• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.125-133
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• 1999

Nonrecurring congestions are generally caused by random or less predictable events, such as accidents, spilled loads stalled or broken-down vehicles that, temporarily reduce the capacity of the freeway. The purpose of this paper is to present the effect of incidents on the traffic congestion on the urban freeway by simulation method. The simulation scenario is composed of two level traffic conditions, two level incident severities, and eight level incident durations. After incident, the recovering duration to the normal traffic flow, increased by linear of incident duration. Total vehicles travel time increased and average travel speed decreased by squares curve of incident duration. Considering incident impacts, incident management system is evaluated the major function of the urban freeway traffic management system. Also, necessary the related research to detect, verify, and develop effective response strategies for traffic incidents.

• Journal of Korean Society of Transportation
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• v.15 no.4
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• pp.143-163
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• 1997

Incident management is significant far the traffic management systems. The management of incidents determines the smoothness of freeway operations. The dynamic nature of incidents and the uncertainty associated with them require solutions based on the incident operator's judgment. Fuzz systems attempt to adapt such human expertise and are designed to replicate the decision making capability of on operator. Fuzzy systems process complex traffic information, and transmit it in a simplified, understandable form to human traffic operators. In this study, fuzzy rules were developed based on data from real incidents on Santa Monica Freeway in LosAngeles. The fuzzy rules ail linguistic based, and hence, user-friendly. A comparison of the results from the linguistic model with the real incident durations indicate that the outputs from the model reliably correspond to real incident durations conditions. The model reliably predicts the freeway incident duration. The modes can thus be used as an effective management tool for freeway incident response systems. The approach could be applied to other problems regarding dispatch systems in transportation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.61-66
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• 2013

The central core of the Traffic Management System is an Incident Management System. Whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Algeria freeway system. After review and analysis of existing incident detection methodologies, Paramics was utilized to test the performance of APID, DELOS algorithms. The existing system of Algeria freeway was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The Paramics simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.119-129
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• 2016

PURPOSES : The purpose of this study is to develop a methodology for estimating additional carbon emissions due to freeway incidents. METHODS : As our country grows, our highway policy has mainly neglected the environmental and social sectors. However, with the formation of a national green growth keynote and an increase in the number of people interested in environmental and social issues, problems related to social issues, such as traffic accidents and congestion, and environmental issues, such as the impact of air pollution caused by exhaust gases that are emitted from highway vehicles, are beginning to be discussed. Accordingly, studies have been conducted on a variety of environmental aspects in the field of road transport, and for the quantitative calculation of greenhouse gas emissions, using various methods. However, in order to observe the effects of carbon emissions, microscopic simulations must use many difficult variables such as cost, analysis time, and ease of analysis process. In this study, additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service), and the annual additional emissions based on incidents were calculated. According to the results, congestion length and emissions tend to increase with an increase in incident clearance time, number of occupied lanes, and worsening level of service. Using this data, we analyzed accident data on the Gyeong-bu Expressway (Yang-Jae IC - Osan IC) for a year. RESULTS : Additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service) and annual additional emissions caused by accidents were calculated. CONCLUSIONS : In this study, a methodology for estimating carbon emissions due to freeway incidents was developed that incorporates macroscopic flow models. The results of the study are organized in the form of a look-Up table that calculates carbon emissions rather easily.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.497-507
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• 2015

Nonrecurrent congestion of freeway was primarily caused by incident. The main cause of incident was known as a traffic accident. Therefore, accurate prediction of traffic incident clearance time is very important in accident management. Traffic accident data on freeway during year 2008 to year 2014 period were analyzed for this study. KNN(K-Nearest Neighbor) algorithm was hired for developing incident clearance time prediction model with the historical traffic accident data. Analysis result of accident data explains the level of accident significantly affect on the incident clearance time. For this reason, incident clearance time was categorized by accident level. Data were sorted by classification of traffic volume, number of lanes and time periods to consider traffic conditions and roadway geometry. Factors affecting incident clearance time were analyzed from the extracted data for identifying similar types of accident. Lastly, weight of detail factors was calculated in order to measure distance metric. Weight was calculated with applying standard method of normal distribution, then incident clearance time was predicted. Prediction result of model showed a lower prediction error(MAPE) than models of previous studies. The improve model developed in this study is expected to contribute to the efficient highway operation management when incident occurs.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.7-17
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• 2001

The purpose of this paper is to develop automatic incident detection algorithm using image based detector in freeway management system. This algorithm was developed by using neutral network for high speed roadway and by using speed and occupancy variable for low speed roadway. The image detector system with the developed automatic incident detection algorithm can detect multi-lane as well as several detect areas for each lane. To evaluate this system, field tests to measure the detecting rate of incidents were performed with other systems which have APID and DES algorithm at high speed roadway(freeway) and low speed roadway(national arterial). As the results of field test, it found that the detect rate of this system was highest rate comparing to other two systems.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.1-9
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• 2010

Predictive information on the freeway incident impacts can be a critical criterion in selecting travel options for users and in operating transportation system for operators. Provided properly, users can select time-effective route and operators can effectively run the system efficiently. In this study, a model is proposed to predict freeway incident impacts. The predictive model for incident impacts is based on short-term prediction. The proposed models are examined using MARE. The analysis results suggest that the models are accurate enough to be deployed in a real-world. The development of microscopic models to predict incident effects is expected to help minimize traffic delay and mitigate related social costs.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.429-434
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• 1999

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.61-72
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• 2005

This paper is designed to report the results of response manual development in relation to the freeway Incident Management System(FIMS) development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first task taken during the process was the selection of the required actions for each step within the Incident Management System. After through review and analysis of existing incident response procedures and manuals, the incident response manual led to the utilization of different technologies and actions in relation to the specific needs and character of the incidents. FIMS also provides Integrated Incident Management according to the verified incident information provided by the each components The deployment of containment and mitigation strategies for incidents will be automatic or manual depending on the configuration of the system. It is anticipated that, over a period of time, operators will be able to response the incident using integrated and organized Procedures and action items.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.280-285
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• 2003