Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway

Ahmed, Mohamed M.; Huang, Hongwei; Abdel-Aty, Mohamed; Guevara, Bernardo

doi:10.1016/j.aap.2011.03.021

Cited by 174 publications

(87 citation statements)

References 43 publications

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“…The crash exposure of a roadway segment is generally associated with its length and the traffic volume. Forms proposed in previous studies include annual average daily traffic [20] and vehicle miles traveled [1]. In the current research, the observational time unit is month.…”

Section: Poisson Modelmentioning

confidence: 99%

“…To account for important issues related to crash data such as overdispersion, underdispersion, excess zero observations, spatiotemporal correlation, multilevel structures, and unobserved heterogeneity, a great many Poisson model variations have been proposed, which significantly improve model fit and predictive performance [3,6]. With more recent advances in crash prediction modeling, Bayesian inference has been extensively applied to traffic safety analysis because of its ability to deal with complex models (often without closed-form likelihood functions) such as the hierarchical model [1,2], spatiotemporal model [7,8], random parameters model [9], and multivariate model [10] and through these [8].…”

Section: Introductionmentioning

confidence: 99%

“…This diversity in freeway traffic composition may result in numerous vehicle interactions, and the high speeds result in shorter driver response times when encountering emergencies. Freeways in mountainous areas may also suffer from poor geometrical design and adverse weather conditions [1,2], which increase the crash risk. Developing a crash prediction model (or safety performance function) that provides a good understanding of the crash occurrence mechanism on a freeway is thus vital [1] when ranking sites for safety improvement and for accurately evaluating the effectiveness of countermeasures.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation

Zeng

Sun

Wen

2017

Journal of Advanced Transportation

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As the basis of traffic safety management, crash prediction models have long been a prominent focus in the field of freeway safety research. Studies usually take years or seasons as the observed time units, which may result in heterogeneity in crash frequency. To eliminate that heterogeneity, this study analyzes monthly crash counts and develops Bayesian hierarchical models with random effects, lag-1 autoregression (AR-1), and both (REAR-1) to accommodate the multilevel structure and temporal correlation in crash data. The candidate models are estimated and evaluated in the freeware WinBUGS using a crash dataset obtained from the Kaiyang Freeway in Guangdong Province, China. Significant temporal effects are found in the three models, and Deviance Information Criteria (DIC) results show that taking temporal correlation into account considerably improves the model fit compared with the Poisson model. The hierarchical models also avoid any misidentification of the factors with significant safety effects, because their variances are greater than in the Poisson model. The DIC value of the AR-1 model is substantially lower than that of the random effect model and equivalent to that of the REAR-1 model, which indicates the superiority of the lag-1 autoregressive structure in accounting for the temporal effects in crash frequency.

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Section: Poisson Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation

Zeng

Sun

Wen

2017

Journal of Advanced Transportation

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“…Intersections controlled by a signalized traffic light. Square, intersection of a circular, one-way, and without traffic lights equipment, in which the traffic flow moves around a circular island to separate vehicles that travel in different directions and to reduce the number of collisions and also better traffic guidance is trying to separate the intersections of the level [8].…”

Section: Urban Intersectionsmentioning

confidence: 99%

Modeling and Evaluation of Intelligent Monitoring Systems at Urban Intersections to Improve Real-Time Monitoring of Congestion and Traffic Safety

Fatholahzadeh¹,

Akbarizadeh²,

Romoozi³

2018

IJCATR

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Abstract:In recent decades, with the advent of technology and information technology, transportation systems have also been moving in this direction, and one of the challenges of the transportation system is due to the multiplicity and increase of vehicle management and control. Many techniques and methods have been proposed in this field that in today's world, the use of intelligent systems has a higher efficiency. In fact, safety has the ability to reduce the number of vehicles with minimal delay and create discomfort for the users depends directly in order and arrangement to facilitate the immediate and direct involvement of the vehicle in traffic flow. One of the ways to demonstrate the efficiency of intelligent monitoring systems is create model before the implementation phase. This article aims at modeling and evaluating an intelligent surveillance system at urban intersections, which is carried out using colored petri nets. In the proposed method, first, the urban intersection architecture is described with the benefit of traffic rules then, the inconsistency and coincidence states are determined and finally, reliability and response time are measured by the CpnTools with the help of Petri Nets. The results show that the intelligent monitoring equipment related to the intelligent surveillance system increases the safety of the road network and, finally, has secured and fluent traffic.

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“…Many researchers have done much work to figure out the relationship. Based on 6-year crash data of a freeway in Colorado, Ahmed et al [14] used Poisson models and Bayesian to obtain significant factors associated with crash risk and results indicated that roadway geometry significantly affects crash risk, segments with steep downgrades drastically increase the crash risk, and compared to dry season, crash risk could be increased significantly during snow season. Kononov et al [15] examined the relationship of traffic flow with safety via the data collected from existing automatic traffic recording stations around the Denver, Colorado, metropolitan area for four-lane freeways and a segment of Interstate 70 and found that as the flow increases, the crash rate initially remains constant until a certain critical threshold combination speed and density is reached and once the threshold is exceeded, the crash rate rapidly rises.…”

Section: Introductionmentioning

confidence: 99%

What leads to severe mountainous freeway crashes in southeast of China?

et al. 2016

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Original scientific paper This paper adopted chi-square test and binary logistic regression to analyse factors about mountainous freeway crash severity level in the southeast of China and to determine the factor impact on crash severity level to make corresponding measures to improve road safety. Results of this paper indicated that younger and older drivers, female drivers, weekends and driving early in morning all make contribution to severe mountainous freeway crashes. Besides, it is more likely to occur in severe crash in spring, summer and autumn compared to that in winter. The importance of study results to audience is that road users can understand the specific characteristics of mountainous freeway crashes in southeast of China and corresponding measurements could be made to improve the safety level. Therefore, this paper proposed some suggestions to improve mountainous freeway safety: younger and older drivers should be told the driving weakness by means of variable message sign or propaganda; female drivers are not encouraged to drive in some special mountainous freeway sections; traffic designs about careful driving at night are supposed to be set especially between 0 am and 5:59 am. Keywords: binary logistic regression; chi-square test; crash severity level; mountainous freeway; road safety Zbog čega dolazi do teških sudara na brdskim cestama u jugoistočnoj Kini?Izvorni znanstveni članak U radu je primijenjen hi-kvadrat test i binarna logistička regresija u analizi faktora koji dovode do teških sudara na brdskim cestama na jugoistoku Kine i određivanju njihova utjecaja na stupanj težine sudara u svrhu poduzimanja odgovarajućih mjera za poboljšanje sigurnosti na cesti. Rezultati su pokazali da mlađi i stariji vozači, žene, vožnja vikendom i rano ujutro, doprinose težini sudara. Uz to, vjerojatnije je da će se teški sudari dogoditi u proljeće, ljeto i jesen, nego zimi. Važnost dobivenih rezultata je u tome što vozači mogu razumjeti specifične karakteristike sudara na brdskoj autocesti na jugoistoku Kine te se mogu poduzeti odgovarajuće mjere da se stupanj sigurnosti poveća. Stoga se u radu daju sugestije za povećanje sigurnosti; mlađe i starije vozače treba upozoriti postavljanjem raznih prometnih znakova ili propagandom; vozačicama se savjetuje da ne voze na nekim dijelovima te ceste; upozorenja bi trebalo postaviti o pažljivoj vožnji noću naročito između 0 i 5:59 ujutro.

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Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway

Cited by 174 publications

References 43 publications

Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation

Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation

Modeling and Evaluation of Intelligent Monitoring Systems at Urban Intersections to Improve Real-Time Monitoring of Congestion and Traffic Safety

What leads to severe mountainous freeway crashes in southeast of China?

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