scholarly journals Implementation of Telematics Solutions in Urban Agglomerations in the Aspect of Road Incidents

2019 ◽  
Vol 10 (4) ◽  
pp. 1
Author(s):  
Ibrahiem M. M. El Emary ◽  
Anna Brzozowska ◽  
Bubel Dagmara
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
Transport Systems ◽  
Incident Management ◽  
Vehicle Speed ◽  
Road Infrastructure ◽  
Traffic Incident ◽  
Traffic Incident Management ◽  
Management Algorithms

Urban mobility is a public service provided by a road traffic management entity. The customer receives access to the road infrastructure and a service of travelling in a city by a transport means of their choice. In the case of road traffic incident management, this issue is becoming increasingly important, as every traffic management entity should deliver a product that meets road users' requirements and expectations. A characteristic element of road traffic management is incidents generated by road infrastructure users that occur at each stage of traffic management. The paper presents the results of research carried out in the aspect of use of appropriate algorithms of traffic incident management on selected national roads, supported by research and scientific discourse on aspects related to telematics systems, with particular emphasis on Intelligent Transport Systems, in order to verify the effectiveness of the implementation of telematics solutions. The issues mentioned above are extremely important in view of the need to acknowledge the expected critical infrastructure. Principles and recommendations used in the selection and implementation of ITS applications become an important element in this respect. The research was used to verify the effectiveness of event management algorithms in road traffic, with different traffic volume and meteorological conditions. Empirical findings used in research allow for the analysis of changes in traffic parameters, such as vehicle speed, traffic volume and detector occupancy, on selected national roads, at specific intervals. This has made it possible to determine the prospects for the development of traffic incident management algorithms, which constitute a set of artificial intelligence methods.

Highway Traffic Incident Detection and Optimal Sensor Placement Layout

2013 ◽  
Vol 650 ◽  
pp. 460-464 ◽  
Author(s):  
Lan Bai ◽  
Qi Sheng Wu ◽  
Mei Yang ◽  
Lan Xin Wei ◽  
Bo Li ◽  
...  
Keyword(s):  
Road Traffic ◽  
Detection Algorithm ◽  
Simulation Software ◽  
Incident Management ◽  
Incident Detection ◽  
Highway Traffic ◽  
Traffic Incidents ◽  
Traffic Incident ◽  
Before And After ◽  
Traffic Incident Management

Traffic incident detection is critical to the core of the traffic incident management process. In order to study the highway traffic incident detection algorithm and the layout spacing of the fixed detector, under the assumptions of the linear traffic flow, to detect traffic incidents as the goal, using TransModeler traffic simulation software to simulate the highway traffic conditions from Xian to Hanzhong, getting the changes in the macroscopic traffic parameters before and after the traffic incident, and analysis of the data, finally puts forward the optimal layout of spacing of basic road traffic incident detection.

Collection, Analysis, and Reporting of Kentucky Traffic Incident Management Performance

2021 ◽  
pp. 036119812110010
Author(s):  
Xu Zhang ◽  
Reginald R. Souleyrette ◽  
Eric Green ◽  
Teng Wang ◽  
Mei Chen ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Management Strategies ◽  
Incident Management ◽  
Vehicle Crashes ◽  
Clearance Time ◽  
Emergency Responders ◽  
Traffic Incident ◽  
Choropleth Maps ◽  
Traffic Incident Management ◽  
Secondary Crashes

Traffic incidents remain all too common. They negatively affect the safety of the traveling public and emergency responders and cause significant traffic delays. Congestion associated with incidents can instigate secondary crashes, exacerbating safety risks and economic costs. Traffic incident management (TIM) provides an effective approach for managing highway incidents and reducing their occurrence and impacts. The paper discusses the establishment and methods of calculation for five TIM performance measures that are used by the Kentucky Transportation Cabinet (KYTC) to improve incident response. The measures are: roadway clearance time, incident clearance time, secondary crashes, first responder vehicle crashes, and commercial motor vehicle crashes. Ongoing tracking and analysis of these metrics aid the KYTC in its efforts to comprehensively evaluate its TIM program and make continuous improvements. As part of this effort, a fully interactive TIM dashboard was developed using the Microsoft Power BI platform. Dashboard users can apply various spatial and temporal filters to identify trends at the state, district, county, and agency level. The dashboard also supports dynamic visualizations such as time-series plots and choropleth maps. With the TIM dashboard in place, KYTC personnel, as well as staff at other transportation agencies, can identify the strengths and weaknesses of their incident management strategies and revise practices accordingly.

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

User Cost Analysis of UDOT’s Traffic Incident Management Program

2021 ◽  
Author(s):  
Mitchell G. Hadfield ◽  
Logan S. Bennett ◽  
Grant G. Schultz ◽  
Mitsuru Saito ◽  
Dennis L. Eggett
Keyword(s):  
Cost Analysis ◽  
Management Program ◽  
Incident Management ◽  
User Cost ◽  
Traffic Incident ◽  
Traffic Incident Management

Traffic Incident Duration Estimation Based on a Dual-Learning Bayesian Network Model

2018 ◽  
Vol 2672 (45) ◽  
pp. 196-209 ◽  
Author(s):  
Haozhe Cong ◽  
Cong Chen ◽  
Pei-Sung Lin ◽  
Guohui Zhang ◽  
John Milton ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Expert Knowledge ◽  
Transportation Systems ◽  
Practical Significance ◽  
Incident Management ◽  
Highway Traffic ◽  
Traffic Incidents ◽  
Traffic Incident ◽  
Incident Duration ◽  
Traffic Incident Management

Highway traffic incidents induce a significant loss of life, economy, and productivity through injuries and fatalities, extended travel time and delay, and excessive energy consumption and air pollution. Traffic emergency management during incident conditions is the core element of active traffic management, and it is of practical significance to accurately understand the duration time distribution for typical traffic incident types and the factors that influence incident duration. This study proposes a dual-learning Bayesian network (BN) model to estimate traffic incident duration and to examine the influence of heterogeneous factors on the length of duration based on expert knowledge of traffic incident management and highway incident data collected in Zhejiang Province, China. Fifteen variables related to three aspects of traffic incidents, including incident information, incident consequences, and rescue resources, were included in the analysis. The trained BN model achieves favorable performance in several areas, including classification accuracy, the receiver operating characteristic (ROC) curve, and the area under curve (AUC) value. A classification matrix, and significant variables and their heterogeneous influences are identified accordingly. The research findings from this study provide beneficial reference to the understanding of decision-making in traffic incident response and process, active traffic incident management, and intelligent transportation systems.

scholarly journals A New Approach of Smart Mobility for Heavy Goods Vehicles in Casablanca

2021 ◽  
Author(s):  
Mohammed Mouhcine Maaroufi ◽  
Laila Stour ◽  
Ali Agoumi
Keyword(s):  
Environmental Sustainability ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Research Work ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Smart Mobility ◽  
Heavy Goods Vehicles

Managing mobility, both of people and goods, in cities is a thorny issue. The travel needs of urban populations are increasing and put pressure on transport infrastructure. The Moroccan cities are no exception and will struggle, in the short term, to respond to the challenges of the acceleration of the phenomenon of urbanization and the increase in demand for mobility. This will inevitably prevent them from turning into smart cities. The term smart certainly alludes to better use of technologies, but smart mobility is also defined as “a set of coordinated actions intended to improve the efficiency, effectiveness and environmental sustainability of cities” [1]. The term mobility highlights the preponderance of humans over infrastructure and vehicles. Faced with traffic congestion, the solutions currently adopted which consist of fitting out and widening the infrastructures, only encourage more trips and report the problem with more critical consequences. It is true that beyond a certain density of traffic, even Intelligent Transport Systems (ITS) are not useful. The concept of dynamic lane management or Advanced Traffic Management (ATM) opens up new perspectives. Its objective is to manage and optimize road traffic in a variable manner, in space and in time. This article is a summary of the development of a road infrastructure dedicated to Heavy Goods Vehicles (HGV), the first of its kind in Morocco. It aims to avoid the discomfort caused by trucks in the urban road network of the city of Casablanca. This research work is an opportunity to reflect on the introduction of ITS and ATM to ensure optimal use of existing infrastructure before embarking on heavy and irreversible infrastructure projects.

Improving Traffic Incident Management Using Team Cognitive Work Analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 152-173
Author(s):  
Vanessa Cattermole-Terzic ◽  
Tim Horberry
Keyword(s):  
Incident Management ◽  
Cognitive Work Analysis ◽  
Work Analysis ◽  
Traffic Incident ◽  
Cognitive Work ◽  
Study Team ◽  
Traffic Incident Management ◽  
To Come ◽  
And Performance ◽  
Senior Officers

Effective traffic incident management requires separate responder agencies, with different and sometimes competing priorities and purposes, to come together as a team. Their priorities include optimizing casualty outcomes, minimizing the disruption to the flow of traffic, and maintaining responder team safety. In this study, team Cognitive Work Analysis was used in a desktop exercise setting to analyze a complex traffic incident management exercise. The study investigated decisions made at the scene of an incident to determine system issues and system support solutions. Participants were all senior officers and decision makers in traffic incident management environments. Results indicated that team Cognitive Work Analysis was highly beneficial in determining gaps in team coordination, communication, and structures. Information regarding shared and not shared work elements between agencies highlighted novel coordination and education requirements within and between agencies, such as disparate priorities at the scene creating the risk of interoperability issues. Analyses of operational, coordination, and structural strategies offered new insights into the traffic incident management work domain and recommendations for improvements to the safety and performance of the overall traffic incident management system.

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