Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

doi:10.3390/ijerph13060609

Cited by 50 publications

(36 citation statements)

References 56 publications

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“…Given the criticism against ZINB in safety studies, the present study develops random effect hurdle negative binomial and Poisson models to study crash frequency on fine time scales as a complementary study to our prior research [26]. Firstly, random effect models including REHNB, REHP, RENB and REP are established to study the daily crash frequency with the panel data.…”

Section: Discussionmentioning

confidence: 99%

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Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

Chen

et al. 2016

IJERPH

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Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are merged into the models incorporating road characteristics. The random effect hurdle negative binomial (REHNB) model is developed to study the daily crash frequency along with three other competing models. The proposed model considers the serial correlation of observations, the unbalanced panel-data structure, and dominating zeroes. Based on several statistical tests, the REHNB model is identified as the most appropriate one among four candidate models for a typical mountainous highway. The results show that: (1) the presence of over-dispersion in the short-term crash frequency data is due to both excess zeros and unobserved heterogeneity in the crash data; and (2) the REHNB model is suitable for this type of data. Moreover, time-varying variables including weather conditions, road surface conditions and traffic conditions are found to play importation roles in crash frequency. Besides the methodological advancements, the proposed technology bears great potential for engineering applications to develop short-term crash frequency models by utilizing detailed data from field monitoring data such as RWIS, which is becoming more accessible around the world.

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Section: Discussionmentioning

confidence: 99%

“…A previous study by the authors examined hourly crash frequency using the ZINB model and showed that ZINB is capable of addressing preponderance zeroes in crash data [26]. However, zero-inflated models used for crash prediction also received some criticisms because of the structural-zero assumption [27,28].…”

Section: Introductionmentioning

confidence: 99%

Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

Chen

et al. 2016

IJERPH

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“…This system has a separate right of way, which has no influence on the current ground transportation system. In the case of crowed urban space and traffic congestion on the road system, it can effectively alleviate traffic pressure and contribute to injury prevention [5,6,7,8,9,10]. Furthermore, suspended monorail transit systems have many advantages, including low manufacturing cost, short construction time and high driving safety and quality, which attracts much attention.…”

Section: Introductionmentioning

confidence: 99%

A Case Study of Dynamic Response Analysis and Safety Assessment for a Suspended Monorail System

Bao

Ding

2016

IJERPH

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A suspended monorail transit system is a category of urban rail transit, which is effective in alleviating traffic pressure and injury prevention. Meanwhile, with the advantages of low cost and short construction time, suspended monorail transit systems show vast potential for future development. However, the suspended monorail has not been systematically studied in China, and there is a lack of relevant knowledge and analytical methods. To ensure the health and reliability of a suspended monorail transit system, the driving safety of vehicles and structure dynamic behaviors when vehicles are running on the bridge should be analyzed and evaluated. Based on the method of vehicle-bridge coupling vibration theory, the finite element method (FEM) software ANSYS and multi-body dynamics software SIMPACK are adopted respectively to establish the finite element model for bridge and the multi-body vehicle. A co-simulation method is employed to investigate the vehicle-bridge coupling vibration for the transit system. The traffic operation factors, including train formation, track irregularity and tire stiffness, are incorporated into the models separately to analyze the bridge and vehicle responses. The results show that the coupling of dynamic effects of the suspended monorail system between vehicle and bridge are significant in the case studied, and it is strongly suggested to take necessary measures for vibration suppression. The simulation of track irregularity is a critical factor for its vibration safety, and the track irregularity of A-level road roughness negatively influences the system vibration safety.

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“…In more recent studies, it is reported that accident counts display an excess presence of zeros than would be expected from either a Poisson or a negative binomial distribution (Chen et al 2016;Dong et al 2016;Kumara & Chin 2003;Qin et al 2004). This raises the issue of finding a more suitable distribution.…”

Section: Introductionmentioning

confidence: 98%

The Extra Zeros in Traffic Accident Data: A Study on the Mixture of Discrete Distributions

Zamzuri¹,

Sapuan

Ibrahim³

2018

JSM

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The presence of extra zeros is commonly observed in traffic accident count data. Past research opt to the zero altered models and explain that the zeros are sourced from under reporting situation. However, there is also an argument against this statement since the zeros could be sourced from Poisson trial process. Motivated by the argument, we explore the possibility of mixing several discrete distributions that can contribute to the presence of extra zeros. Four simulation studies were conducted based on two accident scenarios and two discrete distributions: Poisson and negative binomial; by considering six combinations of proportion values correspond to low, moderate and high mean values in the distribution. The results of the simulation studies concur with the claim as the presence of extra zeros is detected in most cases of mixed Poisson and mixed negative binomial data. Data sets that are dominated by Poisson (or negative binomial) with low mean show an apparent existence of extra zeros although the sample size is only 30. An illustration using a real data set concur the same findings. Hence, it is essential to consider the mixed discrete distributions as potential distributions when dealing with count data with extra zeros. This study contributes on creating awareness of the possible alternative distributions for count data with extra zeros especially in traffic accident applications. ABSTRAKKehadiran lebihan sifar sering dicerap dalam data bilangan kemalangan jalan raya. Kajian lepas cenderung kepada penggunaan model dengan ubah suaian sifar dan menjelaskan bahawa lebihan sifar ini berpunca daripada keadaan kemalangan tidak terlapor. Walau bagaimanapun, terdapat tentangan terhadap pernyataan ini dengan kehadiran lebihan sifar ini boleh berpunca daripada campuran beberapa taburan diskret yang mewakili taburan bagi masa atau lokasi berbeza. Maka, kajian ini bermatlamat untuk meneroka teori bahawa taburan disket tercampur boleh menyumbang kepada lebihan sifar dalam data bilangan. Empat kajian simulasi dijalankan berdasarkan dua senario kemalangan dan dua taburan diskret: Poisson dan binomial negatif; dengan mengambil kira enam gabungan nilai perkadaran bagi nilai purata rendah, sederhana dan tinggi dalam taburan tersebut. Keputusan kajian bersetuju dengan teori tersebut dengan kehadiran lebihan sifar dapat dikenal pasti dalam kebanyakan kes data Poisson tercampur dan binomial negatif tercampur. Set data yang didominasi oleh Poisson (atau binomial negatif) dengan nilai purata rendah menunjukkan bilangan lebihan sifar yang ketara walaupun saiz sampel hanyalah 30. Oleh itu, adalah amat penting bagi pengkaji untuk mengambil kira taburan diskret tercampur ini apabila berhadapan data bilangan dengan lebihan sifar. Kajian ini menyumbang dalam mencetus kesedaran berkenaan potensi taburan alternatif untuk data bilangan terlebih sifar terutamanya dalam aplikasi kemalangan jalan raya.

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Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

Cited by 50 publications

References 56 publications

Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

A Case Study of Dynamic Response Analysis and Safety Assessment for a Suspended Monorail System

The Extra Zeros in Traffic Accident Data: A Study on the Mixture of Discrete Distributions

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