scholarly journals PATTERNS OF URBAN TRANSPORT FLOWS GENERATION

2020 ◽  
Vol 1 (154) ◽  
pp. 248-252 ◽  
Author(s):  
I. Chumachenko ◽  
A. Galkin ◽  
N. Davidich ◽  
Y. Kush ◽  
I. Litomin
Keyword(s):  
Nervous System ◽  
Travel Time ◽  
Traffic Flow ◽  
Individual Characteristics ◽  
Urban Transport ◽  
Traffic Intensity ◽  
Important Criterion ◽  
Traffic Lights ◽  
The Road ◽  
Expert Opinions

The article is devoted to explaining the issue of exploring the patterns of formation of urban traffic flows in case of the development of urban transport systems projects. Existing methods for predicting traffic flow parameters are developed for all drivers of vehicles, regardless of their individual characteristics, and contain only travel time as a parameter. It is proposed to use the route run, travel time, traffic intensity as the possible criteria, the route runs along the main roads, the condition of the road surface, the number of traffic lights on the route, and fatigue when driving. Based on the results of a questionnaire survey of drivers of individual vehicles, the significance of the criteria for choosing a route of movement for drivers with various types of nervous systems is assessed. The most significant criterion was set up when choosing a route for travel is the “condition of the road surface”. The second most important criterion is “run along the route”. The third criterion was “travel time”. The criterion “traffic intensity” has become even less significant for drivers. The next most important criterion was “the route take place over the main roads”. Even less significant was the criterion “quantity of traffic lights on the route”. The criterion “fatigue during movement” became the least significant. To assess the consistency of expert opinions, a concordance coefficient was used. The values of the concordance coefficient showed that there is a consistency of expert opinions both for the total population of drivers and for their groups, divided on the basis of “temperament”. It was found that when choosing a travel route, drivers are guided by numerous criteria. Moreover, the advantage or disadvantage of one or another criterion depends on its individual characteristics, which are determined by the properties of the central nervous system. Keywords: driver, route, traffic flow, vehicle, questionnaire, nervous system, criterion, significance.

A STUDY OF CITY TRAFFIC IN AFTERNOON RUSH HOURS

2013 ◽  
Vol 24 (06) ◽  
pp. 1350040 ◽  
Author(s):  
EDGAR ÁVALOS ◽  
D. W. HUANG ◽  
W. N. HUANG
Keyword(s):  
Cellular Automaton ◽  
Travel Time ◽  
Traffic Flow ◽  
Traffic Lights ◽  
Suburban Areas

The traffic of vehicles from downtown to suburban areas is investigated numerically. We propose a cellular automaton to simulate the traffic of vehicles within a city regulated by traffic lights. Both traffic flow and travel time are presented and we discuss some strategies to optimize these quantities.

scholarly journals Optimization of Traffic Flow On KS Tubun Street using Greenberg Model

2019 ◽  
Vol 8 (2S7) ◽  
pp. 83-86
Keyword(s):  
Traffic Flow ◽  
Red Light ◽  
Green Light ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
The Road ◽  
Road Users ◽  
Time Parameters

KS Tubun Street is a street in Bogor, which has a fairly high vehicle volume and become one of a high-traffic jam area. This is caused by KS Tubun Street is the main road for road users from Jakarta and Bogor. Traffic jam problem that occurs due to the confluence interchange of traffic flow and traffic lights settings that are not proportional to the volume of vehicles across the road. Optimization of traffic flow at KS Tubun Street performed by the stages of forming a model of traffic flow, determining the density and velocity of the vehicle is based on the Greenberg model, and determining the length of the traffic lights to avoid a buildup of vehicles. The result is a traffic flow model with distance and time parameters. The density of vehicles that occurs on the streets of KS. Tubun street based on the Greenberg model between 180 to 240 unit car of passanger (ucp) with the average velocity of vehicles 15 to 19.5 km per hour. The density of vehicles on KS. Tubun street can be break down by increasing time. Traffic light cycle time can be reduced for 8 seconds with the red light glowing time is 80 seconds and the green light glowing time is 62 seconds.

scholarly journals Development and Application of Dynamic Timing Optimization Platform for Big Data Intelligent Traffic Signals

2019 ◽  
Vol 136 ◽  
pp. 01008
Author(s):  
Zhao Wang ◽  
Mengjie Wang ◽  
Wenqiang Bao
Keyword(s):  
Big Data ◽  
Travel Time ◽  
Traffic Flow ◽  
Delay Time ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Total Delay ◽  
Timing Optimization ◽  
Traffic Lights ◽  
Signal Dynamic

As the number of car ownership increases, road traffic flow continues to increase. At the same time, traffic pressure at intersections is increasing as well. At present, most of the traffic lights in China are fixed cycle control. This timing control algorithm obviously cannot make timely adjustments according to changes in traffic flow. In this case, a large number of transportation resources would be wasted. It is very necessary to establish a dynamic timing system for Big data intelligent traffic signals. In this research, the video recognition method was used to acquire the number of vehicles at the intersection in real time, and the obtained data was processed by the optimization algorithm to make a reasonable dynamic timing of the traffic signals. The test results show that after using the big data intelligent traffic signal dynamic timing optimization control platform, in the experimental area, the overall total delay time was reduced by 23%, and the travel time was reduced by 15%. During the off-peak period, the overall total delay time in the experimental region was reduced by 17% and travel time was reduced by 10%. The big data intelligent traffic signal dynamic timing optimization platform would improve the operational efficiency and traffic supply capacity of the existing transportation infrastructure, and could provide real convenience for citizens.

Traffic Flow Simulator by Multiagent

2001 ◽  
Vol 13 (4) ◽  
pp. 419-425
Author(s):  
Hitoshi Tsunashima ◽  
◽  
Yasukazu Nishi ◽  
Takashi Honjyo ◽  
Hiroyuki Kaku ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Artificial Life ◽  
Flow Analysis ◽  
Essential Elements ◽  
Individual Characteristics ◽  
Traffic Flows ◽  
The Road ◽  
The Past ◽  
Flow Simulator ◽  
Unique Individual

Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their drivers' characteristics, which are important factors for any traffic flow analysis, have not been considered sufficiently enough in the past. This paper describes a new concept for simulating complex traffic flows by multiple agents. The agents are considered as a kind of artificial life (A-Life), and their behaviors are independently based on their own knowledge. Drivers, vehicles, roads, and the traffic environment, which are essential elements in our simulation, are defined as the agents. The combination of the driver agent and the vehicle agent work based on the drivers' fields of vision and their unique individual characteristics. The road agent communicates with the vehicle agent in regard to its velocity and position. The effectiveness of our new method for modeling a traffic flow is shown by a simulation study.

scholarly journals Analysis of the distribution of the number of applications of the estimated load on the Federal roads during the year

2018 ◽  
Vol 5 (4) ◽  
Author(s):  
Vladimir Akulov ◽  
Artem Tiraturyan ◽  
Ilya Bodro ◽  
Anastasia Simakova ◽  
Marina Farnieva
Keyword(s):  
Traffic Flow ◽  
Statistical Processing ◽  
Weather Conditions ◽  
Design Stage ◽  
Traffic Intensity ◽  
Agricultural Industry ◽  
The Road ◽  
Calculated Load ◽  
On The Road ◽  
Favorable Weather

The article is devoted to the statistical processing of traffic intensity and composition of traffic flow obtained from the points of automated traffic intensity accounting for 2010-2018 in order to determine the distribution of the number of applications of the calculated load by months. The main source of information for statistical processing was the results of traffic accounting on highways M-1 «Belarus», a-107 MMK Mozhaisk-Volokolamsk highway, M-3 «Ukraine», M-4 «don», M-4 «don». The correct determination of the traffic intensity and composition of the traffic flow is an important task that allows you to make adequate decisions at the design stage of roads, namely to choose a road structure that can operate under load from the actual traffic flow for the entire service life. The authors calculated the total number of applications of the calculated load to the point on the surface of the coating, using the coefficients of reduction of vehicles to the calculated load of 115 kN. After calculating the total number of applications, the resulting value was divided by the number of days in the month in question. According to the data obtained, the total total number of applications of the calculated load at all points of accounting, by month, was found. The minimum values of the number of load applications are observed in winter (January, February, March), when the situation on the road deteriorates due to weather conditions. The values range from 4.75 % to 8 % for roads M-1 «Belarus», M-3 «Ukraine», M-4 «Don», M-4 «Don». The maximum values of the number of load applications observed in the warmer months (July, August, September, October), due to the fact that there are favorable weather conditions for recreation and the most active agricultural industry. The values range from 7.6 % to 11.3 % for the roads M-1 «Belarus», M-3 «Ukraine», M-4 «Don», M-4 «Don».

scholarly journals Device and Algorithm for Vehicle Detection and Traffic Intensity Analysis

2021 ◽  
Vol 17 (1) ◽  
pp. 83-92
Author(s):  
Mikhail Gorobetz ◽  
Andrey Potapov ◽  
Aleksandr Korneyev ◽  
Ivars Alps
Keyword(s):  
Traffic Flow ◽  
Internal Combustion Engines ◽  
Radio Channel ◽  
Vehicle Detection ◽  
Detection Methods ◽  
Traffic Intensity ◽  
Traffic Light ◽  
Traffic Lights ◽  
Advantages And Disadvantages ◽  
Sensor Module

Abstract To effectively manage the traffic flow in order to reduce traffic congestion, it is necessary to know the volumes and quantitative indicators of this flow. Various detection methods are known for detecting a vehicle in a lane, which, in turn, have their own advantages and disadvantages. To detect vehicles and analyse traffic intensity, the authors use a pulse coherent radar (PCR) sensor module. Testing of various modes of operation of the radar sensor was carried out to select the optimal mode for detecting vehicles. The paper describes a method for fixing vehicles of different sizes, filtering and separating the vehicle from the traffic flow. The developed vehicle detection device works in conjunction with signal traffic lights, through which traffic control takes place. The signal traffic lights, which have their own sensors and control units, communicate with each other via a radio channel; there is no need for cable laying. The system is designed to work on road maintenance sites. The paper describes the experimental data when testing on a separate section of the road. The experiment showed the advantage of traffic lights (cars passed the regulated traffic light faster) from the point of view of calculating the traffic flow over the normal traffic light operation. Reducing downtime in traffic jams, in turn, has a beneficial effect on the environmental situation, since at the moment internal combustion engines prevail in vehicles.

scholarly journals Soluciones de conducción para vehículos autónomos, y propuestas adaptativas para establecer los tiempos de semáforos y elegir rutas

2019 ◽  
Vol 20 (2) ◽  
Author(s):  
José Gerardo Carrillo González
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Traffic Lights ◽  
Linear Path ◽  
Time Cycle ◽  
Adaptive Solutions ◽  
The Times ◽  
The Right

Two objectives are pursued in this article: 1) with adaptive solutions, improve the traffic flow by setting the time cycle of traffic lights at intersections and reduce the travel time by selecting the vehicles route (treated as separated problems). 2) Avoid driving conflicts among autonomous vehicles (which have defined trajectories) and these with a non-autonomous vehicle (which follows a free path). The traffic lights times are set with formulas that continuously recalculate the times values according the number of vehicles on the intersecting streets. For selecting the vehicles route an algorithm was developed, this calculates different routes (connected streets that conform a solution from the origin to the destination) and selects a route with low density. The results of the article indicate that the adaptive solutions to set the traffic lights times and to select the vehicles path, present a greater traffic flow and a shorter travel time, respectively, than conventional solutions. To avoid collisions among autonomous vehicles which follow a linear path, an algorithm was developed, this was successfully tested in different scenarios through simulations, besides the algorithm allows the interaction of a vehicle manually controlled (circulating without restrictions) with the autonomous vehicles. The algorithm regulates the autonomous vehicles acceleration (deceleration) and assigns the right of way among these and with the human controlled vehicle.

scholarly journals CALCULATION OF CAR TRAFFIC CAPACITY AT THE CROSSROAD

2021 ◽  
pp. 54-58
Author(s):  
Oleksandr Solarov ◽  
Maryna Mikulina ◽  
Olexandr Tatsenko
Keyword(s):  
Traffic Flow ◽  
Optimal Algorithm ◽  
Main Task ◽  
Maximum Throughput ◽  
Traffic Lights ◽  
The Road ◽  
Road Section ◽  
Improved Performance ◽  
On The Road ◽  
Real Flow

The capacity of a road section depends on many factors, such as the width of the carriageway, the permissible visibility, the slopes, the turning radii, the composition of the cars, the maneuverability and the design of the cars. The development of the automotive industry leads to improved performance of cars and improved throughput. Changing all of these components changes the bandwidth. When the capacity is calculating the composition of the traffic flow became one of the key factors. Mobile traffic is characterized by the composition of different (by age and purpose) vehicles. The composition of the traffic flow is displayed as a percentage. Obtaining and analyzing the algorithm for determining the capacity of traffic flow on a particular section of road (interchange). The analyze of the current state of car use in Ukraine and select the optimal algorithm for obtaining real flow data on the road section was made. The main task of the engineer during the design of a certain section of the road is to ensure the maximum capacity of the road section. Maximum throughput is achieved by improving the road surface, widening the roadway (increasing the number of lanes and installing appropriate signs), allocating reversing lanes and installing reversing traffic lights. When calculating the capacity, it is necessary to take into account when characterizing the relationship between cars in the flow in different road conditions. Intervals between cars in a stream can change even at high intensity of movement that in turn quit

scholarly journals Modelling of car exhaust emission on the basis of data obtained from microscopic traffic flow model

2018 ◽  
Vol 19 (6) ◽  
pp. 786-789
Author(s):  
Mikołaj Wiewióra ◽  
Łukasz Drąg
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Exhaust Emission ◽  
Emission Model ◽  
Traffic Flow Model ◽  
Traffic Lights ◽  
The Road ◽  
Car Exhaust ◽  
Emission Modelling ◽  
Traffic Simulations

In the paper the procedure for car exhaust emission calculation along the road network has been presented. Input parameters for an emission model were obtained from the microscopic traffic flow model. Traffic simulations have been performed in Vissim software. To analyse emission in a road sections whole network has been discretized into fixed length segments. The examples of traffic flow emission modelling for selected lanes at intersection where the traffic flow is controlled by traffic lights are also presented.

scholarly journals PERSEPSI MASYARAKAT TENTANG ALTERNATIF PEMECAHAN MASALAH TRANSPORTASI DI JALAN RIAU KOTA PEKANBARU

2019 ◽  
Vol 2 (1) ◽  
pp. 1-12
Author(s):  
M Taufik Nizam ◽  
Puji Astuti ◽  
Mardianto Manan
Keyword(s):  
Public Transport ◽  
Public Perception ◽  
Urban Transport ◽  
Traffic Light ◽  
Related Factors ◽  
Traffic Lights ◽  
The Road ◽  
Road Users ◽  
Policy Holder ◽  
Alternative Solutions

Riau street in Pekanbaru classified as secondary arterial roads with solid activit s so susceptible to the problem of traffic. The physical condition of damaged roads, land use mix and irregular, activities of right and left side crowded streets, parking inadequate, lack of public transport, and the behavior of road users who are not orderly, is the picture of the problem of traffic that occurs on the Riau street. This is supported also by the growth in the number of private vehicles. The accumulation of a variety of symptoms that led to the road capacity can no longer accommodate the volume of passing vehicles, causing traffic delays. One way to unravel this problem is to assess the public's perception of road users alternative solutions to problems related to urban transport in Riau street. The method used is descriptive quantitative with the number of respondents 100 people and supported by a statement from the policy holder of the traffic in the city of Pekanbaru . Public perception related factors causing transportation problems in Riau street is the traffic policy is less strict in discipline of road users, the traffic volume exceeds the capacity of the road, setting traffic light rigid, road users are not orderly, parking space is limited, public transport is limited, and the illegal parking. Alternative solutions is the increase in traffic policy, modify or regulate the flow of traffic, optimization of public transport facilities and infrastructure, restrictions on the use of private vehicles, road widening, traffic lights adjustment, socialization regulation and enforcement, and the construction of flyovers..

Sign in / Sign up

Export Citation Format

Share Document