Operational impacts of incident quick clearance legislation: a simulation analysis

Fries, Ryan; Hamlin, Carol; Chowdhury, Mashrur; Ma, Yun; Özbay, Kaan

doi:10.1002/atr.135

Cited by 9 publications

(2 citation statements)

References 8 publications

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“…Salum et al [2] developed a quantile regression model and showed that Florida Road Rangers response resulted in shorter incident clearance duration. Fries et al [27] used PARAMICS as a traffic simulation tool to ultimately estimate the financial impact of quick-clearance legislation and compared it with other incident management strategies, such as FSP program, traffic cameras, and sensors. Simulation modeling is used not only for evaluating the benefit-cost ratio of FSP program, but also for assessing the performance and overall operational impact of FSP programs.…”

Section: Review Of Previous Studiesmentioning

confidence: 99%

Evaluating the Impact of Freeway Service Patrol on Incident Clearance Times: A Spatial Transferability Test

Islam

Adanu

Hainen

et al. 2022

Journal of Advanced Transportation

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Freeway service patrol (FSPs) programs have been considered as an effective tool for traffic incident management in minimizing the adverse effects of traffic incidents. In this study, random parameters hazard-based duration modeling method was used to evaluate the impact of the newly implemented Alabama Service and Assistance Patrol (ASAP) program, using incident clearance time as a performance measure. It was determined that there is a statistically significant difference in the factors that influence incidents clearance times between incidents that occurred inside and outside the ASAP regions. A total of five variables (on-road, nighttime, peak hours, rain, and fire response present) were observed to have random effects along with ten fixed effects variables on incidents occurring inside the ASAP regions. On the other hand, incidents that occurred outside the ASAP regions were found to have three random effects variables (on-road, nighttime, and fire response present) and seven fixed effects variables. The estimation results indicate a significant association of incident clearance times to incident related variables such as involvement of CMVs, fatality, vehicle towing, seat belt indicated as involved, and on-road incidents that occurred both inside and outside the ASAP regions. The results also reveal that incident clearance times are influenced strongly by temporal variables (e.g., nighttime), traffic factors (e.g., AADT), and operational variables (e.g., fire response present) for incidents both inside and outside the ASAP area models. Overall, it was observed that the incident clearance times recorded in the regions where the ASAP program is in effect are significantly different. The findings of this study are expected to be useful for the state traffic incident management (TIM) agencies in developing and executing strategies to minimize incident clearance times. Ultimately, the study provides a data-driven evidence-based assessment of the ASAP program in the state.

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Section: Review Of Previous Studiesmentioning

confidence: 99%

Evaluating the Impact of Freeway Service Patrol on Incident Clearance Times: A Spatial Transferability Test

Islam

Adanu

Hainen

et al. 2022

Journal of Advanced Transportation

View full text Add to dashboard Cite

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“…Traffic incidents not only lead to traffic delay but also cause heavy life and economic loss. People have to draw more attention to reduce the traffic incidents . To accomplish this goal, the first and most important thing is to detect the incident accurately.…”

Section: Introductionmentioning

confidence: 99%

More robust and better: a multiple kernel support vector machine ensemble approach for traffic incident detection

Xiao

Gao

Kong

et al. 2013

J of Advced Transportation

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This paper presents a multiple kernel support vector machine (MKL-SVM) ensemble algorithm to detect traffic incidents. It uses resampling technology to generate training set, test set, and training subset firstly; then uses different training subsets to train individual MKL-SVM classifiers; and finally introduces ensemble methods to construct MKL-SVM ensemble to detect traffic incidents. Extensive experiments have been performed to evaluate the performances of the four algorithms: standard SVM, SVM ensemble, MKL-SVM, and the proposed algorithm (MKL-SVM ensemble). The experimental results show that the proposed algorithm has the best comprehensive performances in traffic incidents detection. To achieve better performances, the proposed algorithm needs less individual classifiers to construct the ensemble than SVM ensemble algorithm. Thus, compared with SVM ensemble algorithm, the complexity of the ensemble classifier of the proposed algorithm is reduced greatly. Conveniently, the proposed algorithm also avoids the burden of selecting the appropriate kernel function and parameters.(DR), false alarm rate (FAR), and detection time. Some techniques based on video processing have been adopted to detect traffic incidents. Trivedi et al. described a novel architecture for developing distributed video networks for incident detection and management [29]. Mak and Fan made a study on the detection of lane-blocking incidents on the basis of the traffic data provided by video-based detectors installed along Singapore's Central Expressway [15]. It is a meaningful attempt to use the video processing techniques to detect traffic incidents, but it is sensitive to the outdoor environmental factors, namely static shadows, snow, rain, and glare. Shehata et al. present a literature review of outdoor environment detection. Once the environmental conditions are detected, they can be compensated for, and hence, the accuracy of alarms detected by video-based AID systems will be enhanced [27]. But this compensation is not able to completely eliminate the impact produced by the outdoor environment.The inductive loop detector (ILD) is the most commonly used sensor in traffic surveillance and management applications, which can collect the traffic data stably and does not suffer the outdoor environment impact. There are a lot of advanced algorithms that focus on detecting traffic incidents using ILD data and have achieved good results. These advanced algorithms divide the traffic patterns into two groups-incident traffic pattern and incident-free traffic pattern-then, the traffic incident detection problem will be transformed into a binary classification problem based on ILD data. Qi et al. adopt the cumulative sum of log-likelihood ratio (CUSUM) algorithm to detect freeway incidents by integrating traffic measurements from two contiguous loop detectors and the non-stationarity of traffic flows [23]. In [8,1,25,26], Neural networks are proposed to detect traffic incidents. The conclusion of their papers is that artificial neural networks have ...

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Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

Sun

Wang

2018

Physica A: Statistical Mechanics and its Applications

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Operational impacts of incident quick clearance legislation: a simulation analysis

Cited by 9 publications

References 8 publications

Evaluating the Impact of Freeway Service Patrol on Incident Clearance Times: A Spatial Transferability Test

Evaluating the Impact of Freeway Service Patrol on Incident Clearance Times: A Spatial Transferability Test

More robust and better: a multiple kernel support vector machine ensemble approach for traffic incident detection

Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

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