Frailty Models for the Estimation of Spatiotemporally Maximum Congested Impact Information on Freeway Accidents

Abstract

The objective of this paper is to develop models for the estimation of the temporal and spatial extent of congestion impact caused by accidents. Although there have been various approaches based on the deterministic queuing diagrams and kinematic wave (or shockwave) theory, only a few studies have been able to estimate the spatiotemporal congested region based on field data, such as ubiquitous loop detector data. Accordingly, this paper applies a previously developed procedure to capture the spatiotemporal accident impacts based on binary integer programming (BIP). The procedure provides a foundation for models of the following: 1) maximum spatial distance to the end of the congestion region affected by each accident and 2) maximum time affected by congestion resulting from each accident. Based on these models, the objective of this paper is to estimate two statistical models for providing maximum congested distance and time information due to freeway accidents. Since various observations from BIP were censored with respect to time and space, survival analysis-specifically, frailty models to account for unobserved heterogeneity-is applied to identify factors critical to spatiotemporal congestion impacts of freeway accidents.

Driver's braking behavior approaching pedestrian crossings: a parametric duration model of the speed reduction times

“…To taking into account the effects of the repeated measures on the individual observations, two possible extensions of the AFT model could be used: Weibull regression model with clustered heterogeneity and Weibull regression model with shared frailty. Several previous studies applied the frailty type models in order to include the unobserved heterogeneity (i.e., frailty) with the aim of exploring the effect of freeway work zones on the non‐recurrent traffic congestion , estimating the capacity reduction that is attributable to accidents in the opposite direction of accident and developing models for the estimation of the temporal and spatial extent of congestion impact caused by accidents .…”

Ellipse-Like Radiation Range Grading Method of Traffic Accident Influence on Mountain Highways

“…The research on the temporal and spatial impact propagation of accidents can further grasp the dynamic evolution process of accidents and help to predict the potential degrees of congestion caused by accidents. Researchers mostly have used the deterministic queuing diagram and the motion wave (shock wave) theory to analyze the influence of accidents on the surrounding road network and the principle of accidents from the perspective of time and space [15][16][17][18]. Moskowitz and Newman first proposed a deterministic queuing graph method to study the impact of the downstream capacity of bottleneck sections, that is, to estimate the cumulative total delay value of vehicles from the queuing graph, but it is difficult to reflect the repeated congestion after the accident [19]; Lawson et al proposed an improved queuing graph method to measure the spatiotemporal impact of bottlenecks, but there are still limitations in practical applications, especially when capacity changes occur many times [20].…”

Identification of Critical Factors for Non-Recurrent Congestion Induced by Urban Freeway Crashes and Its Mitigating Strategies

“…However, survival analysis can be applied to a wide variety of random variables beyond those strictly representing the end of life or failure of a machine. Applications in the transportation area include, for example, the occurrence of traffic crashes [24,25], incident duration [26][27][28][29][30], households' vehicle ownership duration [31][32][33][34], and traffic congestion [3,23,[35][36][37][38].…”