Extension and Application of Prosser-Dunne Model to Traffic Operation Analysis of Oversaturated, Closely Spaced Signalized Intersections

1998 ◽  
Vol 1646 (1) ◽  
pp. 106-114 ◽  
Author(s):  
Carroll J. Messer
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Experimental Testing ◽  
Signalized Intersections ◽  
Critical Surface ◽  
Operation Analysis ◽  
Pdx Model ◽  
Computer Simulation Program ◽  
Congestion Problems ◽  
Signalized Arterials

Traffic congestion continues to have a serious impact on the productivity of the nation’s transportation system. Signalized arterials and service interchanges in urban areas serve as critical surface street facilities. These facilities often experience serious congestion problems because of high traffic demands that exceed capacity and also because of their common, closely spaced intersections and ramp terminals. Moreover, service interchanges are usually part of a signalized cross arterial and also may have short spacings to adjacent signalized intersections. Major deficiencies exist in the analysis technology and software tools available for analyzing potential traffic congestion problems at signalized arterials and service interchanges having closely spaced ramp terminals. This paper presents extensions of work originally published by Prosser and Dunne in Australia for analyzing the operational impacts of queue spillback on the capacity and delay of closely spaced signalized intersections. Coding of the described algorithm into FORTRAN was conducted, followed by experimental testing of the model using a calibrated version of the microscopic computer simulation program TRAF-NETSIM. Satisfactory comparisons were obtained between the initial version of the newly developed Prosser-Dunne Extended (PDX) model and NETSIM, but more testing and enhancement of the PDX model are recommended before implementation in existing operational software packages is considered.

Simulation Studies of Traffic Operations at Oversaturated, Closely Spaced Signalized Intersections

1998 ◽  
Vol 1646 (1) ◽  
pp. 115-123 ◽  
Author(s):  
Carroll J. Messer
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Simulation Studies ◽  
Traffic Operations ◽  
Research Focus ◽  
Control Delay ◽  
Congestion Problems ◽  
Initial Research

Traffic congestion continues to have a serious impact on the productivity of the nation’s transportation system. Signalized service interchanges in urban areas serve as a critical connection between freeway and arterial surface street systems. These facilities often experience serious congestion problems because of high traffic demands exceeding capacity and because of their common, closely spaced ramp terminals. Moreover, service interchanges are usually a part of a signalized cross arterial and may also have short spacings to adjacent signalized intersections. Major deficiencies exist in the analysis technology and software tools available for analyzing traffic congestion problems at oversaturated signalized interchanges and closely spaced arterial systems. Results are provided of an investigation into the nature of oversaturated systems and also undersaturated systems that may become congested (oversaturated) because of poor signal timing and deficient spacing between the signalized intersections. Although the initial research focus was on signalized service interchanges based on calibrated NETSIM simulations, the research results are also applicable to closely spaced signalized urban arterials. The research shows that traffic congestion is complex, but it can be characterized and modeled. An upper bound on signal control delay is provided for oversaturated arterial operations.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

Determination of Optimal Public Transportation Routes Using Firefly and Tabu Search Algorithms

2020 ◽  
Vol 4 (5) ◽  
pp. 884-891
Author(s):  
Salwa Salsabila Mansur ◽  
Sri Widowati ◽  
Mahmud Imrona
Keyword(s):  
Tabu Search ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Search Algorithm ◽  
Urban Transportation ◽  
The Public ◽  
Comparison Results ◽  
Congestion Problems ◽  
Transportation Routes

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

scholarly journals META-HEURISTIC APPROACH FOR HIGH-DEMAND FACILITY LOCATIONS CONSIDERING TRAFFIC CONGESTION AND GREENHOUSE GAS EMISSION

2016 ◽  
Vol 24 (4) ◽  
pp. 233-244 ◽  
Author(s):  
Taesung HWANG ◽  
Minho LEE ◽  
Chungwon LEE ◽  
Seungmo KANG
Keyword(s):  
Greenhouse Gas ◽  
Facility Location ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Greenhouse Gas Emission ◽  
Memetic Algorithms ◽  
Distribution Centers ◽  
Ghg Emission ◽  
High Demand ◽  
Facility Locations

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas.

scholarly journals A framework for IoT-enabled environment aware traffic management

2021 ◽  
Vol 11 (1) ◽  
pp. 518
Author(s):  
Mohamed Fazil Mohamed Firdhous ◽  
B. H. Sudantha ◽  
Naseer Ali Hussien
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Fine Particles ◽  
Environment Pollution ◽  
Negative Effects ◽  
Traffic Condition ◽  
Pollution Levels ◽  
Transport Services ◽  
The Cost

Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.

scholarly journals Contribution to Improving the Quality of Traffic in Mobile Networks

2020 ◽  
pp. 21-28
Author(s):  
Onyonkiton Théophile Aballo ◽  
Roland Déguénonvo ◽  
Antoine Vianou
Keyword(s):  
Mobile Networks ◽  
Traffic Congestion ◽  
Loss Rate ◽  
Fourth Generation ◽  
Good Decision ◽  
Latency Jitter ◽  
Congestion Problems ◽  
Time Required ◽  
Effective Speed

Today, mobile networks are faced with congestion which results in regular slowness given the variation in the actual speed of the network, that is to say the time required to transmit all of the data from a point to another. In third and fourth generation mobile networks, actual throughput is not directly measurable, it actually consists of three separate indicators, latency, jitter and loss rate. Many studies have shown that these parameters have a particular influence on congestion problems. In practice, the effective speed on the network is inversely proportional to the latency. However, the bit rate is four times the latency. Next, jitter is the variation of latency over time, impacting the flow by influencing latency. In this article, we have examined the analysis of traffic congestion in third and fourth generation networks in order to make a comparative study of the congestion rate for good decision-making.

scholarly journals Analyzing the Issue of On-street Parking in Commercial Areas: A Case Study of the City of Hyderabad, Pakistan

2018 ◽  
Vol 01 (02) ◽  
pp. 01-09
Author(s):  
Baig Farrukh ◽  
Sahito Noman ◽  
Bano Arsla ◽  
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Survey Methodology ◽  
Greenhouse Gas Emission ◽  
Central Business District ◽  
Rapid Urbanization ◽  
Analysis Technique ◽  
Business District ◽  
Public Views ◽  
The City

In developing countries, rapid urbanization has created an enormous pressure on land use, infrastructure and transportation. The fast growing ratio of motorized vehicles in urban areas is the main cause of environmental degradation. Almost 80% of the greenhouse gas emission is from vehicles in cities. In the city centers, on-street parking is considered the major cause of traffic congestion. The aim of this study was to evaluate the problems of on-street parking and disorderly parking at Central Business District (CBD) of Hyderabad city. The field survey methodology was adopted to perceive the current traffic problems in the city center and traffic count survey was carried out in both peak and off hours. The data was analyzed using descriptive statistics frequency analysis technique with the help of Statistical Package for the Social Sciences (SPSS). The findings revealed that increasing number of vehicles, on-street parking, improper parking, encroachment, inadequate parking space and poor condition of roads are the main causes of traffic congestion. The study bridges up the research gap of determining public views about on-street parking challenges in the context of Hyderabad, Pakistan and provides statistical results which may equally be adapted by policy makers and transportation planners in order to improve the traffic situation.

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