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• A methodological framework to define conflict risk and level of severity during overtaking maneuver using surrogate measures for two-lane two-way highway in non-lane based heterogeneous traffic environment has been outlined. • A number of different models based on the discrete choice modelling approach have been explored to assesses the overtaking conflict risk severity. • The combined role of correlation in the unobserved factors over the alternatives outcomes, fixed threshold, and unobserved heterogeneity effects of different exogenous factors across observations are assessed. • A large set of explanatory variables pertaining to overtaking maneuver in two-lane two-way highway with non-lane based heterogeneous traffic environment are examined; • Several performance measures are used to assist the performance the model evaluation task; and. • A discussion is included with the illustration of the practical applicability of the proposed overtaking maneuver risk modeling framework. Introduction: Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evaluates safety risk in terms of nature and severity of probable conflicts during overtaking maneuvers on a bi-directional undivided two-lane highway in a heterogeneous traffic environment of a low-income country. Nature and severity of probable conflicts were defined with the application of surrogate safety proximity indicators in real-world naturalistic driving environment. Method: A risk severity model for overtaking maneuver was developed to better understand the significant factors associated with the probability of conflict and its severity during overtaking maneuver using discrete choice modeling approaches. The relevance of three alternate discrete outcome frameworks, namely multinomial logit (ML), ordered probit (OP), and mixed logit (MXL) models are addressed. The best fitted model is identified and estimated. The impact of the significant attributes was also evaluated. The study collected data from a section of two-lane highway in Bangladesh using naturalistic driving from both observational and computer vision techniques. A total of 46 explanatory variables related to overtaking maneuver are assessed. Results: Speed differential between overtaking and overtaken vehicles have a significant impact on the probability of severe conflicts. Moreover, the presence of a bus as an overtaking vehicle was found to contribute significantly to the severity of conflicts. Conclusions: The study makes substantial research contributions related to overtaking behavior and safety risk evaluation during overtaking in mixed traffic environment in low-income countries. The results can be used as a proactive tool for the evaluation of overtaking maneuvers and associated safety risk, and making policy decisions reducing safety risk during overtaking maneuver as well as overall safety, while acknowledging the limited resources and facilities in low-income countries. [ABSTRACT FROM AUTHOR]

Introduction : There have been a number of studies that have led to the development of safety risk assessment models to quantify the probability of crash frequencies on roadway facilities (both at micro- and macro-levels), over a specified time period. However, past research has rarely focused on heterogeneous traffic conditions in developing countries. Method: This paper puts forward several models related to the traditional count approach to estimate crash frequency at a micro-level in a non-lane based bi-directional heterogeneous traffic environment. The paper shows the results of dispersion, zero-inflation, and random heterogeneity effects of different exogenous factors by comparing Poisson (P); Negative Binomial (NB); random and fixed parameter Zero-Inflated Poisson (ZIP); and Latent Class Models (LCM). The empirical analysis is based on data from a section of a major national highway in Bangladesh. The performance of the models was validated using different statistical goodness-of-fit measures that compared the estimated and observed average crash frequencies at individual locations. With the identification of the most significant influencing factors, the paper discusses the practical policy implications using partial effects analysis and spatial distribution. Results : It was found that the Zero-Inflated Random Parameter model gives a slightly better statistical fit when compared to alternative approaches. Practical applications : This micro-level modeling approach would be useful to identify significant crash risk factors; to prioritize road sections according to their safety level; to select site-specific appropriate counter-measures; and devise proactive target oriented safety management strategies. Thus, the results shown here could be a point of reference in the planning, designing, maintaining, and managing two-lane highway sections in developing countries. • A methodological approach to develop micro-level crash prediction model for non-lane based bi-directional heterogeneous traffic environment has been put forwarded. • The combined role of dispersion, zero-inflation, class segmentation and random heterogeneity effects of different exogenous factors are examined. • A large set of exogenous variables pertaining to non-lane based heterogeneous traffic environment are tested. • A policy discussion is included to illustrate the practical applicability of the proposed modeling approach. [ABSTRACT FROM AUTHOR]