scholarly journals Extracting Useful Information from Basic Safety Message Data: An Empirical Study of Driving Volatility Measures and Crash Frequency at Intersections

2018 ◽  
Vol 2672 (38) ◽  
pp. 290-301 ◽  
Author(s):  
Mohsen Kamrani ◽  
Ramin Arvin ◽  
Asad J. Khattak
Keyword(s):  
Random Parameter ◽  
Crash Risk ◽  
Crash Frequency ◽  
Safety Message ◽  
Vehicle Data ◽  
Combining Data ◽  
Data Points ◽  
Pass Through ◽  
Safety Countermeasures ◽  
Surrogate Measures

With the emergence of high-frequency connected and automated vehicle data, analysts can extract useful information from them. To this end, the concept of “driving volatility” is defined and explored as deviation from the norm. Several measures of dispersion and variation can be computed in different ways using vehicles’ instantaneous speed, acceleration, and jerk observed at intersections. This study explores different measures of volatility, representing newly available surrogate measures of safety, by combining data from the Michigan Safety Pilot Deployment of connected vehicles with crash and inventory data at several intersections. For each intersection, 37 different measures of volatility were calculated. These volatilities were then used to explain crash frequencies at intersection by estimating fixed and random parameter Poisson regression models. Given that volatility reflects the degree to which vehicles move, erratic movements are expected to increase crash risk. Results show that an increase in three measures of driving volatility are positively associated with higher intersection crash frequency, controlling for exposure variables and geometric features. More intersection crashes were associated with higher percentages of vehicle data points (speed & acceleration) lying beyond threshold-bands. These bands were created using mean plus two standard deviations. Furthermore, a higher magnitude of time-varying stochastic volatility of vehicle speeds when they pass through the intersection is associated with higher crash frequencies. These measures can be used to locate intersections with high driving volatilities. A deeper analysis of these intersections can be undertaken, and proactive safety countermeasures considered to enhance safety.

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.

scholarly journals A Surrogate Video-Based Safety Methodology for Diagnosis and Evaluation of Low-Cost Pedestrian-Safety Countermeasures: The Case of Cochabamba, Bolivia

2019 ◽  
Vol 11 (17) ◽  
pp. 4737
Author(s):  
Lynn Scholl ◽  
Mohamed Elagaty ◽  
Bismarck Ledezma-Navarro ◽  
Edgar Zamora ◽  
Luis Miranda-Moreno
Keyword(s):  
Developing Countries ◽  
Latin American ◽  
Traffic Safety ◽  
Road Safety ◽  
Low Cost ◽  
Video Data ◽  
Crash Risk ◽  
Video Analytics ◽  
Crash Data ◽  
Safety Countermeasures

Due to a lack of reliable data collection systems, traffic fatalities and injuries are often under-reported in developing countries. Recent developments in surrogate road safety methods and video analytics tools offer an alternative approach that can be both lower cost and more time efficient when crash data is incomplete or missing. However, very few studies investigating pedestrian road safety in developing countries using these approaches exist. This research uses an automated video analytics tool to develop and analyze surrogate traffic safety measures and to evaluate the effectiveness of temporary low-cost countermeasures at selected pedestrian crossings at risky intersections in the city of Cochabamba, Bolivia. Specialized computer vision software is used to process hundreds of hours of video data and generate data on road users’ speed and trajectories. We find that motorcycles, turning movements, and roundabouts, are among the key factors related to pedestrian crash risk, and that the implemented treatments were effective at four-legged intersections but not at traditional-design roundabouts. This study demonstrates the applicability of the surrogate methodology based on automated video analytics in the Latin American context, where traditional methods are challenging to implement. The methodology could serve as a tool to rapidly evaluate temporary treatments before they are permanently implemented and replicated.

scholarly journals Distinguishing between Rural and Urban Road Segment Traffic Safety Based on Zero-Inflated Negative Binomial Regression Models

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Xuedong Yan ◽  
Bin Wang ◽  
Meiwu An ◽  
Cuiping Zhang
Keyword(s):  
Regression Models ◽  
Negative Binomial ◽  
Traffic Volume ◽  
Road Segment ◽  
Crash Risk ◽  
Segment Length ◽  
Crash Frequency ◽  
Urban Road ◽  
Fatal Crash ◽  
Rural And Urban

In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency were taken into consideration for distinguishing between rural and urban road segment safety. The GIS-based crash data during four and half years in Pikes Peak Area, US were applied for the analyses. The comparative statistical results show that the crash rates in rural segments are consistently lower than urban segments. Further, the regression results based on Zero-Inflated Negative Binomial (ZINB) regression models indicate that the urban areas have a higher crash risk in terms of both total crash frequency and injury and fatal crash frequency, compared to rural areas. Additionally, it is found that crash frequencies increase as traffic volume and segment length increase, though the higher traffic volume lower the likelihood of severe crash occurrence; compared to 2-lane roads, the 4-lane roads have lower crash frequencies but have a higher probability of severe crash occurrence; and better road facilities with higher free flow speed can benefit from high standard design feature thus resulting in a lower total crash frequency, but they cannot mitigate the severe crash risk.

scholarly journals Information system for the management of intelligent traffic lights

2020 ◽  
pp. 21-26
Author(s):  
Alejandro ORTIZ-FIGUEROA ◽  
Ramona Evelia CHÁVEZ-VALDEZ ◽  
Jesús Alberto VERDUZCO-RAMIREZ ◽  
Ismael VILLAVICENCIO-JACOBO
Keyword(s):  
Information System ◽  
Traffic Management ◽  
Population Increase ◽  
Traffic Light ◽  
Traffic Lights ◽  
Vehicle Data ◽  
Software Engineering Process ◽  
Unified Process ◽  
Pass Through

Derived from the population increase and urban growth, vehicle traffic has increased in the cities of Colima and Villa de Álvarez located in Mexico, and with it the problems of road safety and traffic management; the increasing number of roads and traffic lights implies recording the information of each one of these; Therefore, this article presents an information system for the management of intelligent traffic light infrastructure. In the software engineering process, the Agile Unified Process was used to manage the main risks early and guarantee the quality of the product during its life cycle. The system was tested at a prototype level with satisfactory results, as a result a web system contributes to improving road and citizen safety, since based on two vehicle data it connects with web services to other databases, and identifies Immediately form the incidents of vehicles that pass through the roads, including stolen vehicle, speeding and a panic button. The expectations are to scale it to the real environment, and make available to the corresponding authorities the information collected to favor decision-making.

Modeling the Response of a Transient Thermal System Using Gaussian Processes

2005 ◽  
Author(s):  
A. F. Emery ◽  
D. Bardot
Keyword(s):  
Response Surface ◽  
Gaussian Processes ◽  
Sampling Techniques ◽  
Thermal System ◽  
Variable Parameters ◽  
Global Sensitivity ◽  
Data Points ◽  
Parameter Interactions ◽  
Pass Through ◽  
Transient Thermal

Estimating sensitivities and the uncertainties associated with variable parameters can be prohibitively expensive for complex systems, particularly when sampling techniques, e.g., Monte Carlo, are employed. One approach is to define a response surface based on easy to compute functions using least squares fitting. However, such a surface does not pass through each of the data points and makes it difficult to determine the degree of interaction between the parameters of the system. Parameter interactions can be accurately determined using global sensitivity, but it is computationally expensive. Gaussian Processes can be used to create an inexpensive to evaluate response surface that is an accurate representation of the data. The paper describes the use of Gaussian Processes in conjunction with global sensitivity to examine the behavior of a thermal system, showing that the combination is an effective tool.

scholarly journals On Non-Tensor Product Bivariate Fractal Interpolation Surfaces on Rectangular Grids

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 525 ◽  
Author(s):  
Vasileios Drakopoulos ◽  
Polychronis Manousopoulos
Keyword(s):  
Comparative Study ◽  
Tensor Product ◽  
Necessary Conditions ◽  
Iterated Function System ◽  
Fractal Interpolation ◽  
Fractal Surfaces ◽  
Iterated Function ◽  
Data Points ◽  
Rectangular Grids ◽  
Pass Through

Some years ago, several authors tried to construct fractal surfaces which pass through a given set of data points. They used bivariable functions on rectangular grids, but the resulting surfaces failed to be continuous. A method based on their work for generating fractal interpolation surfaces is presented. Necessary conditions for the attractor of an iterated function system to be the graph of a continuous bivariable function which interpolates a given set of data are also presented here. Moreover, a comparative study for four of the most important constructions and attempts on rectangular grids is considered which points out some of their limitations and restrictions.

Identifying High-Crash-Risk Intersections

2013 ◽  
Vol 2364 (1) ◽  
pp. 44-50 ◽  
Author(s):  
In-Kyu Lim ◽  
Young-Jun Kweon
Keyword(s):  
Quality Control ◽  
Hot Spots ◽  
Empirical Bayes ◽  
Control Method ◽  
Crash Risk ◽  
Frequency Method ◽  
Traditional Methods ◽  
Crash Frequency ◽  
Potential Safety ◽  
Equivalent Property

Identifying high-crash-risk locations, called hot spots, is an important step in improving roadway safety. Use of the empirical Bayes (EB) method coupled with the use of safety performance functions (SPFs) is considered the state of the practice in identifying such locations. However, application of the EB-SPF method requires considerable resources in preparing data, as well as statistical expertise. As a consequence, many highway agencies still rely on traditional methods that use crash frequency and crash rate to identify locations for potential safety improvements without knowing the accuracy of such methods. This study examined four traditional methods commonly used in identifying potential locations for safety improvements and compared them with the EB-SPF method. The four methods evaluated were crash frequency, crash rate, rate–quality control, and equivalent property damage only. The study was limited to four-leg intersections with either a traffic signal or two-way stop control; 2004 to 2008 data were collected for 1,670 such intersections. The study found that the crash frequency method performed the best of the four in correctly identifying the top 1% of unsafe intersections. However, the method tended to flag top hot spots incorrectly. The rate–quality control method performed the best in identifying the top 5% and 10% of unsafe intersections. The findings are expected to help highway agencies that continue to use the traditional methods choose the most appropriate method so that scarce resources available for safety improvement can be invested effectively.

scholarly journals Prediction of instantaneous driving safety in emergency scenarios based on connected vehicle basic safety messages

2019 ◽  
Vol 2 (2) ◽  
pp. 78-90 ◽  
Author(s):  
Kai Yu ◽  
Liqun Peng ◽  
Xue Ding ◽  
Fan Zhang ◽  
Minrui Chen
Keyword(s):  
Safety Information ◽  
Classification Model ◽  
Driving Safety ◽  
Crash Risk ◽  
Risk Level ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Content Type ◽  
Safety Message ◽  
Vehicle Crash

Purpose Basic safety message (BSM) is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Although some safety prototypes of connected vehicle have been proposed with effective strategies, few of them are fully evaluated in terms of the significance of BSM messages on performance of safety applications when in emergency. Design/methodology/approach To address this problem, a data fusion method is proposed to capture the vehicle crash risk by extracting critical information from raw BSMs data, such as driver volition, vehicle speed, hard accelerations and braking. Thereafter, a classification model based on information-entropy and variable precision rough set (VPRS) is used for assessing the instantaneous driving safety by fusing the BSMs data from field test, and predicting the vehicle crash risk level with the driver emergency maneuvers in the next short term. Findings The findings and implications are discussed for developing an improved warning and driving assistant system by using BSMs messages. Originality/value The findings of this study are relevant to incorporation of alerts, warnings and control assists in V2V applications of connected vehicles. Such applications can help drivers identify situations where surrounding drivers are volatile, and they may avoid dangers by taking defensive actions.

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