Effects of reduced threshold of automated speed enforcement on speed and safety

Luoma, Juha; Rajamäki, Riikka; Malmivuo, Mikko

doi:10.1016/j.trf.2012.01.002

Cited by 15 publications

(3 citation statements)

References 2 publications

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“…The idea is to focus on major speeding offenses (e.g., 15 km/h over the limit) that can be assumed to be more important for safety than minor infractions. Because it is difficult to cite drivers who are operating a vehicle within a couple of kilometers per hour of the limit, most public agencies adopt an enforcement threshold, either officially or unofficially ( 44 ). The independent variables include factors such as area type (rural or urban), speed limit, number of lanes, lane width, median type, shoulder availability, service road availability, on-street parking availability, junction spacing, horizontal curve, right of way, adjacent buildings, and access points.…”

Section: Methodsmentioning

confidence: 99%

Identifying Optimal Locations for Speed Enforcement Cameras

Mohammad

Eleimat²

2022

Transportation Research Record: Journal of the Transportation R

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Speed enforcement cameras are used to improve traffic safety. These cameras are usually placed in areas with significant crashes related to speeding. However, in many countries, detailed crash data are not available or are of poor quality. This study aims to propose and explore three simple ranking methods for identifying optimal locations for speed enforcement cameras that do not depend on crash records. The first method is based on the Star Rating Scores and the traffic volume data. The second method relies on developing a data-driven model for predicting speeding violation rate (VR) based on road geometry aspects and comparing it with available road segment crash risk. The third method uses a combination of the first two methods. The proposed methods and prediction models were applied to a case study and successfully identified the optimal location for speed enforcement cameras. The developed prediction models suggest that speed limit, junction spacing, and the number of access points per kilometer are the most common variables to estimate speed VRs for both urban and rural roads. Availability of service roads and the number of lanes were variables that affect the speed VR on urban roads only. The proposed methods are considered valuable simple tools for road safety practitioners to effectively prepare speed enforcement plans for different road networks.

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Section: Methodsmentioning

confidence: 99%

Identifying Optimal Locations for Speed Enforcement Cameras

Mohammad

Eleimat²

2022

Transportation Research Record: Journal of the Transportation R

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“…The safety effects of automated mobile enforcement on both collisions and speed have been validated by several studies (10,(14)(15)(16)(17). However, most of the studies adopted an interrupted time series analysis to evaluate the systemwide effect.…”

mentioning

confidence: 95%

Before-and-After Empirical Bayes Evaluation of Automated Mobile Speed Enforcement on Urban Arterial Roads

El-Basyouny

Kim

2015

Transportation Research Record: Journal of the Transportation R

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Speeding is a leading factor in road collisions and is found to contribute to approximately one-third of all fatal collisions. Speed enforcement is one of the most common countermeasures used to reduce speed. However, a gap exists in the literature regarding the effectiveness of automated mobile photo enforcement on urban arterial roads. This study addresses this gap using the before-and-after empirical Bayes method to account for regression to the mean effects and other confounding factors. Locally developed safety performance functions and yearly calibration factors for different collision severities were obtained by using a reference group of urban arterial roads. The evaluation period covers 8 years. Collision records, deployment information, traffic counts, and road geometric data were collected. The results showed consistent reductions in different collision severities; the reductions ranged from 14% to 20%, with the highest reductions observed for severe collisions. The enforced segments were further categorized according to site selection criteria and deployment hours to examine the effect of enforcement on collision reduction. More reductions were found at segments that had more collisions during the before period and longer deployment hours. The study also compared the safety effects of continuous and discontinuous enforcement strategies on different arterials, and the analysis revealed that continuous enforcement achieved more reductions across all severities and types of collisions. The study also investigated the spillover effects on adjacent unenforced approaches. Significant reductions were found, and these results are discussed with regard to the general and specific deterrence of the enforcement.

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“…Mobile automated enforcement has been used to improve safety (5)(6)(7)(8)(9)(10)(11)(12)(13) and previous work provides strong evidence supporting the impact that these enforcement programs have on improving safety on a national or a municipal level. However, at such a high level of analysis, changes in traffic volume, overall collision trends, and other confounding factors are not usually captured and can negatively affect the quality of the results (14).…”

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confidence: 99%

Use of Objective Safety Evidence to Deploy Automated Enforcement Resources

Ibrahim¹,

Sayed

2019

Transportation Research Record: Journal of the Transportation R

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Automated enforcement programs have been an important tool for improving traffic safety. Previous work provides strong evidence supporting the impact that these programs have on increasing safety either on a micro-level (e.g., road segments), or at a macro-level (e.g., neighborhood, city). In both cases, there are many variables that can influence and affect the safety impacts of the enforcement program. Additionally, there is a lack of understanding of how specific deployment parameters (e.g., how often to visit an enforcement site) can influence the overall safety on a macro-level (e.g., traffic analysis zone). The objective of this study is to quantify the impact that automated enforcement has on collisions on a macro-level as well as to develop models that would provide enforcement authorities with an empirical tool to help plan their deployment strategy. The results show that an increase in the number of tickets issued for exceeding the speed limit resulted in a decrease in collisions, for all collision severities. Moreover, the results also showed that collision reductions were also associated with spending a longer time enforcing a site for each visit. Quantifying these safety impacts supports decision makers by providing them with an opportunity to analyze the safety benefits in relation to their deployment strategy to maximize the efficiency of their resources.

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Effects of reduced threshold of automated speed enforcement on speed and safety

Cited by 15 publications

References 2 publications

Identifying Optimal Locations for Speed Enforcement Cameras

Identifying Optimal Locations for Speed Enforcement Cameras

Before-and-After Empirical Bayes Evaluation of Automated Mobile Speed Enforcement on Urban Arterial Roads

Use of Objective Safety Evidence to Deploy Automated Enforcement Resources

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