Automatic incident detection in smart city using multiple traffic flow parameters via V2X communication

Iqbal, Zafar; Khan, Majid Iqbal

doi:10.1177/1550147718815845

Cited by 24 publications

(8 citation statements)

References 50 publications

(63 reference statements)

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“…To reduce vehicle-to-vehicle accidents, studies [42][43][44] have been conducted on the methods of sharing information between vehicles and surrounding traffic facilities, as well as between vehicles and a traffic integration center. Typical technologies include vehicle-to-everything communication (V2X) [45].…”

Section: Urban Problems Related To the Core Needs Of Smart Citiesmentioning

confidence: 99%

A Smart City Service Business Model: Focusing on Transportation Services

Kim

Yang

2021

Sustainability

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Most cities have adopted smart city services to solve urban problems. However, an examination of their operations reveals that many of these services have either been discontinued or have failed to advance further since they were not profitable. Therefore, this study reviews and proposes the business models of smart city services at a fundamental level. It defines and classifies the smart city service focusing on transportation and the components. The business model has been constructed for electric vehicles and autonomous shuttle businesses in terms of transportation services. It found that the model was profitable in each business only when various stakeholders were linked for mutual interests. Since various service stakeholders cooperate in smart city service, if one of them is unable to secure profitability, it is difficult to operate the smart city service fully. Therefore, a detailed review of the business model is required before providing a smart city service.

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Section: Urban Problems Related To the Core Needs Of Smart Citiesmentioning

confidence: 99%

A Smart City Service Business Model: Focusing on Transportation Services

Kim

Yang

2021

Sustainability

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“…In the space three-dimensional coordinate system, the location of the actual traffic accident is obtained by calculation. After determining the actual location of the traffic accident, a traffic network map with the accident location as the center and the distance between the accident location and the rescue team as the radius is established by using WEBGIS technology [15][16] . The system designed in this paper selects map services in ArcGIS Server to provide rescue Map Service.…”

Section: Emergency Traffic Disposal Using Webgis Technologymentioning

confidence: 99%

Research on Intelligent City Traffic Management System based on WEBGIS

You

Jin

Hong

et al. 2021

Preprint

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Aiming at the problem that the traditional urban traffic management system can't effectively integrate the data, which leads to the low efficiency of data processing and the effect of traffic management, a smart city traffic management system based on WEBGIS is designed. Based on the traditional system, the dynamic traffic data acquisition hardware module is designed. According to the weekly similarity characteristics of traffic flow data, the traffic flow in different time periods is predicted and the road signal is controlled. The WEBGIS technology is used to deal with the traffic accidents, and the effective management of the urban traffic is realized. Simulation results show that the designed management system can effectively reduce the congestion of urban trunk roads and improve the efficiency of traffic management.

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“…It comprises three major modules including incident detection, reporting, and clearance. e incident detection module includes the systems that evolved from nonautomatic incident detection systems via mobile telephone calls by eye-witnesses to automatic incident detection (AID) systems [14] that utilize parametric data gathered from on-road and in-vehicle sensing devices. e data are then analyzed using comparative, statistical, time-series, and ML algorithms to extract traffic patterns that are used to classify incidents [15].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Traffic Incident Detection and Classification Framework by Leveraging the Efficacy of Model Stacking

et al. 2021

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Automatic incident detection (AID) plays a vital role among all the safety-critical applications under the parasol of Intelligent Transportation Systems (ITSs) to provide timely information to passengers and other stakeholders (hospitals and rescue, police, and insurance departments) in smart cities. Moreover, accurate classification of these incidents with respect to type and severity assists the Traffic Incident Management Systems (TIMSs) and stakeholders in devising better plans for incident site management and avoiding secondary incidents. Most of the AID systems presented in the literature are incident type-specific, i.e., either they are designed for the detection of accident or congestion. While traveling along the road, one may come across different types of traffic incidents, such as accidents, congestion, and reckless driving. This necessitates that the AID system detects and classifies not only all the popular traffic incident types, but severity as well that is associated with these incidents. Therefore, this study aims to propose an efficient incident detection and classification (E-IDC) framework for smart cities, by incorporating the efficacy of model stacking, to classify the incidents with respect to their types and severity levels. The experimental results showed that the proposed E-IDC framework achieved performance gains of 5%–56% in terms of incident severity classification and 1%–14% in terms of incident type classification when applied with different classifiers. We have also applied the Wilcoxon test to benchmark the performance of our proposed framework that reflects the significance of our approach over existing individual incident predictors in terms of severity and type classification. Moreover, it has been observed that the proposed E-IDC framework outperforms the existing ensemble technique, such as XGBoost used for the classification of incidents.

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Automatic incident detection in smart city using multiple traffic flow parameters via V2X communication

Cited by 24 publications

References 50 publications

A Smart City Service Business Model: Focusing on Transportation Services

A Smart City Service Business Model: Focusing on Transportation Services

Research on Intelligent City Traffic Management System based on WEBGIS

An Efficient Traffic Incident Detection and Classification Framework by Leveraging the Efficacy of Model Stacking

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