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Record W2777813056 · doi:10.32469/10355/62243

Transportation safety modeling and evaluation : alternative geometric designs, enforcement, and airfield applications

2017· dissertation· en· W2777813056 on OpenAlexfundno aff
Boris Claros

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of MissouriVirginia Space Grant Consortium
KeywordsCrashIntersection (aeronautics)Transport engineeringEnforcementCollisionEngineeringGeometric designComputer scienceComputer security

Abstract

fetched live from OpenAlex

A top priority of transportation agencies in the United States is to improve safety of transportation facilities through the use of latest technology, innovative designs, procedural methods, and training practices to decrease fatalities, injuries, and property damage. In order to continue improving roadway safety, different approaches such as alternative designs have been considered. Alternative designs for roadway facilities include J-turn for minor roads and high-speed expressway intersections, the Diverging Diamond Interchange (DDI) for freeway interchanges, or red light cameras for signalized intersections. There is limited research evaluating the safety effectiveness of recently implemented alternative designs and enforcement strategies. This dissertation focused on developing jurisdiction specific crash prediction models, calibrating existing models, and applying rigorous statistical methods to study the safety effectiveness of these new alternative treatments. This dissertation found that the DDI design replacing a conventional diamond decreased crash frequency for all severities. Fatal and injury (FI) crashes experienced a 62.6 percent reduction. Property damage only (PDO) crashes reduced by 35.1 percent and total (TOT) crashes decreased by 47.9 percent. The collision diagram analysis of the DDI showed that the top two crash types were: 1) rear end collisions between right turning movements on the exit ramp at the intersection, and 2) rear end collisions on the outside crossroad approach leg to the ramp terminal. The DDI design traded a severe crash type, right angle left turn crash, with less severe rear end, sideswipe, and loss of control crash types. Wrong way crashes inside the crossroad between ramp terminals accounted for 4.8 percent of the FI crashes occurring at the DDI. This dissertation also examined the DDI safety effect on two adjacent facilities: speed change lanes and major signalized intersections. There is no strong evidence that DDIs impacted the safety of adjacent roadway facilities, either positively or negatively. Another alternative intersection design studied in this dissertation was the J-turn intersection. The safety evaluation of the implementation of the J-turn replacing two-way stopcontrolled intersections was effective at decreasing FI crashes by 63.8 percent and TOT crashes by 31.2 percent. The collision diagram analysis showed that the most recurrent crashes were sideswipe with 31.6 percent and rear end with 28.1 percent on the main road. Red light running was also evaluated in this dissertation. The implementation of red light running cameras in Missouri resulted in a reduction of FI crashes by 7.4 percent and increase in PDO crashes by 3.8 percent. Additionally, right angle crashes were reduced across all severities, including 14.5 percent for FI crashes. Rear end crashes increased by 16.5 percent overall. The crash cost benefit results showed a positive net economic benefit of $35,269 per site per year in 2001 dollars (approximately $47,000 in 2015 dollars). It translated into an overall 5.0 percent economic crash cost benefit. In addition to roadway safety, this dissertation also evaluated airfield safety. In the field of aviation, runway incursions are the incorrect presence of and aircraft, vehicle or person on an active runway designated for takeoff and landing. Runway incursions can result in property damage or loss of life through incidents leading to aircraft collisions or avoidance maneuvers. Efforts are on the rise to reduce the risk of runway incursions at airports. However, guidance is mostly qualitative and does not provide specific quantitative measures to predict runway incursion frequency and evaluate the effectiveness of treatments. This dissertation adapted statistical roadway safety modeling to airport airfield operations. The transferability of roadway safety modeling theory was possible because airfield operations share similar measures of exposure and hazard concepts. Thus, models were developed to estimate runway incursion frequency for hub airports in the United States. Assessing runway incursion frequency and treatment effectiveness with quantitative measures enables a more straightforward comparison of different facilities, alternatives, and treatments. The models developed in this dissertation contribute to decision making and the implementation of cost effective countermeasures to mitigate runway incursions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.288
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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