Key factors contributing to crash severity at highway-rail grade crossings

The purpose of this paper is to develop and com- pare the preferred multinomial logit （MNL） and ordered logit （ORL） model in identifying factors that are important in making an injury severity difference and exploring the impact of such explanatory variables on three different severity levels of vehicle-related crashes at highway-rail grade crossings （HRGCs） in the United States. Vehicle-rail crash data on USDOT highway-rail crossing inventory and public crossing sites from 2005 to 2012 are used in this study. Preferred MNL and ORL models are developed and marginal effects are also calculated and compared. A majority of the variables have shown similar effects on the probability of the three different severity levels in both models. In addition, based on the Akaike information criterion, it is found that the MNL model is better than the ORL model in predicting the vehicle crash severity levels on HRGCs in this study. Therefore, the researchers recommend the use of MNL model in predicting severity levels of vehicle-rail crashes on HRGCs.

Accident and hazard prediction models for highway–rail grade crossings:a state-of-the-practice review for the USA

Highway–rail grade crossings(HRGCs)are one of the most dangerous segments of the transportation network.Every year numerous accidents are recorded at HRGCs between highway users and trains,between highway users and traffic control devices,and solely between highway users.These accidents cause fatalities,severe injuries,property damage,and release of hazardous materials.Researchers and state Departments of Transportation(DOTs)have addressed safety concerns at HRGCs in the USA by investigating the factors that may cause accidents at HRGCs and developed certain accident and hazard prediction models to forecast the occurrence of accidents and crossing vulnerability.The accident and hazard prediction models are used to identify the most hazardous HRGCs that require safety improvements.This study provides an extensive review of the state-of-the-practice to identify the existing accident and hazard prediction formulae that have been used over the years by different state DOTs.Furthermore,this study analyzes the common factors that have been considered in the existing accident and hazard prediction formulae.The reported performance and implementation challenges of the identified accident and hazard prediction formulae are discussed in this study as well.Based on the review results,the US DOT Accident Prediction Formula was found to be the most commonly used formula due to its accuracy in predicting the number of accidents at HRGCs.However,certain states still prefer customized models due to some practical considerations.Data availability and data accuracy were identified as some of the key model implementation challenges in many states across the country.

A New Accident Prediction Model for Highway-Rail Grade Crossings Using the USDOT Formula Variables

This paper presents the ZINDOT model,a methodology utilizing a zero-inflated negative binomial model with the variables used in the United States Department of Transportation(USDOT)accident prediction formula,to determine the expected accident count at a highway-rail grade crossing.The model developed contains separate formulas to estimate the crash prediction value depending on the warning device type installed at the crossing:crossings with gates,crossings with flashing lights and no gates,and crossings with crossbucks.The proposed methodology also accounts for the observed accident count at a crossing using the Empirical Bayes method.The ZINDOT model estimates were compared to the USDOT model estimates to rank the crossings based on the expected accident frequency.It is observed that the new model can identify crossings with a greater number of accidents with Gates and Flashing Lights and Crossbucks in both Illinois(data which were used to develop the model)and Texas(data which were used to validate the model).A practitioner already using the USDOT formulae to estimate expected accident count at a crossing could easily use the ZINDOT model as it employs the same variables used in the USDOT formula.This methodology could be used to rank highway-rail grade crossings for resource allocation and safety improvement.

Development of combined transitional pavement structure for urban tram track-road grade crossings

The grade crossings and adjacent pavements of urban trams are generally subjected to complex load conditions and are susceptible to damage.Therefore,in this study,a novel pavement structure between tram tracks and roads constructed using polyurethane(PU)elastic concrete and ultra-high-performance concrete(UHPC),referred to as a track-road transitional pavement(TRTP),is proposed.Subsequently,its performance and feasibility are evaluated using experimental and numerical methods.First,the mechanical properties of the PU elastic concrete are evaluated.The performance of the proposed structure is investigated using a three-dimensional finite element model,where vehicleinduced dynamic and static loads are considered.The results show that PU elastic concrete and the proposed combined TRTP are applicable and functioned as intended.Additionally,the PU elastic concrete achieved sufficient performance.The recommended width of the TRTP is approximately 50 mm.Meanwhile,the application of UHPC under a PU elastic concrete layer significantly reduces vertical deformation.Results of numerical calculations confirmed the high structural performance and feasibility of the proposed TRTP.Finally,material performance standards are recommended to provide guidance for pavement design and the construction of tram-grade crossings in the future.

The CA model for traffic-flow at the grade roundabout crossing

The cellular automaton model is suggested to describe the traffic-flow at the grade roundabout crossing. After the simulation with computer, the fundamental properties of this model have been revealed. Analysing this kind of road structure, this paper transforms the grade roundabout crossing with inner-roundabout-lane and outer-roundabout-lane into a configuration with many bottlenecks. Because of the self-organization, the traffic flow remains unblocked under a certain vehicle density. Some results of the simulation are close to the actual design parameter.

Optimization of Shanghai marine environment monitoring sites by integrating spatial correlation and stratified heterogeneity

The water quality grades of phosphate（PO4-P） and dissolved inorganic nitrogen（DIN） are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validation is used to determine the statistical inference method. To minimize absolute average errors and error mean squares,stratified Kriging（SK） interpolation is applied to DIN and ordinary Kriging（OK） interpolation is applied to PO4-P.Ten percent of the sites is adjusted by considering their impact on the change in deviations in DIN and PO4-P interpolation and the resultant effect on areas with different water quality grades. Thus, seven redundant historical sites are removed. Seven historical sites are distributed in areas with water quality poorer than Grade IV at the north and south branches of the Changjiang（Yangtze River） Estuary and at the coastal region north of the Hangzhou Bay. Numerous sites are installed in these regions. The contents of various elements in the waters are not remarkably changed, and the waters are mixed well. Seven sites that have been optimized and removed are set to water with quality Grades III and IV. Optimization and adjustment of unrestricted areas show that the optimized and adjusted sites are mainly distributed in regions where the water quality grade undergoes transition.Therefore, key sites for adjustment and optimization are located at the boundaries of areas with different water quality grades and seawater.