A Macrolevel tabu-search based approach to determine the major factors in built environment-traffic safety relationship

Download

12626307.pdf

Date

2021-3-05

Author

Alişan, Onur

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

454
views

487
downloads

Traffic crashes are a significant contributing factor to fatalities globally, with an increasing pace of crashes occurring in urban areas. Thus, this study aims to analyze the relationship between urban built environment and traffic safety (BE-TS) to reveal the factors that threaten TS so that they could be avoided in early planning phases. BE was operationalized through the D-classification (e.g., density and diversity) whereas, TS was operationalized through varying crash categories (e.g., severity) and representation (i.e., frequency and density). A GIS-based process was applied to assign crashes and BE variables at the census block group level, followed by a dimension reduction process to eliminate correlated variables in an extensive set. Then the relationship between BE and TS was examined through a series of generalized linear regression models with several statistical distributions. A tabu-search-based model generation was applied to each BE-TS model to identify the set of BE variables that minimizes the modeling error. Moreover, variables were traced during the algorithm to identify consistent and then critical variables. Those models were analyzed for varying case studies, two cases within the developed country context, from the US, single county (Leon), and tri-county (Broward, Miami-Dade, and Palm-Beach) cases; and a case within developing country context, from Turkey (Konya). According to the results, exposure variables (e.g., bus stops and traffic volume) have positive associations with all crash types. However, there are variables with mixed relations (e.g., primary road percentage has positive relations with crash types except for vulnerable road user involved crashes, and employment density has positive or negative impacts according to the local economic structure). Finally, non-motorized modes are found to have positive, and motorized modes are found to have negative associations with all crash types within the developed country context, which are not common in safety research.

Subject Keywords

Built Environment, Traffic Safety, Crash Frequency, Subset Selection, Tabu-Search

URI

https://hdl.handle.net/11511/89653

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

A Multimodal Approach for Aggressive Driving Detection Kumtepe, Omurcan; Yuncu, Enes; Akar, Gözde (2016-05-19) Aggressive driving behavior is among the important causes of traffic accidents. Hence, detection of driver aggressiveness has an importance in terms of decreasing the number of traffic accidents. Collected driving data while the vehicle is in traffic can be used to make inferences about the aggressiveness of the driver. In this study, a multimodal method is proposed in order to detect driver aggressiveness. The proposed method is based on utilizing the visual data taken from the on vehicle camera and sensor...
Tabu-Search-Based Combinatorial Subset Selection Approach to Support Investigation of Built Environment and Traffic Safety Relationship Alisan, Onur; Tüydeş Yaman, Hediye; Ozguven, Eren Erman (2022-07-01) Traffic crashes are a leading cause of death globally, with an increasing rate in urban areas. Thus, this study focuses on the relationship between built environment (BE) and traffic safety (TS), by constructing a relationship model using BE variables. The aim of this paper is to determine the best subset of BE variables through a generalizable methodology. The BE is operationalized through the D-classification (e.g., density, diversity, and design), and various datasets are collected from different agencie...
An approach to investigate relationship between speed and safety on urban arterials Ardiç Eminağa, Zerrin; Akyılmaz, M. Özdemir; Department of Civil Engineering (2008) Traffic safety is an important problem in today’s world with increasing number of fatalities and injuries in traffic accidents. For the solution of this problem, determination of accident prone locations on a network and reasons behind is an essential step, which is studied to some extend via different traffic accident analyses in the literature. While major factors affecting accident risk, such as speed, congestion, infrastructural aspects are known, it is still very difficult to figure out the interaction...
A comparison of roadside design approaches in terms of road safety to improve Turkish roadside safety standards Betus, Yakup; Tüydeş Yaman, Hediye; Department of Civil Engineering (2022-5-31) When an errant vehicle runs off the road, crashing into objects/ reaching places in the vicinity creates “run-off-road (ROR)” accidents, which may result in severe injuries or fatalities. Roadside designs with proper Road Restraint Systems (RRS) ideally should cause neither hazards to the third parties nor threats to the vehicle users. The major components of the RRSs are the Vehicle Restraint Systems (VRS), including the safety barriers (i.e., guardrails) designed to i) either stop the errant vehicle fully...
An innovative model integrating spatial and statistical analyses for a comprehensive traffic accident study Şener, İpek Neşe; İnal, Ayhan; Department of Civil Engineering (2004) The negative social and economic results of traffic accidents are the most serious problems within the concept of traffic safety. Every year, unfortunately, a huge number of traffic accidents result in destructive losses. Especially, when the holiness of human life is concerned, traffic safety has an invaluable role for the traffic improvement strategies. In this manner, Turkey places one of the highest ranks regarding the growing rate and severity of traffic accidents that should be immediately taken under...

Citation Formats

O. Alişan, “A Macrolevel tabu-search based approach to determine the major factors in built environment-traffic safety relationship,” Ph.D. - Doctoral Program, Middle East Technical University, 2021.