Dataset Information

The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation.

ABSTRACT: This paper presents the use of the Aimsun microsimulation program to simulate vehicle violating behaviors and observe their impact on road traffic crash risk. Plugins for violations of speeding, slow driving, and abrupt stopping were developed using Aimsun's API and SDK module. A safety analysis plugin for investigating probability of rear-end collisions was developed, and a method for analyzing collision risk is proposed. A Fuzzy C-mean Clustering algorithm was developed to identify high risk states in different road segments over time. Results of a simulation experiment based on the G15 Expressway in Shanghai showed that abrupt stopping had the greatest impact on increasing collision risk, and the impact of violations increased with traffic volume. The methodology allows for the evaluation and monitoring of risks, alerting of road hazards, and identification of hotspots, and could be applied to the operations of existing facilities or planning of future ones.

SUBMITTER: Wang J

PROVIDER: S-EPMC5590972 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation.

Wang Junhua J Kong Yumeng Y Fu Ting T Stipancic Joshua J

PloS one 20170908 9

This paper presents the use of the Aimsun microsimulation program to simulate vehicle violating behaviors and observe their impact on road traffic crash risk. Plugins for violations of speeding, slow driving, and abrupt stopping were developed using Aimsun's API and SDK module. A safety analysis plugin for investigating probability of rear-end collisions was developed, and a method for analyzing collision risk is proposed. A Fuzzy C-mean Clustering algorithm was developed to identify high risk s ...[more]

PMID: 28886141

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Project description:BACKGROUND:Law enforcement traffic stops are one of the most common entryways to the US justice system. Conventional frameworks suggest traffic stops promote public safety by reducing dangerous driving practices and non-vehicular crime. Law enforcement agencies have wide latitude in enforcement, including prioritization of stop types: (1) safety (e.g. moving violation) stops, (2) investigatory stops, or (3) economic (regulatory and equipment) stops. In order to prevent traffic crash fatalities and reduce racial disparities, the police department of Fayetteville, North Carolina significantly re-prioritized safety stops. METHODS:Annual traffic stop, motor vehicle crash, and crime data from 2002 to 2016 were combined to examine intervention (2013-2016) effects. Fayetteville was compared against synthetic control agencies built from 8 similar North Carolina agencies by weighted matching on pre-intervention period trends and comparison against post-intervention trends. RESULTS:On average over the intervention period as compared to synthetic controls, Fayetteville increased both the number of safety stops + 121% (95% confidence interval + 17%, + 318%) and the relative proportion of safety stops (+ 47%). Traffic crash and injury outcomes were reduced, including traffic fatalities - 28% (- 64%, + 43%), injurious crashes - 23% (- 49%, + 16%), and total crashes - 13% (- 48%, + 21%). Disparity measures were reduced, including Black percent of traffic stops - 7% (- 9%, - 5%) and Black vs. White traffic stop rate ratio - 21% (- 29%, - 13%). In contrast to the Ferguson Effect hypothesis, the relative de-prioritization of investigatory stops was not associated with an increase in non-traffic crime outcomes, which were reduced or unchanged, including index crimes - 10% (- 25%, + 8%) and violent crimes - 2% (- 33%, + 43%). Confidence intervals were estimated using a different technique and, given small samples, may be asymmetrical. CONCLUSIONS:The re-prioritization of traffic stop types by law enforcement agencies may have positive public health consequences both for motor vehicle injury and racial disparity outcomes while having little impact on non-traffic crime.

Project description:ObjectiveTo determine whether emergency physicians (EPs) and prehospital emergency medical services (EMS) personnel differ in their assessment of motor vehicle crash (MVC) severity and the potential for serious injury when viewing crash scene photographs.MethodsAttending and resident EPs, paramedics, and emergency medical technicians (EMTs) from a single emergency medicine system used a web-based survey platform to rate the severity of 100 crash photographs on a 10-point Likert scale (Crash Score) and the potential for serious injury on a 0-100% scale (Injury Score). Serious injury was defined as skull fracture or intracranial bleeding, spine fracture or spinal cord injury, intrathoracic or intraabdominal injury, or long bone fracture. Crash and Injury Scores were stratified into EP and paramedic/EMT (EMS) groups and the mean score was calculated for each photo. Spearman rank correlation coefficients with 95% confidence intervals (95% CI) and Bland-Altman plots were constructed to assess agreement. Secondary analyses were performed after categorizing data into quartiles based on participants' estimations of MVC severity.ResultsA total of 54 attending and 53 resident EPs, 156 paramedics, and 34 EMTs were invited to participate in the survey. Of these, 39 (72%) attending and 46 (87%) resident EPs, 107 (69%) paramedics, and 17 (50%) EMTs completed the survey. A total of 183 (88%) surveys were completed in full. The overall Crash Score correlation coefficient between EPs and EMS was 0.98 (95% CI, 0.97-0.99). The Crash Score correlation coefficients for each quartile were 0.86 (0.57-0.97), 0.93 (0.85-0.96), 0.58 (0.16-0.85), and 0.88 (0.66-0.97), respectively. The overall Injury Score correlation coefficient between EPs and EMS was 0.98 (0.88-0.97). The Injury Score correlation coefficients for each quartile were 0.94 (0.48-0.91), 0.76 (0.50-0.92), 0.80 (0.69-1.00), and 0.94 (0.57-0.97), respectively.ConclusionAlthough overall agreement between EPs and EMS personnel was excellent, differences in estimation of crash severity and potential for injury were identified among crashes estimated to be moderate in severity.

Dataset Information

The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation.

Publications

The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation.

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