scholarly journals Discrete Event Simulation of Driver's Routing Behavior Rule at a Road Intersection

2019 ◽  
Author(s):  
Ben Benzaman ◽  
Erfan Pakdamanian
Keyword(s):  
Traffic Congestion ◽  
Discrete Event ◽  
Wait Time ◽  
Arrival Rate ◽  
Dynamics Simulation ◽  
Route Selection ◽  
Traffic Light ◽  
Traffic Dynamics ◽  
Shortest Distance ◽  
Selection Factors

Several factors influence traffic congestion and overall traffic dynamics. Simulation modeling has been utilized to understand the traffic performance parameters during traffic congestions. This paper focuses on driver behavior of route selection by differentiating three distinguishable decisions, which are shortest distance routing, shortest time routing and less crowded road routing. This research generated 864 different scenarios to capture various traffic dynamics under collective driving behavior of route selection. Factors such as vehicle arrival rate, behaviors at system boundary and traffic light phasing were considered. The simulation results revealed that shortest time routing scenario offered the best solution considering all forms of interactions among the factors. Overall, this routing behavior reduces traffic wait time and total time (by 69.5% and 65.72%) compared to shortest distance routing.

Congestion Control by Reducing Wait time at the traffic junction using fuzzy logic controller

2020 ◽  
Vol 10 ◽  
Author(s):  
Manpreet Singh Bhatia ◽  
Alok Aggarwal
Keyword(s):  
Real Time ◽  
Traffic Congestion ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Detection System ◽  
Green Light ◽  
Wait Time ◽  
Arrival Rate ◽  
Traffic Signal ◽  
Traffic Light

Traffic congestion is one of the most severe problems especially in metro cities due to ever increasing number of vehicles on roads by 20% per year even with well-planned road management system and sufficient infra. Most of the existing traffic signal controllers use fixed cycle type, giving a constant green/red/yellow phase for each traffic signal cycle. These traditional controllers cannot adapt the dynamics of traffic at real time which a traffic man can do. Deploying traffic men at every traffic light junction is not feasible due to manpower shortage and cost considerations. In this work a three input fuzzy controller is proposed which can adapt the dynamics of real time traffic and reduce the congestion at the traffic light junction. Proposed fuzzy controller has three inputs namely; queue length, arrival rate and peak hours and one output parameter, time extension which is to be controlled by the use of the three input parameters. All four lanes have been allocated a fixed green signal time of 60 seconds at the start. Extension/decrease of the green light is done dynamically with ±28 seconds. Compared to conventional fixed cycle type, proposed approach gives a minimum improvement of 6% and a maximum of 47% depending on various traffic conditions at the junction. In terms of CO2 emission improvement of 20% and 42.12% and in terms of fuel consumption improvement of 34.73% and 57.18% has been observed compared to UCONDES (Urban CONgestion DEtection System) and OVMT (Original Vehicular Mobility Trace) respectively.

scholarly journals Multi-objective Optimization for a Complex Intersection Using Design of Experiments and Simulation

2020 ◽  
Vol 53 (6) ◽  
pp. 791-802
Author(s):  
Saeed Aramesh ◽  
Ali Ghorbanian
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Wait Time ◽  
Pollutant Emission ◽  
Regression Equations ◽  
Traffic Light ◽  
Traffic Lights ◽  
Optimal Period ◽  
The Mean ◽  
Full Factorial

Considering the importance of time in today's world and the rising traffic congestion in urban areas, using methods to reduce wait times and air pollution can have a significant impact on promoting urban management. Given the uncertainty in the number of vehicles and the emission rate of vehicles, a complex T intersection with three traffic lights was simulated in this study. Three objective functions were defined for the mean of wait time, average queue length, and aggregate pollutant emission of the vehicles in queue. First, regression equations for each of the variables were obtained by a full factorial design and analysis of variance, and the optimal period for each traffic light was then computed with a utility function approach. Finally, the results were compared to the results obtained from the optimization of each response variable OptQuest for Arena software.

scholarly journals Discrete-Event Simulation of Road Traffic Congestion to Support Green Supply Chain

2018 ◽  
Vol 7 (3.20) ◽  
pp. 377
Author(s):  
Muhammad Zulqarnain Hakim Abd Jalal ◽  
Wan Laailatul Hanim Mat Desa ◽  
Mohd Kamal Mohd Nawawi ◽  
Ruzelan Khalild
Keyword(s):  
Supply Chain ◽  
Discrete Event Simulation ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Current System ◽  
Discrete Event ◽  
Green Supply Chain ◽  
Traffic Light ◽  
Event Simulation ◽  
Road Traffic Congestion

This paper presents a discrete-event simulation (DES) study on road traffic intersections at one of the fastest developing towns in Kedah, Malaysia. Inefficient traffic light control (TLC) of the existing system contributes to the road traffic congestion (RTC) especially during peak hours, which leads to environment pollution. With the increasing awareness about environmental issues, businesses and governments increasingly want to reduce the pollution which leads to green supply chain. RTC can be caused by a temporary obstruction or a permanent capacity bottleneck in the network itself. A DES model was developed based on current system and then “what-if” scenario was analyzed to check whether improvement would be achieved. Results from the analysis show that average waiting time and number in queue could be reduced specifically at two of the lanes under study.   

A Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Rapid Development ◽  
Route Selection ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
A Value ◽  
Distance Data ◽  
Simple Additive Weighting ◽  
The City ◽  
Selection Of

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.

scholarly journals Formation of the Traffic Flow Rate under the Influence of Traffic Flow Concentration in Time at Controlled Intersections in Tyumen, Russian Federation

2021 ◽  
Vol 13 (15) ◽  
pp. 8324
Author(s):  
Viacheslav Morozov ◽  
Sergei Iarkov
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Traffic Congestion ◽  
Traffic Management ◽  
System Analysis ◽  
Motor Vehicle ◽  
Experimental Studies ◽  
Transport Systems ◽  
Experiment Planning ◽  
Traffic Light

Present experience shows that it is impossible to solve the problem of traffic congestion without intelligent transport systems. Traffic management in many cities uses the data of detectors installed at controlled intersections. Further, to assess the traffic situation, the data on the traffic flow rate and its concentration are compared. Latest scientific studies propose a transition from spatial to temporal concentration. Therefore, the purpose of this work is to establish the regularities of the influence of traffic flow concentration in time on traffic flow rate at controlled city intersections. The methodological basis of this study was a systemic approach. Theoretical and experimental studies were based on the existing provisions of system analysis, traffic flow theory, experiment planning, impulses, probabilities, and mathematical statistics. Experimental data were obtained and processed using modern equipment and software: Traficam video detectors, SPECTR traffic light controller, Traficam Data Tool, SPECTR 2.0, AutoCad 2017, and STATISTICA 10. In the course of this study, the authors analyzed the dynamics of changes in the level of motorization, the structure of the motor vehicle fleet, and the dynamics of changes in the number of controlled intersections. As a result of theoretical studies, a hypothesis was put forward that the investigated process is described by a two-factor quadratic multiplicative model. Experimental studies determined the parameters of the developed model depending on the directions of traffic flow, and confirmed its adequacy according to Fisher’s criterion with a probability of at least 0.9. The results obtained can be used to control traffic flows at controlled city intersections.

Towards a Multi Objective Path Optimisation for Car Navigation

2011 ◽  
Vol 65 (1) ◽  
pp. 125-144 ◽  
Author(s):  
Ching-Sheng Chiu ◽  
Chris Rizos
Keyword(s):  
Selection Criteria ◽  
Empirical Studies ◽  
Route Selection ◽  
Multi Objective ◽  
Optimal Paths ◽  
Proposed Model ◽  
Shortest Distance ◽  
Shortest Path Algorithms ◽  
Car Navigation System ◽  
Car Navigation

In a car navigation system the conventional information used to guide drivers in selecting their driving routes typically considers only one criterion, usually the Shortest Distance Path (SDP). However, drivers may apply multiple criteria to decide their driving routes. In this paper, possible route selection criteria together with a Multi Objective Path Optimisation (MOPO) model and algorithms for solving the MOPO problem are proposed. Three types of decision criteria were used to present the characteristics of the proposed model. They relate to the cumulative SDP, passed intersections (Least Node Path – LNP) and number of turns (Minimum Turn Path – MTP). A two-step technique which incorporates shortest path algorithms for solving the MOPO problem was tested. To demonstrate the advantage that the MOPO model provides drivers to assist in route selection, several empirical studies were conducted using two real road networks with different roadway types. With the aid of a Geographic Information System (GIS), drivers can easily and quickly obtain the optimal paths of the MOPO problem, despite the fact that these paths are highly complex and difficult to solve manually.

Smart Traffic Light System

2021 ◽  
Vol 9 (9) ◽  
pp. 679-686
Author(s):  
Rashi Maheshwari
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Monitoring ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Mathematical Functions ◽  
Light System ◽  
Smart Traffic ◽  
And Control

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

Medical readiness: evaluating the robustness of medical clinic staffing solutions

2016 ◽  
Vol 14 (4) ◽  
pp. 407-419
Author(s):  
Michael Q Corpuz ◽  
Christina F Rusnock ◽  
Vhance V Valencia ◽  
Kyle Oyama
Keyword(s):  
Negative Impact ◽  
Cost Benefit Analysis ◽  
Relative Effectiveness ◽  
Discrete Event ◽  
Cost Savings ◽  
Cost Benefit ◽  
Wait Time ◽  
Cost Effective ◽  
Wait Times ◽  
Staffing Mix

Medical readiness requires Department of Defense medical clinics to be robust to changes in patient demand. Minor fluctuations in patient demand occur on a regular basis, but major increases can also occur. Major demand increases can result from a number of occurrences, including mass military deployments, medical incidents, outbreaks, and overflow from Veterans’ Affairs clinics. This research evaluates a system of clinics at Wright-Patterson Air Force Base in order to determine its ability to handle a 200% surge in patient demand. In addition, this study evaluates the relative effectiveness of six different staffing mix options to minimize patient wait times, also under the surge demand conditions. This evaluation is conducted using discrete-event simulation to estimate patient wait times and includes a sensitivity analysis of the increased patient demand, as well as a cost–benefit analysis to determine the most cost-effective alternative scenario. The study finds that adjustments to staffing mix enable cost savings while meeting current demands. In addition, the study finds that adjusting the staffing mix will not have a negative impact on patient wait time in the surge conditions, relative to the current staffing mix.

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