Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

doi:10.1016/j.jsr.2018.02.010

Cited by 182 publications

(124 citation statements)

References 51 publications

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“…In the light of these two defects discussed above, there are some researchers who have improved their studies by using the approach of RPLM when investigating the effect of the factors on dependent variables in other traffic research areas. Anastaspopoulos et al [18] investigated the effect of the related factors on the delay of highway project using the Journal of Advanced Transportation 3 [17,[20][21][22][23][24]. However, few researches apply RPLM to pedestrians' and (electric) bicyclists' IRLR behaviours at intersections.…”

Section: Literature Reviewmentioning

confidence: 99%

A Random Parameter Logit Model of Immediate Red-Light Running Behavior of Pedestrians and Cyclists at Major-Major Intersections

Wang

Yuan

Liu

et al. 2019

Journal of Advanced Transportation

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It is a dangerous behaviour for pedestrians and nonmotorized vehicles to cross intersections without waiting when they arrive at intersections during the red-light period. This paper investigates three typical signalized major-major intersections in the center of Beijing, by collecting and analyzing 1368 samples of pedestrians and nonmotorized vehicles. A random parameter logit model (RPLM) is established, with immediate red-light running (IRLR) behaviour as the dependent variable. The results show that the number of people waiting upon arrival, number of people crossing upon arrival, traffic mode, motor vehicle phase upon arrival, and speed change upon arrival have significant effects on IRLR behaviour. Accordingly, we suggest enforcing education administration on cyclists to reduce cyclists' IRLR behaviour. Thus, people's red-light running (RLR) behaviour will further decrease with fewer cyclists' IRLR behaviour. Accordingly, the safety of pedestrians and nonmotorized vehicles at signalized intersections has attracted the

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Section: Literature Reviewmentioning

confidence: 99%

A Random Parameter Logit Model of Immediate Red-Light Running Behavior of Pedestrians and Cyclists at Major-Major Intersections

Wang

Yuan

Liu

et al. 2019

Journal of Advanced Transportation

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“…Bielli et al [22,23] proposed a new method to calculate fitness function value for bus network optimization by using a genetic algorithm to generate a new iterative population (bus network set). Lam et al [24][25][26][27] put forward the analysis of rail transit and bus transfer service optimization system. The results show that the joint implementation of intermodal public transport and other plans can significantly improve the performance of the social multimodal transport system.…”

Section: Coordination and Optimization Of Rail And Public Transportmentioning

confidence: 99%

Optimizing Bus Line Based on Metro-Bus Integration

Wei

Long

et al. 2020

Sustainability

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Metros are usually built and added on the basis of a completed bus network in Chinese cities. After the metro construction, it is faced with the problem of how to adjust and optimize the original bus lines based on the new metro system. This research mainly proposes a bus line optimization method based on bus and metro integration. In the consideration of the geographical space, the cooperation and competition relationship between bus and metro lines is qualitatively introduced according to the geographical location and service range of metro (800 m radius) and bus (500 m radius) stations. The competition and cooperation indexe sare applied to define the co-opetition relationship between bus and metro lines. The bus line optimization model is constructed based on the co-opetition coefficient and Changsha Metro Line Number 2 is chosen as a case study to verify the optimization model. The results show that the positive competition, efficient cooperation, and travel efficiency between metro and bus has been significantly enhanced after optimization. Moreover, this paper provides a reasonable reference for public transport network planning and resource allocation.

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“…Third, to determine trends in rates per 100,000 population of crashes and hospitalisations from crashes, as well as trends in TAC claims that involved hospitalisation as a proportion of all hospitalisations, Poisson regression analyses (with the exposed population size as offset) were conducted. The Poisson distribution was assumed given the count nature of the data: the use of Poisson models for count data is common in both compensation [38][39][40][41][42][43] and crash likelihood prediction [44] studies. In this study, the regression analyses examined the association between year and the outcome of interest.…”

Section: Data Definitions and Analysis Strategymentioning

confidence: 99%

Trends in lawyer use in road traffic injury compensation claims

2020

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Injury compensation claimants use legal services to help them navigate compensation schemes, including accessing benefits and resolving disputes. Little is known, however, about the extent of lawyer use by compensation claimants, including changes over time. This paper presents findings from one of the largest empirical investigations of lawyer use in an injury compensation setting to date. Using evidence from more than 275,000 claims in the road traffic injury scheme in the state of Victoria, Australia, this study examines the prevalence of, and changes in, lawyer use between 2000 and 2015. The analysis identifies a significant increase in the use of lawyers in the scheme, and explores possible explanations. This study provides critical insights into lawyer use in compensation settings: the steep increase in lawyer involvement has both access to justice and financial implications for compensation schemes, given the associations between lawyer use, claimant outcomes, and long-term scheme viability. OPEN ACCESSCitation: Scollay CE, Berecki-Gisolf J, Grant GM (2020) Trends in lawyer use in road traffic injury compensation claims. PLoS ONE 15(4): e0231025.

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Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data

Cited by 182 publications

References 51 publications

A Random Parameter Logit Model of Immediate Red-Light Running Behavior of Pedestrians and Cyclists at Major-Major Intersections

A Random Parameter Logit Model of Immediate Red-Light Running Behavior of Pedestrians and Cyclists at Major-Major Intersections

Optimizing Bus Line Based on Metro-Bus Integration

Trends in lawyer use in road traffic injury compensation claims

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