Several recent transportation safety studies have indicated the importance of accounting for correlated outcomes, for example, among different crash types, including differing injury-severity levels. In this paper, we discuss inference for such data by introducing a flexible Bayesian multivariate model. In particular, we use a Dirichlet process mixture to keep the dependence structure unconstrained, relaxing the usual homogeneity assumptions. The resulting model collapses into a latent class multivariate model that …Read More
In transportation safety studies, it is often necessary to account for unobserved heterogeneity and multimodality in data. The commonly used standard or over-dispersed generalized linear models (e.g., negative binomial models) do not fully address unobserved heterogeneity, assuming that crash frequencies follow unimodal exponential families of distributions. This paper employs Bayesian nonparametric Dirichlet process mixture models demonstrating some of their major advantages in transportation safety studies. We examine the performance of …Read More
Thakali, L., Fu, L., & Chen, T. (2016). Model Based versus Data-driven Approach for Road Safety Analysis : Does More Data Help? Transportation Research Record: Journal of the Transportation Research Board, No. 2601. Abstract: Crash data for road safety analysis and modeling are growing steadily in size and completeness due to latest advancement in information technologies. This increased availability of large datasets has generated resurgent interest in applying data-driven nonparametric approach as …Read More
Heydari, S., Fu, L., Lord, D., Mallick, B.K. (2016). Multilevel Dirichlet process mixture analysis of railway grade crossing crash data. Analytic Methods in Accident Research, 9, 27-43.
Thakali, L., Kwon, T. J., & Fu, L. (2015). Identification of Crash Hotspots using Kernel Density Estimation and Kriging Methods – A Comparison. Journal of Modern Transportation. DOI: 10.1007/s40534-015-0068-0 Abstract: This paper presents a study aimed at comparing the outcome of two geostatistical based approaches, namely, Kernel Density Estimation (KDE) and Kriging, for identifying crash hotspots in a road network. Aiming at locating high-risk locations for potential intervention, hotspot identification …Read More
Hossain, S. M. K., Fu, L., Lake, R. (2014). Improving Winter Road Conditions: Evaluation of Deicing Performance of Alternative Salts and Development of Adjustment Factors. Canadian Journal of Civil Engineering (CJCE). (Accepted: 6 January 2015)
Hossain, S.M. K., Fu, L.; Olesen A.(2014). Effectiveness of Anti-icing Operations for Snow and Ice Control of Parking Lots and Sidewalks. Canadian Journal of Civil Engineering (CJCE), 41(6): 523-530, 10.1139/cjce-2013-058 This paper describes an empirical study aimed at investigating the performance of the anti-icing strategy for snow and ice control of parking lots and sidewalks. The research is motivated by the need to address several key questions concerning various operational …Read More
Kwon, T. J., Fu, L., & Jiang, C. (2014). RWIS Stations – Where and How Many to Install: A Cost Benefit Analysis Approach, Canadian Journal of Civil Engineering (CJCE), DOI: 10.1139/cjce-2013-0569. ABSTRACT This paper presents a cost-benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models …Read More
Feng, F. and Fu, L. (2014). “Winter Road Surface Condition Forecasting.” J. Infrastruct. Syst. , 10.1061/(ASCE)IS.1943-555X.0000241 , 04014049. Winter Road Surface Condition Forecasting This study has attempted to address a challenging problem in winter road maintenance, namely road surface condition (RSC) forecasting. A novel conceptual framework for short-term road surface condition forecasting is proposed. This framework is designed to consider all important conditional factors, including weather, traffic, and maintenance …Read More
Heydari, S., Miranda-Moreno, L.F., Fu, L. (2014). Speed limit reduction in urban areas: A before-after study using Bayesian generalized mixed linear models. Accident Analysis and Prevention, in press.