Research on the Influence of Last Digit Restriction to the Traffic Flow Characteristics

2012 ◽  
Vol 253-255 ◽  
pp. 1976-1981
Author(s):  
Hao Hua Du ◽  
Meng Pan
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Recovery Time ◽  
Flow Characteristics ◽  
License Plate ◽  
Traffic Condition ◽  
The Road ◽  
Vehicle Velocity ◽  
Before And After ◽  
Changing Trend

The Beijing government is taking measures to remit traffic congestions by restriction based on the last digit on a license plate, which influences the characteristic of traffic flow. This paper first builds a model about traffic flow characteristic, including vehicle velocity, roadway reliability and traffic congestion recovery time. The paper also researches different pattern of vehicle velocity before and after the rail number restriction, analyzes the changing trend of road-mobility reliability with traffic demands, and calculates the pattern of traffic congestion recovery time between the restrictions. The result indicates that when traffic flow’s density is large, the vehicle’s velocity is increased to 180% of the original after the restriction; and the recovery time from congestion to smooth is decreased to 75.8% of the original; after taken the restriction measures, the road unblocked reliability in Peak hours is increased, and the traffic condition ameliorate evidently.

Evaluation Analysis and Optimization Design of Urban Road Traffic Condition Based on VISSIM

2011 ◽  
Vol 97-98 ◽  
pp. 531-534
Author(s):  
Xin Qiu ◽  
An Xia Zheng ◽  
Ying Zhu ◽  
Bin Xu
Keyword(s):  
Traffic Flow ◽  
Optimization Design ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Simulation Software ◽  
Traffic Condition ◽  
Urban Road ◽  
The Road ◽  
Road Congestion

Based on the survey of the traffic flow characteristics in the intersection, combined with the traffic flow basic principle and the existing research results at home and abroad, the road congestion condition is evaluated by determining the microcosmic evaluation index coefficient by VISSIM microcosmic simulation software. Then, the reasonable measures are put forward to improve urban road congestion condition. The analysis shows that the residents’ trip efficiency is improved and the quality of the urban road traffic condition is ameliorated.

scholarly journals Prediction of Average Speed Based on Relationships Between Neighbouring Roads Using K-NN and Neural Network

2020 ◽  
Vol 16 (01) ◽  
pp. 18
Author(s):  
Bagus Priambodo ◽  
Azlina Ahmad ◽  
Rabiah Abdul Kadir
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Clustering Method ◽  
Traffic Condition ◽  
Average Speed ◽  
The Road ◽  
Road Congestion ◽  
Neighbouring Area ◽  
Road Segments

For decades, various algorithms to predict traffic flow have been developed to address traffic congestion. Traffic congestion or traffic jam occurs as a ripple effect from a road congestion in the neighbouring area. Previous research shows that there is a spatial correlation between traffic flow in neighbouring roads. Similar traffic pattern is observed between roads in a neighbouring area with respect to day and time. Currently, time series models and neural network models are widely applied to predict traffic flow and traffic congestion based on historical data. However, studies on relationships between road segments in a neighbouring area are still limited. It is important to investigate these relationships because they can assist drivers in avoiding roads which are impacted by road congestion. Also, the result can be used to improve the accuracy of prediction of traffic flow. Hence, this study investigates relationships of roads in a neighbouring area based on similarity of traffic condition. Traffic condition is influenced by number of vehicles and average speed of vehicles. In our study, clustering method is used to divide the speed of traffic into four (4) categories: very congested, congested, clear and very clear. We used k-means clustering method to cluster condition of traffic flow on road segments.  Then, we applied the k-Nearest Neighbour (k-NN) method to classify the traffic condition in neighbouring roads. From the classification of traffic condition in neighbouring roads, we then determine the relationship between road segments. We presented the road with highest relationship on the map and used it as input factor to predict traffic speed of the road using neural network. Results show that combination of k-means and k-NN method produced better results than using both, correlation method and using the k-means method only.

scholarly journals Visualization and Understanding of Traffic Flow and Congestion in India

2020 ◽  
Author(s):  
Tsutomu Tsuboi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Social Issues ◽  
Flow Characteristics ◽  
Flow Theory ◽  
Gujarat State ◽  
Traffic Condition ◽  
Traffic Flow Theory ◽  
Traffic Data Collection ◽  
Real Traffic

This study focuses on traffic condition analysis, especially in under developing country India and makes more visible of traffic flow by using traffic flow theory in order to understand real traffic condition. India is one of rapid economic growing countries and large market with second largest population 1.3 billion in 2018. On the other hand, there are social issues such as environment air pollution and global warming by traffic CO2 emission of transportation. This kind of condition is not only in India, but in other South East Asia and Africa in future. From recent more than one-month traffic observation in a typical major city Ahmedabad in Gujarat state, which has about 8 million population and industrialized city. In terms of traffic data collection, 14 CCTV cameras are used in the city. Based on multiple traffic cameras monitoring, author found the unique traffic flow characteristics and compares traffic flow theory. In this study, it is described what is key parameters to show real traffic congestion condition and how these congestion occurs.

Traffic Flow Characteristics on a Three-Lane Rural Highway in Finland: Results from Empirical Studies and Simulations

1997 ◽  
Vol 1572 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Åsa Enberg ◽  
Matti Pursula
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Empirical Studies ◽  
Flow Characteristics ◽  
Field Studies ◽  
Optimum Length ◽  
Before And After ◽  
Traffic Flow Characteristics ◽  
Simulation Results ◽  
Rural Highway

The traffic-flow characteristics on an experimental, 20-km-long three-lane highway section in Finland were studied. The sections of highway that have a separate passing lane consist of three lanes. The central lane is assigned alternately to each direction as a passing lane with a length of 1.05 to 1.70 km. The lengths of the no-overtaking zones between successive passing lanes are 1.5 to 4.0 km. The traffic-flow characteristics on the three-lane highway have been observed by comprehensive before-and-after field studies and complementary simulations. Because it was possible to use passing lanes, the number of overtakings on the three-lane highway was remarkably higher than on the former two-lane highway. The overall average travel speeds were slightly higher, and the speed decreased a little more slowly with increasing flow on the three-lane compared with the two-lane highway. Overall platooning and mean platoon lengths decreased as a result of platoon dispersal on the passing lanes. The speeds used in the passing lanes were clearly higher than in the basic lanes. According to the simulation results, the optimum length for a single passing lane was between 0.5 and 2.5 km depending on flow rate and measure of effectiveness. For the actual three-lane highway conditions, passing lanes 1.0 to 1.5 km long seemed to bring the most benefits.

scholarly journals PREDICTIVE MODELLING OF TRAFFIC FLOWFLOW IN AKURE, NIGERIA: UNSIGNALIZED INTERSECTIONS IN FOCUS

2017 ◽  
Vol 10 (2) ◽  
pp. 270-278
Author(s):  
Adebayo Oladipo Owolabi ◽  
Olugbenga Joseph Oyedepo ◽  
Enobong Etim Okoko
Keyword(s):  
Traffic Flow ◽  
Predictive Modelling ◽  
Study Data ◽  
Geometric Features ◽  
Peak Period ◽  
Flow Models ◽  
The Road ◽  
Traffic Characteristics ◽  
Unsignalized Intersections ◽  
Before And After

Unsignalized intersections namely two-way stop-controlled intersection (TWSC) and all-way stop-controlled intersection (AWSC) are widely used in Akure. Five intersections consisting of three Tee and two Cross that were critical to traffic flow in the study area were selected for study. Data on geometric features were collected using odometer, while traffic parameters were captured and metered using cine camera placed at a vantage point from the road section during peak and off-peak periods on week days. Traffic flows at the intersections were expressed as functions of traffic characteristics and geometric features of the approaches; while the effect of distances of intersections before and after the intersections studied were also incorporated as a correction factors in the models. The models were developed using multiple linear regression technique with the aid of SPSS software and validated with empirical data other than those used for model calibration. Adjusted R2 values of 0.881 and 0.882 were obtained for Tee and Cross intersections respectively for peak period, while 0.938 and 0.940 respectively were obtained for the off-peak period. These indicate that the flow models are very robust in replicating the observed data. The predictive models have the potential to accurately estimate traffic flow at intersections in the study area and other cities of the world with similar traffic conditions.

scholarly journals THE TRAFFIC VOLUME AND LEVEL OF SERVICE (LOS) OF UNIVERSITI PUTRA MALAYSIA (UPM) SERDANG CAMPUS MAIN ACCESS

2019 ◽  
Vol 17 ◽  
Author(s):  
Zakiah Ponrahono ◽  
Noorain Mohd Isa ◽  
Ahmad Zaharin Aris ◽  
Rosta Harun
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Noise Pollution ◽  
Traffic Volume ◽  
Level Of Service ◽  
Idle Mode ◽  
The Road ◽  
Road Capacity ◽  
Motorized Vehicles ◽  
University Setting

The inbound and outbound traffic flow characteristic of a campus is an important physical component of overall university setting. The traffic circulation generated may create indirect effects on the environment such as, disturbance to lecturetime when traffic congestion occurs during peak-hours, loss of natural environment and greenery, degradation of the visual environment by improper or illegal parking, air pollution from motorized vehicles either moving or in idle mode due to traffic congestion, noise pollution, energy consumption, land use arrangement and health effects on the community of Universiti Putra Malaysia (UPM) Serdang. A traffic volume and Level of Service (LOS) study is required to facilitate better accessibility and improves the road capacity within the campus area. The purpose of this paper is to highlight the traffic volume and Level of Service of the main access the UPM Serdang campus. A traffic survey was conducted over three (3) weekdays during an active semester to understand the traffic flow pattern. The findings on traffic flow during peak hours are highlighted. The conclusions of on-campus traffic flow patterns are also drawn.

Bottleneck Simulation of Two-Lane Traffic CA Model with Turn Signal

2013 ◽  
Vol 404 ◽  
pp. 640-644
Author(s):  
Rui Kang ◽  
Kai Yang
Keyword(s):  
Numerical Simulations ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Driver Behavior ◽  
Traditional Model ◽  
Right Of Way ◽  
Time Space ◽  
Before And After ◽  
Ca Model ◽  
The Right

Based on the STCA model, an improved two-lane traffic CA model in view of turn signals is proposed. The model considers changes in driver behavior before and after the signaling of the leading vehicle, and introduces rules of changing lanes, cutting lanes and yielding the right of way for the flowing vehicle. Through computer numerical simulations, this study has presented time-space diagrams and also analyzed the effects of driver behavior of the rear vehicles on traffic flow. The results reveal that a higher rate of cutting lanes incurs a heavier traffic flow in normal situations while yielding the right of way relieves traffic congestion in a bottleneck situation. Compared with the traditional model, STCA model can depict more complex traffic situations resulted from different driver behaviors and reproduce a more realistic process of traffic flow.

scholarly journals Mixed Vehicular Traffic Flow Model on an Inclined Multilane Road

2020 ◽  
Vol 5 (7) ◽  
pp. 331-342
Author(s):  
Delina Mshai Mwalimo ◽  
Mary Wainaina ◽  
Winnie Kaluki
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Flow Model ◽  
Free Flow ◽  
Traffic Density ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
The Road ◽  
Slow Moving

This study outlines the Kerner’s 3 phase traffic flow theory, which states that traffic flow occurs in three phases and these are free flow, synchronized flow and wide moving jam phase. A macroscopic traffic model that is factoring road inclination is developed and its features discussed. By construction of the solution to the Rienmann problem, the model is written in conservative form and solved numerically. Using the Lax-Friedrichs method and going ahead to simulate traffic flow on an inclined multi lane road. The dynamics of traffic flow involving cars(fast moving) and trucks(slow moving) on a multi-lane inclined road is studied. Generally, trucks move slower than cars and their speed is significantly reduced when they are moving uphill on an in- clined road, which leads to emergence of a moving bottleneck. If the inclined road is multi-lane then the cars will tend to change lanes with the aim of overtaking the slow moving bottleneck to achieve free flow. The moving bottleneck and lanechange ma- noeuvres affect the dynamics of flow of traffic on the multi-lane road, leading to traffic phase transitions between free flow (F) and synchronised flow(S). Therefore, in order to adequately describe this kind of traffic flow, a model should incorporate the effect of road inclination. This study proposes to account for the road inclination through the fundamental diagram, which relates traffic flow rate to traffic density and ultimately through the anticipation term in the velocity dynamics equation of macroscopic traffic flow model. The features of this model shows how the moving bottleneck and an incline multilane road affects traffic transistions from Free flow(F) to Synchronised flow(S). For a better traffic management and control, proper understanding of traffic congestion is needed. This will help road designers and traffic engineers to verify whether traffic properties and characteristics such as speed(velocity), density and flow among others determines the effectiveness of traffic flow.

scholarly journals Traffic Flow Analysis and Management

2021 ◽  
Author(s):  
Tsutomu Tsuboi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Flow Analysis ◽  
Traffic Monitoring ◽  
Diving Behavior ◽  
Low Carbon ◽  
Gujarat State ◽  
Traffic Condition ◽  
Transportation Demand ◽  
The City

This research is about joint government founded program between Japan and India or Science and Technology Research Partnership for Sustainable development (SATREPS). The purpose of this research is to establish Low Carbon Transportation in developing countries and we choose one of major city in India, where it is Ahmedabad city of Gujarat state—west cost of India. In order to approach the target, we need to understand the current situation of traffic condition in the city. The current traffic condition in India is some chaotic because of their different driving behavior compared with the advanced countries. It is becoming the chaotic traffic condition in India by not only diving behavior during investigation of this research. The main reason of the traffic congestion comes from the unbalance between growing transportation demand and its insufficient infrastructure preparation. In this chapter, it introduces the current traffic condition based on four years monitoring of the traffic by the traffic monitoring cameras and comparison by the traffic flow theory at first. Then it introduces the new traffic analysis method especially for its traffic congestion analysis and its parameters. After the traffic congestion analysis, it summarizes conclusion and our next step from the experience.

scholarly journals UNDERSTANDING URBAN TRAFFIC FLOW CHARACTERISTICS FROM THE NETWORK CENTRALITY PERSPECTIVE AT DIFFERENT GRANULARITIES

2016 ◽  
Vol XLI-B2 ◽  
pp. 263-268 ◽  
Author(s):  
P. X. Zhao ◽  
S. M. Zhao
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Research Unit ◽  
Urban Traffic ◽  
Network Centrality ◽  
Trajectory Data ◽  
The Road ◽  
Analysis Process ◽  
Intersection Line ◽  
Taxi Trajectory

In this study, we analyze urban traffic flow using taxi trajectory data to understand the characteristics of traffic flow from the network centrality perspective at point (intersection), line (road), and area (community) granularities. The entire analysis process comprises three steps. The first step utilizes the taxi trajectory data to evaluate traffic flow at different granularities. Second, the centrality indices are calculated based on research units at different granularities. Third, correlation analysis between the centrality indices and corresponding urban traffic flow is performed. Experimental results indicate that urbaxperimental results indicate that urbaxperimental results indicate that urban traffic flow is relatively influenced by the road network structure. However, urban traffic flow also depends on the research unit size. Traditional centralities and traffic flow exhibit a low correlation at point granularity but exhibit a high correlation at line and area granularities. Furthermore, the conclusions of this study reflect the universality of the modifiable areal unit problem.

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