Driver Behavior at Rail-Highway Crossings

1998 ◽  
Vol 1648 (1) ◽  
pp. 28-34 ◽  
Author(s):  
John Abraham ◽  
Tapan K. Datta ◽  
Sue Datta
Keyword(s):  
Traffic Control ◽  
Statistical Significance ◽  
Driver Behavior ◽  
Essential Element ◽  
License Plate ◽  
Traffic Crash ◽  
Crash Data ◽  
Targeted Enforcement ◽  
Study Sites ◽  
Different Levels

A study of driver behavior at 37 rail-highway crossings in Michigan revealed the possible association between past crash histories and violations. Data collection included recording license plate numbers for violating vehicles, driver gender, approximate age of the driver, and the vehicle make and model. Driver violations were categorized into five different levels of severity ranging from routine to critical. The 37 study sites were subdivided into four groups based on crossing geometry and traffic control. The number of sites in the groups ranged from 5 to 18. Seven years of crash data on the study sites were considered for significance testing. Observed violation data for the same groups were calculated, and tests for statistical significance were performed on them. The results of this study indicated promise for the use of the violation data in determining the relative hazardousness of rail-highway crossings in combination with crash histories. The violation data may also be used to develop countermeasures that would help alleviate violations and eventually traffic crash problems at rail-highway crossing sites. Targeted enforcement as well should assist in driver behavioral modifications. Additionally, the timely arrival of trains after the warning devices are triggered is an essential element that motorists assess when considering taking risks.

Safety Evaluation and Improvements for Highway Intersections

2008 ◽  
Vol 2060 (1) ◽  
pp. 46-52 ◽  
Author(s):  
Li Yuan ◽  
Jian Lu
Keyword(s):  
Traffic Control ◽  
Cost Benefit Analysis ◽  
Safety Evaluation ◽  
Cost Benefit ◽  
Safety Performance ◽  
Crash Analysis ◽  
Traffic Crash ◽  
Crash Data ◽  
Intersection Safety ◽  
Traffic Signal Timing

Intersection safety is one of the most important issues in transportation. Traffic crash analysis—the most popular method to evaluate or assess the safety performance of an intersection—has been used for a long time. However, it is based on a lot of crash data, which need to be accumulated over a long period. In addition, traffic crashes sometimes occur randomly as a result of human driving behavior. Therefore, without sufficient data and crash history, traffic crash analysis may not give an overall evaluation of an intersection's safety performance. This paper introduces an approach to evaluating highway intersection safety performance. It is fully based on the existing conditions of the intersection, including geometrics, sight distance, pavement surface conditions, traffic control devices, traffic signal timing, and phasing. The non-accident-based approach is based on field surveys under the conditions mentioned previously. The approach will also result in a safety index to indicate the safety performance of the intersection. Corresponding countermeasures are ranked and recommended based on cost–benefit analysis. This paper is based on research results from part of a project (entitled Safety Design of Highway Intersections) sponsored by the China Department of Transportation. In this paper, the approach (called a diagnostic approach) is practically applied to evaluate the safety performance of some intersections in Shan Dong Province. Results from the real application indicate that the approach has good applicability and can be used by field safety engineers in real applications.

Integrating Crime and Traffic Crash Data in Nashville

2010 ◽  
Author(s):  
Jason Wyatt ◽  
Michael Alexander
Keyword(s):  
Traffic Crash ◽  
Crash Data

scholarly journals Analysis of Severe Injuries in Crashes Involving Large Trucks Using K-Prototypes Clustering-Based GBDT Model

Safety ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 32
Author(s):  
Syed As-Sadeq Tahfim ◽  
Chen Yan
Keyword(s):  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
The United States ◽  
Clustering Methods ◽  
Severe Injuries ◽  
Traffic Crash ◽  
Crash Data ◽  
Boosted Decision Trees ◽  
The Individual ◽  
Crash Characteristics

The unobserved heterogeneity in traffic crash data hides certain relationships between the contributory factors and injury severity. The literature has been limited in exploring different types of clustering methods for the analysis of the injury severity in crashes involving large trucks. Additionally, the variability of data type in traffic crash data has rarely been addressed. This study explored the application of the k-prototypes clustering method to countermeasure the unobserved heterogeneity in large truck-involved crashes that had occurred in the United States between the period of 2016 to 2019. The study segmented the entire dataset (EDS) into three homogeneous clusters. Four gradient boosted decision trees (GBDT) models were developed on the EDS and individual clusters to predict the injury severity in crashes involving large trucks. The list of input features included crash characteristics, truck characteristics, roadway attributes, time and location of the crash, and environmental factors. Each cluster-based GBDT model was compared with the EDS-based model. Two of the three cluster-based models showed significant improvement in their predicting performances. Additionally, feature analysis using the SHAP (Shapley additive explanations) method identified few new important features in each cluster and showed that some features have a different degree of effects on severe injuries in the individual clusters. The current study concluded that the k-prototypes clustering-based GBDT model is a promising approach to reveal hidden insights, which can be used to improve safety measures, roadway conditions and policies for the prevention of severe injuries in crashes involving large trucks.

Does Displaying Safety Messages on Dynamic Message Signs have Measurable Impacts on Crash Risk?

2021 ◽  
pp. 036119812110444
Author(s):  
Megat-Usamah Megat-Johari ◽  
Nusayba Megat-Johari ◽  
Peter T. Savolainen ◽  
Timothy J. Gates ◽  
Eva Kassens-Noor
Keyword(s):  
Negative Binomial ◽  
Driver Behavior ◽  
Field Research ◽  
Crash Risk ◽  
Traffic Crashes ◽  
Crash Data ◽  
Safety Issues ◽  
Dynamic Message Signs ◽  
Safety Message ◽  
Message Signs

Transportation agencies have increasingly been using dynamic message signs (DMS) to communicate safety messages in an effort to both increase awareness of important safety issues and to influence driver behavior. Despite their widespread use, evaluations as to potential impacts on driver behavior, and the resultant impacts on traffic crashes, have been very limited. This study addresses this gap in the extant literature and assesses the relationship between traffic crashes and the frequency with which various types of safety messages are displayed. Safety message data were collected from a total of 202 DMS on freeways across the state of Michigan between 2014 and 2018. These data were integrated with traffic volume, roadway geometry, and crash data for segments that were located downstream of each DMS. A series of random parameters negative binomial models were estimated to examine total, speeding-related, and nighttime crashes based on historical messaging data while controlling for other site-specific factors. The results did not show any significant differences with respect to total crashes. Marginal declines in nighttime crashes were observed at locations with more frequent messages related to impaired driving, though these differences were also not statistically significant. Finally, speeding-related crashes were significantly less frequent near DMS that showed higher numbers of messages related to speeding or tailgating. Important issues are highlighted with respect to methodological concerns that arise in the analysis of such data. Field research is warranted to investigate potential impacts on driving behavior at the level of individual drivers.

The effect of supplier development initiatives on purchasing performance: a structural model

2005 ◽  
Vol 10 (4) ◽  
pp. 289-301 ◽  
Author(s):  
Cristóbal Sánchez‐Rodríguez ◽  
David Hemsworth ◽  
Ángel R. Martínez‐Lorente
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Manufacturing Industry ◽  
Structural Model ◽  
Essential Element ◽  
Equation Modeling ◽  
Supplier Development ◽  
Manufacturing Companies ◽  
Content Type ◽  
Different Levels

PurposeSupply chain management is an increasingly important organizational concern, and proper management of supplier relationships constitutes one essential element of supply chain success. However, there is little empirical research that has tested the effect of supplier development on performance. The main objective is to analyze the effect of supplier development practices with different levels of implementation complexity on the firm's purchasing performance.Design/methodology/approachThree supplier development constructs were defined: basic supplier development, moderate supplier development, and advanced supplier development. Three structural models were hypothesized and tested using structural equation modeling through field research on a sample of 306 manufacturing companies in Spain.FindingsIdentified important interrelationships among the various supplier development practices, basic, moderate, and advanced. Also indicated that the implementation of supplier development practices significantly contributes to the prediction of purchasing performance.Research limitations/implicationsThe use of a single key informant could be seen as a potential limitation of the study. The study was a cross‐sectional and descriptive sample of the manufacturing industry at a given point in time. A more stringent test of the relationships between the different levels of supplier development and performance requires a longitudinal study, or field experiment.Practical implicationsThis study focused on supplier development practices and revealed how involving suppliers in supplier development activities is important and may help buyers to increase their purchasing performance. The findings from the structural analysis should provide practicing managers with insights on how these practices and their benefits are related in terms of purchasing performance, thus affecting their ability to make better sourcing decisions.Originality/valueFills an important gap in the purchasing literature with respect to the area of supplier development. While there is much written about supplier development based on conceptual and case study research, this study is unique in that it is the first attempt to empirically model the relationships between different levels of supplier development and their impact on purchasing performance using a comprehensive set of practices.

scholarly journals Safety Analysis of Interchange Functional Areas

2018 ◽  
Vol 2672 (30) ◽  
pp. 120-130
Author(s):  
Akinfolarin Abatan ◽  
Peter T. Savolainen
Keyword(s):  
Random Effects ◽  
Traffic Control ◽  
Negative Binomial ◽  
Research Literature ◽  
Safety Performance ◽  
Random Effects Models ◽  
Traffic Crash ◽  
Design Alternatives ◽  
Traffic Conflicts ◽  
Functional Areas

Limited access facilities, such as freeways and expressways, are generally designed to the highest standards among public roads. Consequently, these facilities demonstrate crash, injury, and fatality rates that are significantly lower than other road facility types. However, these rates are generally elevated in the immediate vicinity of interchanges because of increases in traffic conflicts precipitated by weaving, merging, and diverging traffic. Given the extensive costs involved in interchange construction, it is important to discern the expected operational and safety impacts of various design alternatives. To this end, the objective of this study was to analyze safety performance within the functional areas of interchanges. The study involves the integration of traffic crash, volume, and roadway geometric data from 2010 to 2014 in the state of Iowa. Separate analyses were conducted for the freeway mainline and ramp connections. A series of safety performance functions (SPFs) were estimated for both the mainline and ramps. Random effects negative binomial models were estimated, which account for correlation in crash counts at the same location over time. The results show the frequency of crashes to vary based on traffic volume, interchange configuration, speed limit, and traffic control at the ramp terminal. The random effects models are shown to significantly outperform pooled models, which suggest there are several important location-specific factors that are not included in the analysis dataset. The SPFs from this study are also compared with several reference models from the extant research literature.

scholarly journals An Efficient Traffic Control System and License Plate Detection Using Image Processing

2017 ◽  
Vol 6 (01) ◽  
pp. 20-25
Author(s):  
Dr. Govind Shah
Keyword(s):  
Traffic Control ◽  
License Plate ◽  
License Plate Recognition ◽  
Traffic Surveillance ◽  
Payment Systems ◽  
General Technique ◽  
Black And White ◽  
Traffic Control System ◽  
Monitoring Devices ◽  
Real Time Application

Automatic license plate recognition is extracted from license plate of the vehicle. It is taken as an image or a continuous image taken in sequence. The extracted information can be with or without a database in many applications like electronic payment systems and freeway and arterial monitoring devices for traffic surveillance. ALPR employs CC camera, advanced camera or black and white, color camera to capture the image. ALPR is fruitful if the captured images are of good quality. ALPR is a real time application that processes the images of license plates in various conditions like dark or bright times in a day. A general technique should be identified to process images in many different countries or states. We should know that the license plate generally consists of various colors, languages, fonts and others have images in the background. Also, these plates are obstructed by mud, light, some accessories especially on a car. Here, we discuss about methods for ALPR. We classify ALPR based on the features they are used in each method and knowing their advantages, disadvantages, recognition accuracy and processing speed. Managing the timing in traffic controlling by calculating the density of an image.

scholarly journals Frequency of number of roots and root canals of maxillary first premolar teeth.

2021 ◽  
Vol 28 (10) ◽  
pp. 1513-1518
Author(s):  
Munawar Aziz Khattak ◽  
Sana Arbab ◽  
Syed Amjad Shah
Keyword(s):  
Statistical Significance ◽  
Maxillofacial Surgery ◽  
P Value ◽  
Cross Sectional ◽  
Mean Values ◽  
Khyber Pakhtunkhwa ◽  
Root Canals ◽  
India Ink ◽  
Different Levels ◽  
Chamber Floor

Objective: To determine the frequency of the number of roots and root canals in a sample of 250 extracted maxillary first premolar teeth of patients visiting Peshawar Dental College and Hospital Khyber Pakhtunkhwa. Study Design: Cross Sectional. Setting: Department of Oral Biology, Peshawar Dental College and Hospital Khyber Pakhtunkhwa. Period: April 2016 to December 2016. Material & Methods: A total of 250 extracted human maxillary first premolars were collected from the Department of Oral & Maxillofacial Surgery, Peshawar Dental College, and Hospital Khyber Pakhtunkhwa. All teeth were visually inspected to count the number of roots. Subsequently, the access cavity was prepared, and pulp extirpated from each tooth. Endodontic explorer was used to locating the canal orifice(s) at the pulp chamber floor. Later the root canal orifices were injected with India ink to stain the canals. After that roots of teeth were sectioned at different levels to note down the number of canals. Data were analyzed using SPSS version 19. The statistical significance of the variations from mean values was considered significant if the p-value was less than 0.05. Results: Out of 250 maxillary first premolar teeth, 44.8% had one root, 40.4% had two separate and 12.8% had two fused roots. Three roots were seen in 2.0% teeth. Two root canals were present in the vast majority (70.4%), whereas one and three root canals were seen in 27.6% and 2.0% teeth, respectively. The correlation between the number of roots and root canals of maxillary first premolar teeth was highly significant. Conclusions: There was a high frequency of maxillary first premolars with two roots and two root canals.

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