A performance evaluation of an efficient traffic congestion detection protocol (ECODE) for intelligent transportation systems

2015 ◽  
Vol 24 ◽  
pp. 317-336 ◽  
Author(s):  
Maram Bani Younes ◽  
Azzedine Boukerche
Keyword(s):  
Performance Evaluation ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Congestion Detection ◽  
A Performance

scholarly journals SCENARIO MODEL TO REDUCE TRAFFIC CONGESTION USING INTELLIGENT TRANSPORTATION SYSTEMS

2020 ◽  
Vol 6 (2) ◽  
pp. 54-73
Author(s):  
Erma Suryani ◽  
◽  
Rully Agus Hendrawan ◽  
Fizar Syafa’at ◽  
Alifia Az-Zahra ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Scenario Model

INTELLIGENT TRANSPORTATION SYSTEMS IN IMPROVING TRAFFIC FLOW IN TOURISM DESTINATIONS∗

2007 ◽  
Vol 13 (3) ◽  
pp. 627-636
Author(s):  
Edna Mrnjavac ◽  
Robert Marsanić
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Emergency Services ◽  
Road Traffic ◽  
Weather Conditions ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transportation Infrastructure ◽  
Public Traffic ◽  
Tourism Destinations

The rapid growth and development of motorisation combined with relatively small investments made to improving transportation infrastructure in cities, as well as in tourism destinations, has led to serious problems in the unobstructed movement of vehicles in public traffic areas. Traffic congestion on roadways, in ferryboat ports and at state borders during the summer months and year-round lines of cars going to or returning from work are a regular presence in traffic in most urban and tourism destinations in Croatia, as well as in the rest of Europe. Intelligent transportation systems (ITS) can be implemented in urban and tourism centres, which, for example, have no opportunity for increasing the capacity of their traffic networks by constructing new, or expanding existing, transportation infrastructure, and no opportunity for increasing parking capacities. The only solution would be to optimise traffic networking by introducing intelligent technologies. Intelligent transportation systems and services represent a coupling of information and telecommunication technologies with transportation means and infrastructure to ensure greater efficiency in the mobility of people and goods. ITS implementation helps to provide better information to motorists and travellers (tourists); improve traffic and tourist flows, cargo transportation, public passenger-transportation; facilitate the work of emergency services; enable electronic traffic-related payments; enhance the security of people in road traffic; and monitor weather conditions and the environment. To motorists the system provides guidance to roads on which traffic is less intense, guidance to available parking spaces, and guidance, for example, to a good restaurant or interesting tourist attraction. his paper focuses, in particular, on ITS application in city and tourism destinations in connection with parking problems. Guiding vehicles to the closest vacant parking space helps to reduce traffic congestion, reduce the amount of time lost in searching and increase the occupancy rate of car-parks

Analysis of the Influence of Traffic Information Messages on Route Selection

1995 ◽  
Vol 39 (17) ◽  
pp. 1082-1086
Author(s):  
W. Bradley Fain
Keyword(s):  
Situation Awareness ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Information ◽  
Route Selection ◽  
Variable Message Signs ◽  
Message Format ◽  
Message Signs

Intelligent Transportation Systems (ITS) can reduce traffic congestion by displaying congestion-related delay information on roadside variable message signs or in-vehicle displays. Message format and content may have a significant impact on the percentage of drivers who decide to make a route diversion. In this study, the effect of various traffic information message types on driver routing decisions was evaluated. Results suggest that messages including both an advisory and a descriptive component promote situation awareness and rapid decision making, both of which are critical for this application.

scholarly journals Smart Route: Internet-of-Vehicles (IoV)-Based Congestion Detection and Avoidance (IoV-Based CDA) Using Rerouting Planning

2020 ◽  
Vol 10 (13) ◽  
pp. 4541 ◽  
Author(s):  
Zahid Khan ◽  
Anis Koubaa ◽  
Haleem Farman
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Performance Metrics ◽  
Complex Structure ◽  
Transportation Systems ◽  
Congestion Avoidance ◽  
Internet Of Vehicles ◽  
Area Of Interest ◽  
Congestion Detection

Massive traffic jam is the top concern of multiple disciplines (Civil Engineering, Intelligent Transportation Systems (ITS), and Government Policy) presently. Although literature constitutes several IoT-based congestion detection schemes, the existing schemes are costly (money and time) and, as well as challenging to deploy due to its complex structure. In the same context, this paper proposes a smart route Internet-of-Vehicles (IoV)-based congestion detection and avoidance (IoV-based CDA) scheme for a particular area of interest (AOI), i.e., road intersection point. The proposed scheme has two broad parts: (1) IoV-based congestion detection (IoV-based CD); and (2) IoV-based congestion avoidance (IoV-based CA). In the given area of interest, the congestion detection phase sets a parametric approach to calculate the capacity of each entry point for real-time traffic congestion detection. On each road segment, the installed roadside unit (RSU) assesses the traffic status concerning two factors: (a) occupancy rate and (b) occupancy time. If the values of these factors (either a or b) exceed the threshold limits, then congestion will be detected in real time. Next, IoV-based congestion avoidance triggers rerouting using modified Evolving Graph (EG)-Dijkstra, if the number of arriving vehicles or the occupancy time of an individual vehicle exceeds the thresholds. Moreover, the rerouting scheme in IoV-based congestion avoidance also considers the capacity of the alternate routes to avoid the possibility of moving congestion from one place to another. From the experimental results, we determine that proposed IoV-based congestion detection and avoidance significantly improves (i.e., 80%) the performance metrics (i.e., path cost, travel time, travelling speed) in low segment size scenarios than the previous microscopic congestion detection protocol (MCDP). Although in the case of simulation time, the performance increase depends on traffic congestion status (low, medium, high, massive), the performance increase varies from 0 to 100%.

scholarly journals Building the Traffic Flow Network with Taxi GPS Trajectories and Its Application to Identify Urban Congestion Areas for Traffic Planning

2020 ◽  
Vol 13 (1) ◽  
pp. 266
Author(s):  
Jiayu Qin ◽  
Gang Mei ◽  
Lei Xiao
Keyword(s):  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Planning ◽  
Flow Network ◽  
Gps Trajectories ◽  
Congestion Problems

Traffic congestion is becoming a critical problem in urban traffic planning. Intelligent transportation systems can help expand the capacity of urban roads to alleviate traffic congestion. As a key concept in intelligent transportation systems, urban traffic networks, especially dynamic traffic networks, can serve as potential solutions for traffic congestion, based on the complex network theory. In this paper, we build a traffic flow network model to investigate traffic congestion problems through taxi GPS trajectories. Moreover, to verify the effectiveness of the traffic flow network, an actual case of identifying the congestion areas is considered. The results indicate that the traffic flow network is reliable. Finally, several key problems related to traffic flow networks are discussed. The proposed traffic flow network can provide a methodological reference for traffic planning, especially to solve traffic congestion problems.

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