and BIC statistics. The cumulative residuals (CURE) plot method was adopted for checking the goodness of fit of the models. As a result of the modeling efforts, the annual average daily traffic, access point density, shoulder width, and shoulder type variables were introduced to the final model for total collisions. The same variables except the shoulder type variable were introduced to the injury collision model. Overall, then, it appears that curbs mean fewer total collisions and no change in injury collisions as compared to no curbs on the sampled road segments. The models developed in this study were based only on the data for North Carolina and limited number of variables. The developed models can be improved in the future by collecting data on more miles, by bringing more explanatory variables into models, and by using the data from other states. Additionally, the characteristics of vehicles speeds on multilane highways were analyzed and compared. The results showed that the mean speeds for the non-curbed sites were about 2 to 3 mph higher than those for the curbed sites.
Comparing Operation and Safety between a New Nano Interchange and Conventional System Interchange
(2008-12-19) Moon, Jae Pil; Billy M. Williams, Committee Member; John R. Stone, Committee Member; Joseph E. Hummer, Committee Chair; Nagui M. Rouphail, Committee Member
The primary purpose of this research is to estimate the capability and applicability of new nano interchange designs as they compare to conventional four-level interchanges. Nano interchanges were conceived to provide drivers with high speed and short travel distances while requiring less right of way in dense urban areas where real estate is expensive. This research consists of two tasks: (1) operational evaluation and (2) safety evaluation. The operational evaluation compares measures of effectiveness (MOEs) between nano interchanges and conventional interchanges for thirty volume scenarios comprised of varied data for through volumes, ramp volumes, and percentages of heavy vehicles. The estimations were conducted for an entire interchange and for key freeway segments. The MOEs for an entire interchange are travel time, speed, delay time, and ramp travel time; and the MOEs for key freeway segments are density, speed, and level of service. The safety estimations were made by building safety prediction models for collisions that may occur in the influence areas of ramps. These safety models are based on negative binomial distribution and quantified safety effects of traffic, geometric, and environmental factors using three statistical methods: (1) a generalized linear model with only main effect variables, (2) a generalized linear model with main effects and interaction terms, and (3) the new Hauer method model. Specifically, this study addresses the safety effectiveness of left-hand ramps, which are needed in the nano interchange designs, because the safety effects have not been well quantified in previous studies. Considering goodness-of-fit statistics such as the likelihood-ratio test, Akaike?s information criterion (AIC), ordinary R-squared values,the Miaou method, and CURE plots, the best safety models were chosen for four collision categories: (1) Total collisions of all types, (2) Severe collisions, (3) Related Total collisions,and (4) Related Severe collisions. The operational evaluation for an entire interchange shows that conventional interchanges perform better than nano interchanges for the volume scenarios tested. The analyses of key freeway segments show that most of operational difficulties for the nano interchanges are in diverging influence areas located on upgrade segments. The analyses also indicate that several merging influence areas that are connected to ramps with steeper and longer upgrades also have lower performance levels. The safety prediction model developed unique linear or non-linear relationships among traffic, geometric, and environmental factors. Left-hand ramps appear to have higher collision frequencies than right-hand ramps, and on-ramps have higher collision frequencies than off-ramps. In addition to estimating the safety effects, this study compares three modeling procedures. This research shows that the Hauer procedure sufficiently represents linear and non-linear relationships in terms of diverse functional forms by each explanatory variable, whereas a generalized log-linear model does not adequately develop linear relationships for some explanatory variables in terms of linear functional forms. However, the generalized log-linear model with interaction terms among independent variables fits to data as well as the Hauer procedure. Finally, based on these estimations, the operational and safety problems of nano interchanges are addressed in this study, and the following recommendations are made to improve the operation and safety effectiveness of the interchange: (1) deceleration or acceleration lanes could be extended; (2) a two-lane off-ramp or on-ramp for the nano interchange could be considered; and (3) left-hand ramps could be replaced by right-hand ramps.
Synthesized through trip model for small and medium urban areas
(2008-04-11) Han, Yang; Peter Bloomfield, Committee Member; John R. Stone, Committee Chair; Billy M. Williams, Committee Member; Joseph E. Hummer, Committee Member
Traffic Simulation Failure Detection and Analysis
(2005-12-16) Wan, Baohong; Billy M. Williams, Committee Member; Joseph E. Hummer, Committee Member; Nagui M. Rouphail, Committee Chair; Leonard A. Stefanski, Committee Member
Microscopic, stochastic traffic simulation may yield simulation failures under multiple replications. The failed runs are not valid in the estimation of traffic performance and should be excluded from the final simulation output analysis. On the other hand, these failure runs provide important clues to perform a simulation flaw diagnosis. An unconventional failure detection and analysis methodology was proposed to comprise three layers: time series inspection, spatial analysis, and causal analysis. The process of time series inspection traces the variation of indicator variables over the time domain for the purpose of detection of simulation failures. The spatial analysis identifies failure occurrence patterns, and the subsequent causal analysis judge contributing factors to simulation failures using a tabular method in combination with other tools. A widely-used traffic simulator, CORSIM, is used as the test-bed simulator. Three real-world traffic networks were simulated as the case studies for the proposed method. The study results indicated that the proposed failure detection and analysis method is valid and effective to improve traffic simulation from multiple perspectives. Its application in the evaluation of networks testified its utility in multiple aspects. The proposed procedure helped uncover the existing deficiencies in the current simulation models, and, therefore, provide important guidance for the organized model improvement efforts. On the other hand, the procedure was also applied in the analysis of a projected traffic scenario to testify its value in the identification of critical sites on the network from the traffic engineering perspective.