Effect of increasing the freeway posted speed limit on entry ramp speed-change lane crash frequency

Tagar, Synthia; Pulugurtha, Srinivas S.

doi:10.1016/j.treng.2021.100067

Cited by 7 publications

(4 citation statements)

References 36 publications

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“…The increase in crash frequency at the higher posted speed limit is expected since increased speeds are known to entail a higher risk of a crash. In that regard, several studies have demonstrated the positive exponential relationship between the speed limit and crashes ( 37 , 68–70 ). In alignment with this study, the previous study of Alhomaidat et al ( 71 ) indicated a 13.9 percent increase in arterial road crash frequency as a result of 5 mph increase in adjacent freeway speed limits.…”

Section: Discussionmentioning

confidence: 99%

Segment-Level Spatial Spillover Effects of Exogenous Characteristics of Arterials on Crash Frequency

Atumo

Zhang²,

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Studies of spatial effects on road traffic safety are highly skewed in relation to aggregation units. As a result, the spatial effect of road traffic crashes at segment-level aggregation is rarely investigated. In light of that, this study investigates spatial spillover effects to determine the effects of independent variable changes initiated in one segment on the dependent variable of its neighboring segments. Additionally, the performance of the implemented models is evaluated under five different spatial weighting approaches. Spatial spillover effect of fatal and injury crashes aggregated at the segment level is estimated with the spatial lag of explanatory variables model under the general framework of Poisson and negative binomial models. The results indicate (i) spatial spillover effects are better modeled with spatial relation conceptualized by inverse distance spatial weighting schemes; (ii) spatial lag of explanatory variables under negative binomial and inverse distance spatial weighting provides the best model fitting; (iii) exogenous interactions among influence factors of fatal and injury crashes have a noteworthy effect in determining the crash frequency of neighboring segments. Convincingly, spatial spillover effect seems to significantly affect the results of conventional count modeling at the segment levels. To that effect, this study expects to provide empirical evidence and complement the existing literature on the impact of changes in explanatory variables initiated in a given segment on the safety of segments in proximity.

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Section: Discussionmentioning

confidence: 99%

Segment-Level Spatial Spillover Effects of Exogenous Characteristics of Arterials on Crash Frequency

Atumo

Zhang²,

et al. 2023

Transportation Research Record: Journal of the Transportation R

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“…Vehicular technologies and driver interactions are expected to evolve more in the next few decades than they have evolved in the past due to ongoing technological enhancements and research in the automobile industry [ 4 , 5 ]. Many researchers in the past have focused on identifying factors influencing single and multivehicle fatal crashes [ [6] , [7] , [8] , [9] ]. The identified risk-causing factors related to on-road and off-road characteristics in the existing literature are the dimension of the median [ 6 ], day of the week [ 7 ], side traffic barriers [ 8 ], speed limit [ 9 ], road infrastructure [ 9 ], highway class [ 10 ], road alignment [ 7 ], socio-demographic characteristics near the crash location [ 11 ], traffic control [ 7 ], and adverse weather conditions [ 12 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Many researchers in the past have focused on identifying factors influencing single and multivehicle fatal crashes [ [6] , [7] , [8] , [9] ]. The identified risk-causing factors related to on-road and off-road characteristics in the existing literature are the dimension of the median [ 6 ], day of the week [ 7 ], side traffic barriers [ 8 ], speed limit [ 9 ], road infrastructure [ 9 ], highway class [ 10 ], road alignment [ 7 ], socio-demographic characteristics near the crash location [ 11 ], traffic control [ 7 ], and adverse weather conditions [ 12 ]. Besides, some researchers also evaluated the effect of red-light cameras [ 13 ], road surface [ 14 ], intersection type [ 15 ], and annual average daily traffic (AADT) [ 15 , 16 ] on crashes at intersections.…”

Section: Literature Reviewmentioning

confidence: 99%

Fatal crashes involving vehicles with driver warning systems: Identifying risk factors using a correlated random parameters ordered logit modeling approach

Gajera,

Pulugurtha

2024

Heliyon

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“…However, the Poisson regression method does not account for overdispersion or variation to the mean ( 11 ). Therefore, the univariate negative binomial regression (NB) models were then employed to estimate crash frequency to solve that issue ( 12 – 15 ). The Poisson-lognormal (PLN) regression is an alternative method to the NB method that researchers utilized because of its elasticity compared with the NB ( 16 , 17 ).…”

mentioning

confidence: 99%

Multivariate Poisson-Lognormal Models for Predicting Peak-Period Crash Frequency of Joint On-Ramp and Merge Segments on Freeways

Faden

Abdel-Aty

Mahmoud

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Because of a growing crash occurrence in conflict areas, the ramp and merge segments on freeways are a concern for transportation researchers and practitioners. Therefore, short-term safety-performance functions (SPFs) have been proposed to predict crash frequency at a.m. and p.m. peak-period aggregation levels using microscopic traffic-detector data. The proposed short-term crash prediction models could achieve more accuracy and flexibility, give a better understanding of how safety evaluations change over time, and enable the taking of appropriate actions. This study contributes to the literature by using the multivariate Poisson-lognormal (MVPLN) method via an integrated nested Laplace approximation (INLA) approach to investigate the dependency and the correlation between two responses (on-ramp- and merge-related crash frequencies). Models are developed for total crashes (KABCO) and fatal and severe injury crashes (KAB), utilizing 70% of a total 239 and 238 for joint on-ramp and merge segments at a.m. and p.m. peaks, respectively, from three states of a freeway (i.e., Florida, Virginia, and Wisconsin). The traffic and specific geometric data (e.g., the number of lanes, ramp configurations, presence of weaving segment, and interchange connector type) for ramp and merge segments were used as independent variables. The significant variables were found to be the exposure parameters and various geometric feature variables for ramp and merge segments. Results of posterior means for the correlation coefficients between the ramp and merge crash frequencies indicate that a significant correlation exists between the two locations.

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Effect of increasing the freeway posted speed limit on entry ramp speed-change lane crash frequency

Cited by 7 publications

References 36 publications

Segment-Level Spatial Spillover Effects of Exogenous Characteristics of Arterials on Crash Frequency

Segment-Level Spatial Spillover Effects of Exogenous Characteristics of Arterials on Crash Frequency

Fatal crashes involving vehicles with driver warning systems: Identifying risk factors using a correlated random parameters ordered logit modeling approach

Multivariate Poisson-Lognormal Models for Predicting Peak-Period Crash Frequency of Joint On-Ramp and Merge Segments on Freeways

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