Abstract: Carbon dioxide (CO2) alongside other gas emissions in the atmosphere cause a greenhouse effect, resulting in an increase of the average temperature of the planet. Transportation vehicles are among the main contributors of CO2 emission. Stationary vehicles with initiated motors produce more emissions than mobile ones. Intersections with traffic lights that force the vehicles to become stationary for a period of time produce more CO2 pollution than other parts of the road. This paper focuses on analyzing the CO2 produced by the traffic flow at Anzac Parade Road - Barker Street intersection in Sydney, Australia, before and after the implementation of Light rail transport (LRT). The data are gathered during the construction phase of the LRT by collecting the number of vehicles on each path of the intersection for 15 minutes during the evening rush hour of 1 week (6-7 pm, July 04-31, 2018) and then multiplied by 4 to calculate the flow of vehicles in 1 hour. For analyzing the data, the microscopic simulation software “VISSIM” has been used. Through the analysis, the traffic flow was processed in three stages: before and after implementation of light rail train, and one during the construction phase. Finally, the traffic results were input into another software called “EnViVer”, to calculate the amount of CO2 during 1 h. The results showed that after the implementation of the light rail, CO2 will drop by a minimum of 13%. This finding provides an evidence that light rail is a sustainable mode of transport.
Abstract: This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.
Abstract: Urban intersection control without the use of the traffic light has the potential to vastly improve the efficiency of the urban traffic flow. For most proposals in the literature, such lightless intersection control depends on the mass market commercialization of highly intelligent autonomous vehicles (AV), which limits the prospects of near future implementation. We present an efficient lightless intersection traffic control scheme that only requires Level 1 AV as defined by NHTSA. The technological barriers of such lightless intersection control are thus very low. Our algorithm can also accommodate a mixture of AVs and conventional vehicles. We also carry out large scale numerical analysis to illustrate the feasibility, safety and robustness, comfort level, and control efficiency of our intersection control scheme.
Abstract: The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.
Abstract: A Distributed Denial of Service (DDoS) attack is a
major threat to cyber security. It originates from the network layer or
the application layer of compromised/attacker systems which are
connected to the network. The impact of this attack ranges from the
simple inconvenience to use a particular service to causing major
failures at the targeted server. When there is heavy traffic flow to a
target server, it is necessary to classify the legitimate access and
attacks. In this paper, a novel method is proposed to detect DDoS
attacks from the traces of traffic flow. An access matrix is created
from the traces. As the access matrix is multi dimensional, Principle
Component Analysis (PCA) is used to reduce the attributes used for
detection. Two classifiers Naive Bayes and K-Nearest neighborhood
are used to classify the traffic as normal or abnormal. The
performance of the classifier with PCA selected attributes and actual
attributes of access matrix is compared by the detection rate and
False Positive Rate (FPR).
Abstract: In this paper the influence of heterogeneous traffic on
the temporal variation of ambient PM10, PM2.5 and PM1
concentrations at a busy arterial route (Sardar Patel Road) in the
Chennai city has been analyzed. The hourly PM concentration, traffic
counts and average speed of the vehicles have been monitored at the
study site for one week (19th-25th January 2009). Results indicated
that the concentrations of coarse (PM10) and fine PM (PM2.5 and
PM1) concentrations at SP road are having similar trend during peak
and non-peak hours, irrespective of the days. The PM concentrations
showed daily two peaks corresponding to morning (8 to 10 am) and
evening (7 to 9 pm) peak hour traffic flow. The PM10 concentration is
dominated by fine particles (53% of PM2.5 and 45% of PM1). The
high PM2.5/PM10 ratio indicates that the majority of PM10 particles
originate from re-suspension of road dust. The analysis of traffic flow
at the study site showed that 2W, 3W and 4W are having similar
diurnal trend as PM concentrations. This confirms that the 2W, 3W
and 4W are the main emission source contributing to ambient PM
concentration at SP road. The speed measurement at SP road showed
that the average speed of 2W, 3W, 4W, LCV and HCV are 38, 40,
38, 40 and 38 km/hr and 43, 41, 42, 40 and 41 km/hr respectively for
the weekdays and weekdays.
Abstract: The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.
Abstract: Traffic Density provides an indication of the level of
service being provided to the road users. Hence, there is a need to
study the traffic flow characteristics with specific reference to
density in detail. When the length and speed of the vehicles in a
traffic stream vary significantly, the concept of occupancy, rather
than density, is more appropriate to describe traffic concentration.
When the concept of occupancy is applied to heterogeneous traffic
condition, it is necessary to consider the area of the road space and
the area of the vehicles as the bases. Hence, a new concept named,
'area-occupancy' is proposed here. It has been found that the
estimated area-occupancy gives consistent values irrespective of
change in traffic composition.
Abstract: In this paper, we use an M/G/C/C state dependent
queuing model within a complex network topology to determine the
different performance measures for pedestrian traffic flow. The
occupants in this network topology need to go through some source
corridors, from which they can choose their suitable exiting
corridors. The performance measures were calculated using arrival
rates that maximize the throughputs of source corridors. In order to
increase the throughput of the network, the result indicates that the
flow direction of pedestrian through the corridors has to be restricted
and the arrival rates to the source corridor need to be controlled.
Abstract: Biological evolution has generated a rich variety of
successful solutions; from nature, optimized strategies can be
inspired. One interesting example is the ant colonies, which are able
to exhibit a collective intelligence, still that their dynamic is simple.
The emergence of different patterns depends on the pheromone trail,
leaved by the foragers. It serves as positive feedback mechanism for
sharing information.
In this paper, we use the dynamic of TASEP as a model of
interaction at a low level of the collective environment in the ant-s
traffic flow. This work consists of modifying the movement rules of
particles “ants" belonging to the TASEP model, so that it adopts with
the natural movement of ants. Therefore, as to respect the constraints
of having no more than one particle per a given site, and in order to
avoid collision within a bidirectional circulation, we suggested two
strategies: decease strategy and waiting strategy. As a third work
stage, this is devoted to the study of these two proposed strategies-
stability. As a final work stage, we applied the first strategy to the
whole environment, in order to get to the emergence of traffic flow,
which is a way of learning.
Abstract: A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.