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Journal articles on the topic 'Traffic flow Research Australia'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Qi, Yanmin, Zuduo Zheng, and Dongyao Jia. "Exploring the Spatial-Temporal Relationship between Rainfall and Traffic Flow: A Case Study of Brisbane, Australia." Sustainability 12, no. 14 (July 11, 2020): 5596. http://dx.doi.org/10.3390/su12145596.

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The impact of inclement weather on traffic flow has been extensively studied in the literature. However, little research has unveiled how local weather conditions affect real-time traffic flows both spatially and temporally. By analysing the real-time traffic flow data of Traffic Signal Controllers (TSCs) and weather information in Brisbane, Australia, this paper aims to explore weather’s impact on traffic flow, more specifically, rainfall’s impact on traffic flow. A suite of analytic methods has been applied, including the space-time cube, time-series clustering, and regression models at three different levels (i.e., comprehensive, location-specific, and aggregate). Our results reveal that rainfall would induce a change of the traffic flow temporally (on weekdays, Saturday, and Sunday and at various periods on each day) and spatially (in the transportation network). Particularly, our results consistently show that the traffic flow would increase on wet days, especially on weekdays, and that the urban inner space, such as the central business district (CBD), is more likely to be impacted by inclement weather compared with other suburbs. Such results could be used by traffic operators to better manage traffic in response to rainfall. The findings could also help transport planners and policy analysts to identify the key transport corridors that are most susceptible to traffic shifts in different weather conditions and establish more weather-resilient transport infrastructures accordingly.

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2

Nguyen-Phuoc, Duy Q., Graham Currie, Chris De Gruyter, and William Young. "Net Impacts of Streetcar Operations on Traffic Congestion in Melbourne, Australia." Transportation Research Record: Journal of the Transportation Research Board 2648, no. 1 (January 2017): 1–9. http://dx.doi.org/10.3141/2648-01.

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Public transit is widely recognized to reduce urban traffic congestion, as it encourages automobile travelers off the road. However, streetcars have been criticized for causing traffic congestion because large trams must operate in mixed traffic on narrow, congested streets. At the same time, streetcars reduce congestion by encouraging automobile drivers to use trams. So what is the net effect of streetcars on congestion? This paper presents a new method for assessing the net traffic congestion effects associated with streetcar operations in Melbourne, Australia, which has the largest streetcar network in the world. Impacts were determined with the use of a traffic network model to compare congestion with trams and without trams. The positive impacts of trams were estimated by using mode shift from tram to automobile when tram services were removed. Negative impacts were explored by considering streetcar traffic operations, the impact of curbside tram stops, and the effect of exclusive priority tram lanes on traffic flow. Findings show that the streetcar network in inner Melbourne results in a net congestion benefit to traffic; a 3.4% decrease in vehicle time traveled and total delay on the road network was established. The streetcar network also contributes to reducing the number of moderately congested links by 16%. Areas for future research are suggested, such as exploring the spatial distribution of the mode shift to automobile and the long-term effect of trams on traffic.

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Choi, Seongjin, Hwasoo Yeo, and Jiwon Kim. "Network-Wide Vehicle Trajectory Prediction in Urban Traffic Networks using Deep Learning." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 45 (September 7, 2018): 173–84. http://dx.doi.org/10.1177/0361198118794735.

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This paper proposes a deep learning approach to learning and predicting network-wide vehicle movement patterns in urban networks. Inspired by recent success in predicting sequence data using recurrent neural networks (RNN), specifically in language modeling that predicts the next words in a sentence given previous words, this research aims to apply RNN to predict the next locations in a vehicle’s trajectory, given previous locations, by viewing a vehicle trajectory as a sentence and a set of locations in a network as vocabulary in human language. To extract a finite set of “locations,” this study partitions the network into “cells,” which represent subregions, and expresses each vehicle trajectory as a sequence of cells. Using large amounts of Bluetooth vehicle trajectory data collected in Brisbane, Australia, this study trains an RNN model to predict cell sequences. It tests the model’s performance by computing the probability of correctly predicting the next [Formula: see text] consecutive cells. Compared with a base-case model that relies on a simple transition matrix, the proposed RNN model shows substantially better prediction results. Network-level aggregate measures such as total cell visit count and intercell flow are also tested, and the RNN model is observed to be capable of replicating real-world traffic patterns.

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Dominey-Howes, D., and J. Goff. "Hanging on the line – on the need to assess the risk to global submarine telecommunications infrastructure – an example of the Hawaiian "bottleneck" and Australia." Natural Hazards and Earth System Sciences 9, no. 2 (April 17, 2009): 605–7. http://dx.doi.org/10.5194/nhess-9-605-2009.

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Abstract. National economies are becoming increasingly dependent on the global telecommunications system – and in particular, its submarine cable infrastructure. We note that a variety of natural hazard processes are capable of damaging and destroying this infrastructure, both in deep water and at the coast. Some places within the global telecommunications system are already known to be bottlenecks or "choke points". Hawaii is just such a choke point and interestingly, Hawaii is also affected by numerous large magnitude natural hazard processes. Any damage to the submarine telecommunications infrastructure routed through Hawaii could result in significant impacts on the electronic flow of data and voice traffic, negatively affecting dependent economies such as Australia. We propose that proper risk assessments be undertaken at all bottlenecks in the global telecommunications system affected by natural hazards (such as tsunami). We use Hawaii as an example of the sort of research that should be undertaken.

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5

Glannopoulos, G. A., and Muhammad A. S. Mustafa. "Saturation Flow and Capacity of Shared Lanes: Comparative Evaluation of Estimation Methods." Transportation Research Record: Journal of the Transportation Research Board 1555, no. 1 (January 1996): 50–58. http://dx.doi.org/10.1177/0361198196155500107.

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The operation of shared lanes, especially in the case of permitted phasing control, is still considered a complicated task and one for which many procedures and methods have been introduced. Dealt with here is the complexity when left- or right-turn movements or both are made during the unsaturated part of the opposing traffic flow. Three main methods used for estimating the shared lane's saturation flow rate and capacity values—that used in the 1985 Highway Capacity Manual (HCM) and the Australian Road Research Board (ARRB) and the Canadian methods—were analyzed and evaluated. The methodology for the comparative evaluation was based on two main approaches. In the first approach, example 1 of Chapter 9 of the HCM was used as a case study in which left through and left through right shared lanes exist in permitted phase control. In this case several computer runs were performed using the programs SIDRA and SINTRAL to estimate saturation flow and capacity values of the shared lanes opposed by different traffic volumes of the conflicting movements. Results of this approach showed that the 1985 HCM and ARRB methods are fairly close in estimating saturation flow and capacity, whereas the Canadian method gave considerably different results. Analysis showed that the sensitivity of the Canadian method to estimate saturation flow rates of the shared lane in cases of different levels of opposing traffic was an average of 10 times higher than the average of the two other methods, which were very close in their estimation of levels of opposing traffic volumes. In the second approach, field measurements of saturation flow rate values of shared lanes at different locations and operational conditions were compared with the values estimated by the three methods under the same conditions. Results, based on field observations, revealed that the Canadian method estimates of saturation flow were always lower than the measured values. At low saturation flow values, HCM estimates were slightly higher than the observed values; however, at higher saturation flow rate values. HCM estimates closely matched the observed ones. The ARRB method estimates were quite close to the observed saturation flow values under all of the different conditions considered in the field observation task.

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6

Afkham, Maryam, Reza Ramezanian, and Shahrooz Shahparvari. "Balancing traffic flow in the congested mass self-evacuation dynamic network under tight preparation budget: An Australian bushfire practice." Omega 111 (September 2022): 102658. http://dx.doi.org/10.1016/j.omega.2022.102658.

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7

Tondang, Ridho, Kunarso Kunarso, Jarot Marwoto, Heryoso Setiyono, and Hariyadi Hariyadi. "Current Patterns on East Season in The Northern Waters of The Sunda Strait." Indonesian Journal of Oceanography 2, no. 1 (February 29, 2020): 64–72. http://dx.doi.org/10.14710/ijoce.v2i1.7301.

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The northern waters of Sunda Strait is the first Indonesian Archipelagic Sea Lanes. (ALKI I) which is an important and a very crowded shipping lane. The first Indonesias Archipelagic Sea Lanes (ALKI 1) connects the marine traffic from Africa, West Australia to South China Sea, Japan and the other way around. Indonesia in determining the archipelagic sea lanes considers several criterias, one of them is the oceanographic condition which is the ocean currents. The purpose of this research is to examine the characteristic of the ocean current pattern in the northern waters of Sunda Strait. The stages of this research include the measurement of field data, field data processing, and hydrodynamics modeling. The research location was determined by purposive sampling method. The determination of the research location follows the path of bathymethry. The result of field measurement is processed then used as data validation of current simulation result of hydrodinamic model. The result of the hydrodynamics model simulation showing the direction of current in northern waters of Sunda Strait moving back and forth following the tidal periods. The direction of the dominant current in northern waters of Sunda Strait is to Northeast (flood current) and Southwest (ebb current). The current velocity in northern waters of Sunda Strait is approximately between 0,0122 m/s and 2,590 m/s. The maximum velocity of the current belongs to several observation points that located in the seabed. This is to be expected due to the impact of Indonesia Through Flow.

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8

Polus, Abishai, and Sitvanit Shmueli. "Analysis and Evaluation of the Capacity of Roundabouts." Transportation Research Record: Journal of the Transportation Research Board 1572, no. 1 (January 1997): 99–104. http://dx.doi.org/10.3141/1572-12.

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Roundabouts are replacing conventional unsignalized intersections in many parts of the world and could become more widespread in the United States, although there are some limitations as well as clear advantages. Models for entry capacity into the rotary were developed. Entry capacity depends on the geometric characteristics of the roundabout, particularly the diameter of the outside circle of the intersection. The geometric characteristics determine the speed of vehicles around the central island and, therefore, have an impact on the gap-acceptance process and consequently the capacity. Traffic conditions that impede entry capacity involve the flow around the roundabout. Flow and geometric data from six small to medium-sized roundabouts were analyzed. Individual and aggregated entry-capacity models were calibrated by using the diameter and circulating flows as explanatory variables. Very good fits to the data were obtained; the results also fit models developed in other countries. The Australian model resulted in slightly higher entry capacities for moderate to low circulating flows and lower entry capacities for high circulating flows. Very close proximity to the German model was obtained, although it does not depend on the geometric characteristics of the circle. The roundabout provides an advantage over a conventional unsignalized intersection. A faithful concurrence between the model developed and the latest Highway Capacity Manual model for right-turn capacity at an unsignalized intersection is obtained if the circulating flow is replaced by the conflicting flow. The advantage of entry capacities of the roundabout over the calculated capacities of the Highway Capacity Manual left-turn model is shown. Further research is proposed to study the effect on entry capacity of two circulating lanes rather than one and the effect of the increase in circulating flows on the gap-acceptance process, particularly the reduction in critical gap at high flows.

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9

Li, Lifang. "Research on Traffic Flow Mathematical Model in Urban Traffic." International Journal of Smart Home 9, no. 11 (November 30, 2015): 123–32. http://dx.doi.org/10.14257/ijsh.2015.9.11.14.

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10

Zhu, Yong Cun, Wen Yong Li, Yang Zhang, and Tao Wang. "Research on Traffic Flow Redistribution Algorithm under the Traffic Accident." Applied Mechanics and Materials 253-255 (December 2012): 1747–50. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1747.

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To reduce traffic incident, it is imperative to take effective measures. This paper presents a dynamic route guidance method based on capacity constrained allocation method. Firstly, it analyzes the character of capacity constrained allocation method which takes into account the right of way and traffic load characteristics and used ant algorithms to optimize algorithm. Secondly, it integrates with multi-period continuous dynamic route guidance to realize the redistribution of road traffic flow . Finally, an example is took to prove that this manner can be a perfect solution to the road traffic evens on the impact of the road traffic flow.

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11

Tullberg, J. N., D. F. Yule, and D. McGarry. "Controlled traffic farming—From research to adoption in Australia." Soil and Tillage Research 97, no. 2 (December 2007): 272–81. http://dx.doi.org/10.1016/j.still.2007.09.007.

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12

Hua Zhang, Xiaoye Wang, and Yingyuan Xiao. "Similarity Research for Urban Intersection Traffic Flow." International Journal of Digital Content Technology and its Applications 6, no. 1 (January 31, 2012): 439–45. http://dx.doi.org/10.4156/jdcta.vol6.issue1.53.

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13

Tu, Min, Baoshan Liu, and Fangqiang Zhong. "Research of intelligent traffic flow prediction algorithm." Journal of Physics: Conference Series 1423 (December 2019): 012038. http://dx.doi.org/10.1088/1742-6596/1423/1/012038.

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14

Zhao, Qing Yu, Li Hua Chen, Zhi Jun Gao, and Jin Xin Cao. "Research on the Urban Traffic Flow and Traffic Problems in Hohhot." Applied Mechanics and Materials 587-589 (July 2014): 2053–56. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.2053.

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With a sustained growth of cars, many urban traffic problems caused by cars should be solved as soon as possible. However, basic urban traffic investigation and analysis of current situation is the the basis and the key to solve the problems. In this paper, investigation of traffic volume and pot speed is done at DongYing Road in Hohhot, and basic data base is established. Some significant parameters of urban traffic are calculated, and current traffic situation of the investigated road is detailedly analysed and studied. What is more, some problems found during the investigation are proposed and corresponding feasible suggestions are given.

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15

Li, Yue, and Hua Pu Lu. "Research on Traffic Flow Characteristics of Urban Expressway." Applied Mechanics and Materials 587-589 (July 2014): 2036–39. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.2036.

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Urban expressways play an important role in urban traffic networks. Different from the highway speed-flow-density relationship, the urban expressway has more complicate characteristics. With the traffic stream data collected from loop detectors on different sites of the expressway in Beijing, traffic parameters of traffic speed, density and volume are analyzed. As the relationship of speed flow and density changes remarkably during different period of time, this paper establish a speed-flow-density model during nighttime and daytime separately. The relationship among traffic density, speed and volume are key-points analyzed. The research can provide data support and scientific basis for the design and planning of urban expressway.

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16

Huang, Zhi Peng, Lin Cheng, and Wei Hua Zhang. "Traffic Flow Turbulence Characteristics Research Based on the Cellular Automaton Model." Applied Mechanics and Materials 496-500 (January 2014): 3022–25. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.3022.

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Turbulence coefficient r is introduced to simulate traffic disorder traffic flow characteristics. By analyzing the disturbance vehicles in the driving environment of different disordered state, the values of model simulation under different conditions analysis, using the traffic flow turbulence coefficient r disorder defined traffic flow characteristics, offers new reference for the study of the traffic flow theory. The accident rate and traffic flow turbulence characteristics are simulated and analyzed, which provides the theoretical gist for the simulation study of traffic flow.

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17

Qin, Zhen Hai. "The Urban Road Short-Term Traffic Flow Prediction Research." Applied Mechanics and Materials 423-426 (September 2013): 2954–56. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2954.

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To predict the future traffic flow status more accurately is of great significance to alleviate urban traffic congestion for a short period of time and avoid the waste of social resources. At first, this paper summarizes the characteristics of urban expressway traffic flow. Then establishes BP neural network short-term traffic flow evaluation model based on MATLAB, and finally through the instance, verify the validity of the model.

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18

陈, 玉成. "Research on Optimal Traffic Flow Control Scheme for a Complex Traffic Node." Advances in Applied Mathematics 09, no. 05 (2020): 803–16. http://dx.doi.org/10.12677/aam.2020.95096.

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19

Xu, Xiusheng, Laixin Zhang, and Tianyi Tang. "Research Based on vehicle exhaust emission estimation." Highlights in Science, Engineering and Technology 4 (July 26, 2022): 265–72. http://dx.doi.org/10.54097/hset.v4i.913.

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With the development and progress of society, short-term traffic flow prediction has become an increasingly important topic. Accurate prediction of traffic flow can not only provide necessary guidance for the transportation department, but also bring convenience to travel, but also play an important role in the prevention and control of urban air pollution. This paper mainly studies the prediction of vehicle flow, and then estimates the vehicle exhaust through the calculated vehicle flow, trying to establish the estimation model of vehicle flow and vehicle exhaust. Through Gaode map interface and WGS-84 (GPS) coordinates of each bayonet provided, the road name corresponding to the bayonet equipment is obtained according to the distance vector, and the data is preprocessed. For the interval road motor vehicle flow, the dynamic prediction can be realized by using the interdependence between the time series observations. According to the time dimension of prediction, traffic flow prediction can generally be divided into long-term traffic flow prediction (in year), medium-term traffic flow prediction (in month and day) and short-term traffic flow prediction (in hour and minute). According to the data provided, due to the weak regularity of short-term traffic flow data of interval roads, strong random error interference, and high uncertainty, it is difficult to predict accurately, The long-term and medium-term traffic flow data have strong periodicity and weak random interference. Considering the accuracy and data provided, this paper mainly selects the prediction method based on endogenous variables represented by autoregressive moving average model ARIMA and time cycle neural network LSTM. Because the use conditions of the two models are different, it is necessary to improve the model and modify the use scenario of the model. The advantage of this method is that the data acquisition cost is low and easy to implement. Finally, the prediction effect of traffic flow is evaluated by cellular automata to improve the performance of the model.

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Xiong, Junting, and Hongbin Xie. "Research Prospects of Ship Traffic Flow Simulation Technology." IOP Conference Series: Earth and Environmental Science 189, no. 6 (November 6, 2018): 062031. http://dx.doi.org/10.1088/1755-1315/189/6/062031.

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21

Hu, Jun, Minghui Wang, Haibo Hu, and Lei You. "Research on Influence Factors of Air Traffic Flow." Advanced Science Letters 12, no. 1 (June 15, 2012): 418–22. http://dx.doi.org/10.1166/asl.2012.2763.

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22

Zeng, Jun-Wei, Sen-Bin Yu, Yong-Sheng Qian, Xu-Ting Wei, Xiao Feng, and Hui Wang. "Research on traffic flow characteristics at signal intersection." Modern Physics Letters B 31, no. 26 (September 20, 2017): 1750238. http://dx.doi.org/10.1142/s0217984917502384.

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Based on the cautious driving behavior and the principle of the vehicles at left-side having priority to pass in the intersection, a two-dimensional cellular automata model for planar signalized intersection (NS-STCA) is established. The different turning vehicles are regarded as the research objects and the effect of the left-turn probability, signal cycle, vehicle flow density on traffic flow at the intersection is investigated.

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23

Tang, Haijing, Yu Liang, Zhongnan Huang, Taoyi Wang, Lin He, Yicong Du, Xu Yang, and Gangyi Ding. "Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research." Computational Intelligence and Neuroscience 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/1874945.

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The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction.

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Chen, Ming Qiang, and Jun Hong Feng. "Research of Air Traffic Flow Forecasts Based on BP Neural Network." Advanced Materials Research 671-674 (March 2013): 2912–15. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.2912.

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Air traffic is increasing worldwide at a steady annual rate, and airport congestion is already a major issue for air traffic controllers. The traditional method of traffic flow prediction is difficult to adapt to complex air traffic conditions. Due to its self-learning, self-organizing, self-adaptive and anti-jamming capability, the neural network can predict more effectively the air traffic flow than the traditional methods can. A good method for training is an important problem in the prediction of air traffic flow with neural network. This paper will try to find a new model to solve the traffic flow prediction problem by back propagation neural network.

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Zhang, Yi, and Chang Hua Li. "Research on Measure of Disorder in Traffic Flow Using 2D Entropy." Advanced Materials Research 962-965 (June 2014): 2510–15. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2510.

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The effective measure of the disorder in a traffic flow has a great significance to improve the traffic condition and reduce the negative impact on environment caused by traffic jams. Since the traffic one-dimension entropy cannot reflect the spatial distribution characteristics, this paper proposed and defined traffic two-dimension entropy that reflected the statistical information of vehicle types and spatial distribution. In order to reflect the actual condition of a road, the weight of space around a vehicle was used in the simulation. The simulation results showed that: traffic two-dimension entropy to quantify and describe the disorder in traffic flow is reasonable and effective.

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26

Zhang, He Quan. "Research and Improvement of the Keep-Right-Except-to-Pass Rule." Advanced Materials Research 915-916 (April 2014): 459–63. http://dx.doi.org/10.4028/www.scientific.net/amr.915-916.459.

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In order to deal with the impact on traffic flow of the rule, we compare the influence factors of traffic flow (passing, etc.) into viscous resistance of fluid mechanics, and establish a traffic model based on fluid mechanics. First, in heavy and light traffic, we respectively use this model to simulate the actual segment of the road and find that when the traffic is heavy, the rule hinder the further increase in traffic. For this reason, we make further improvements to the model to obtain a fluid traffic model based on no passing and find that the improved model makes traffic flow increase significantly. Then, the improved model is applied to the light traffic, we find there are no significant changes in traffic flow .In this regard we propose a new rule: when the traffic is light, passing is allowed, but when the traffic is heavy, passing is not allowed.

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27

Wang, Zhan, and Shu Wu. "Research on GRNN Model for Short-Term Air Traffic Flow Management." Applied Mechanics and Materials 263-266 (December 2012): 3244–49. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.3244.

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For the exigent requirement of short-term air traffic flow optimized dispatching, this paper analyzes dynamic behavior and network flow algorithm of short-term air traffic flow management, presents evacuation based ST-TFMP dynamic network flow algorithm, builds ST-TFMP GRNN model. The model is verified by simulation experiment, the results show it is feasible. The model improves precision of short-term air traffic flow management, saves time and cost, and it also actualizes the intelligence short-term air traffic flow management.

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Wang, Liang, Yu Jie Wang, and Ling Yu Wang. "Simulation Research of Flow and Speed on Urban Expressway Interchange Entrance." Advanced Materials Research 779-780 (September 2013): 796–99. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.796.

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The urban expressway overpass entrance is an important node of the urban road system. Traffic jams often happen at entrance. The characteristics of urban expressway entrance and the advantages of the microscopic traffic simulation were combined to analyze capacity of entrance. VISSIM simulation software was used and the validity of the simulation model was verified. The influence of the main road traffic flow and the desired speed of entrance to flow and speed of the urban expressway entrance were analyzed through simulation experiment. On the whole, traffic capacity of urban expressway entrance reduces with the increase of traffic flow on the main road. The higher the desired speed is, the faster traffic capacity reduces. The increase of speed and control of main road traffic flow is of great significance for improving the capacity and service level of expressway.

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Dong, Peng, Xifu Wang, Lifen Yun, and Hongqiang Fan. "Research on the characteristics of mixed traffic flow based on an improved bicycle model." SIMULATION 94, no. 5 (October 30, 2017): 451–62. http://dx.doi.org/10.1177/0037549717736947.

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Mixed traffic flow is a main feature of urban traffic in developing countries. Mixed bicycle flow includes human-powered and electric-powered bicycles and plays an important role in this mixed traffic flow. In mixed bicycle flow, cyclist behavior is flexible and variable. Cyclists move arbitrarily in the road and may influence the vehicle flow at intersections. Therefore, we first propose an improved bicycle model that can reproduce the main features of cyclist behavior, such as overtaking and self-protection. Then a simulation model based on the improved bicycle model is proposed to research the characteristics of mixed traffic flow in intersections. The conflict avoidance rules are then applied in the simulation model to eliminate traffic accidents. The simulation results indicate that the improved bicycle model is practical and that the density–velocity diagram of bicycle flow is similar to real traffic data. The existence of bicycle flow decreases vehicle velocity and worsens traffic flow in mixed traffic flow. However, the influence of bicycle flow might disappear at a particular vehicle density.

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30

van Wageningen-Kessels, Femke, Hans van Lint, Kees Vuik, and Serge Hoogendoorn. "Genealogy of traffic flow models." EURO Journal on Transportation and Logistics 4, no. 4 (April 2, 2014): 445–73. http://dx.doi.org/10.1007/s13676-014-0045-5.

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31

Yang, Zhi Wei. "The Research on the Traffic Rules of Freeways." Advanced Materials Research 926-930 (May 2014): 4154–57. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.4154.

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In this paper, a study of freeway traffic rules, respectively, from the traffic flow and road safety performance provides a theoretical basis for the establishment of a more rational road rules. First, we set up an appraisal system of the traffic flow which describes the flow from the average speed, the traffic density, the overtaking rate. And we calculate them separately. Meanwhile, by fitting, we can obtain the relationship between the traffic flow and the overtaking ratio. Then, an evaluation system of the safety is established which is based on the IHSDM (the evaluation model for highway safety). We can use it to get the conclusion that when the difference between the speeds of running vehicles is greater, the corresponding accident rate is higher. And the rate has a direct response to the road safety performance. Also, we combine the overtaking model to explore the safety performance in different road rules. Finally, in the case of different traffic rules, we can get a comprehensive of the model.

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Boyarshinov, M. G., A. S. Vavilin, and E. V. Vaskina. "APPLICATION OF THE WAVELET ANALYSIS TO RESEARCH THE TRAFFIC FLOW INTENSITY." Intelligence. Innovations. Investment, no. 4 (2022): 88–103. http://dx.doi.org/10.25198/2077-7175-2022-4-88.

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The relevance of the work is the specific properties of the wavelet analysis, which make it possible to identify not only the amplitude-scale (frequency) characteristics of the time series under consideration, but also the evolution of these characteristics during the observation time. As a result of the study, it is advisable to identify those indicators of the intensity of traffic flow that may turn out to be indicators of possible problematic situations (congestion, traffic accidents, etc.). It is advisable to use them in the future when regulating and controlling traffic on the basis of processing information about traffic flows that comes from stationary video recording complexes of traffic violations. The object of study is a road with intensive one-way traffic, equipped with a software and hardware complex that allows measuring the characteristics of the flow of motor transport. The subject of the study is the daily intensity of the flow of cars. The purpose of this study is to identify patterns in the indicators evolution obtained using wavelet analysis as a result of processing of the time series of the car traffic intensity on the road network. As a theoretical and methodological approach, the wavelet transforms using the MHat wavelet, and the Morlet wavelet is used. The approach used by the authors allowed us to establish the correspondence of some characteristics obtained during the wavelet analysis with the evolution of the traffic flow intensity function during the daily observation time, which is the scientific novelty of the study. The wavelet analysis of the data of the video surveillance software and hardware complexes obtained during the day allowed us to construct time dependences of amplitude-scale (frequency) indicators of the car traffic intensity on the road connecting the central and rear areas of the city of Perm. As a result of the study of time series, experimental three-dimensional distributions of wavelet images, scalograms, skeletons and scalegrams of the function of the daily intensity of the traffic flow were obtained. An explanation of the characteristic features of the obtained dependencies and their relationship with the initial function of the traffic flow intensity is proposed. The practical significance lies in obtaining amplitude-scale (frequency) characteristics as a result of wavelet analysis of the traffic intensity using MHat and Morlet wavelets, which is of practical interest from the point of view of predicting the movement of vehicles, controlling the operation of traffic lights, monitoring the operation of equipment, etc. The direction of further research is to obtain, process, analyze and generalize the results of performing amplitude-scale wavelet analysis for time series of traffic flow intensity on parts of the road network with different vehicle traffic intensity.

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Cao, Jin Xin, and Xiao Han Liu. "Research on the Equilibrium Speed-Density Relationship Around Flyover Work Zone." PROMET - Traffic&Transportation 28, no. 3 (July 1, 2016): 277–89. http://dx.doi.org/10.7307/ptt.v28i3.1892.

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Increasing traffic demand has already reached the capacity of existing traffic facilities in most cities. In order to alleviate the traffic pressure and expand the capacity of the road network, constructing flyovers has become an effective way in most cities in China. During the period of the flyover construction, work zones occupy road space, impact traffic flow characteristics and driver behaviour; therefore, this causes a significant reduction of the capacity. Researching of the traffic flow characteristics during the period of flyover construction can improve traffic organization and traffic safety around work zones. This study analyses the traffic flow characteristics around the flyover work zone based on the site data collected in Hohhot City, China. This study shows that the traditional Logistic model for the equilibrium speed-density relationship is not applied to the traffic flow around the flyover work zone. Based on an in-depth analysis of the traffic flow characteristics and specific driver behaviours, this paper proposes an improved Logistic model to depict the equilibrium speed-density relationship around the flyover work zone. To analyse the mathematical characteristics of the speed-density relationship, this paper proposes a method to insert virtual data points into the initial data, which can make the fit curve be continuous.

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Yang, Zhaosheng, Qichun Bing, Ciyun Lin, Nan Yang, and Duo Mei. "Research on Short-Term Traffic Flow Prediction Method Based on Similarity Search of Time Series." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/184632.

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Short-time traffic flow prediction is necessary for advanced traffic management system (ATMS) and advanced traveler information system (ATIS). In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of prediction model are determined through searching similar time series. Finally, the echo state networks model is used for traffic flow multistep prediction. The performance of the proposed method is measured with expressway traffic flow data collected from loop detectors in Shanghai, China. The experimental results demonstrate that the proposed method can achieve better multistep prediction performance than conventional methods.

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35

Hoogendoorn, Serge P., and Piet H. L. Bovy. "Continuum modeling of multiclass traffic flow." Transportation Research Part B: Methodological 34, no. 2 (February 2000): 123–46. http://dx.doi.org/10.1016/s0191-2615(99)00017-x.

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36

Zhang, Yan Min, Hai Bing Luo, and Jian Qiang Wang. "Research on Strategy Intelligent Control of Traffic Signal." Applied Mechanics and Materials 713-715 (January 2015): 889–92. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.889.

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In order to make the traffic flow smoothly through the intersection, to minimize the delay time, must ensure that the control decision of the traffic signal is real-time and accuracy. Aiming at the existing problems of the traditional timing control method, analysis of traffic signal control parameters, performance indicators, put forward the fuzzy inference is applied to the traffic signal control system, puts forward an intelligent traffic signal control system based on fuzzy control; the vehicle queue length, inlet flow rate, green extension as the control parameters and simulation the results show that the proposed control method can effectively improve the traffic congestion, improve the vehicle capacity.

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Zhang, Wen Bin, Bo Wang, and Harrod Genesis. "Research on the Improvement Schemes of Irregular Intersection." Applied Mechanics and Materials 253-255 (December 2012): 1971–75. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1971.

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In order to make the traffic flow more stability and smoothly at irregular intersection, the improvement schemes is researched on a typical irregular intersection, Hao valley intersection in Wuhan. Firstly, a field investigation is carried out for this intersection. Secondly, we carried on the optimization in many different ways, such as transportation demand management, traffic flow organization of regional, signal optimization, intersection Canalization and other optimizations. Finally, a microscopic traffic flow simulation software, VISSIM, is used to simulate the traffic situation before and after improvement. Results shows the improvement schemes effect is obviously, and the delay and conflicts substantially reduced. This research can provide a reference for similar intersection improvements.

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Zhang, H. M. "Driver memory, traffic viscosity and a viscous vehicular traffic flow model." Transportation Research Part B: Methodological 37, no. 1 (January 2003): 27–41. http://dx.doi.org/10.1016/s0191-2615(01)00043-1.

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39

Radović, Dunja, and Vuk Bogdanović. "Research of time headways at roundabout approaches." Put i saobraćaj 67, no. 3 (October 3, 2021): 23–28. http://dx.doi.org/10.31075/pis.67.03.04.

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It is known that traffic flow characteristics have significant influence at the capacity of all functional segments of the road and street network. One of the most important traffic flow parameters which affect the capacity of roundabouts is follow-up headway at minor approaches of roundabouts. This traffic flow parameter, like the most others, depends on driver behaviour, i.e. local traffic conditions. This paper presents the research results related to follow-up headway at three roundabouts obtained by the photographic method. This data collection method is chosen because its application completely eliminates the impact of research at behaviour of traffic participants. After the research, a representative sample is formed and its processing and analysis led to conclusions about the value of follow-up headway at roundabouts which can be applied in standard procedures for capacity calculation at roundabouts in midsize cities of our region.

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Qi, Bo, Chang Xi Ma, and Li Sun. "Research on Dynamic Traffic Flow Forecasting Based on Improved Particle Swarm Optimization Algorithm and Neural Network Theory." Applied Mechanics and Materials 178-181 (May 2012): 2686–89. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2686.

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Focused on urban traffic flow issue, the dynamic traffic flow forecasting model is established based on the improved particle optimization algorithm and nerve network theory. Taking the macro dynamic traffic flow as the model, the paper analyzes primarily the features of traffic flow by means of stage-distinguishing method, researches the improved particle optimization algorithm and nerve network theory further and establishes the dynamic traffic flow forecasting model. Finally, it utilizes this model to forecast the traffic flow on North Binghe Road in Lanzhou City. All the results demonstrate that this forecasting model is of higher prestige and proper availability.

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41

Clark, S. D., and S. A. Smulders. "Control of Freeway Traffic Flow." Journal of the Operational Research Society 48, no. 4 (April 1997): 450. http://dx.doi.org/10.2307/3010275.

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Smulders, S. A. "Control of Freeway Traffic Flow." Journal of the Operational Research Society 48, no. 4 (April 1997): 450. http://dx.doi.org/10.1057/palgrave.jors.2600492.

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Mao, He, and Xiu Hua Xu. "Research on Second Ring Expressway Traffic Congestion in Beijing." Applied Mechanics and Materials 409-410 (September 2013): 1339–42. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1339.

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According to the urban expressway traffic congestion of Beijing, from the perspective of traffic flow, the study makes a calculation and analysis on road network congestion rate, load of road network and traffic operation index. Training the traffic congestion and load of road network by using the BP neutral network in MATLAB, and put forward some countermeasures to solve the problem of traffic congestion. Through analyzing the load of different section and congestion rate, we can obtain the spatial distribution of the traffic flow and grasp the overall traffic on the Ring Road running load, develop appropriate management control programs for traffic managers, provide service and travel mode for travelers at the same time, so that balance the overall network load tends.

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Wang, Ran, Jian Bo Xiao, Hao Zhang, Yu Ying Tan, Ming An Ni, Yang Liu, Zhi Fu Zhang, and Xi Ling Xie. "Intelligent Optimization Consider Hour Traffic Flow Traffic Lights Working Condition." Advanced Materials Research 655-657 (January 2013): 1410–14. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1410.

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We design an intelligent optimization system about the response of a traffic signal response, based on a research on traffic at various periods of Wuhan. Fedded traffic flow on the road monitored back to the SCM control system. On the basis of the existing traffic control devices, produce a new intelligent traffic lights according to the traffic flow to change the access time. And optimize the design through modeling and calculation. After simulation, the system significantly reduces the waiting time of the automobile, relieves the burden of traffic at its peak, and eases the pressure on energy and the environment.

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Song, Zan, and Qing Ye. "Research and Design of Road Traffic Flow Detection System." Advanced Materials Research 945-949 (June 2014): 3291–95. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.3291.

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A road traffic flow detection system is designed based on induction loop, and the control platform is constructed based on the most advanced 32-bit ARM processor and CPLD. The systems hardware framework and software design process are introduced in this paper. The defects of traditional system such as deficient processing capacity and low measurement accuracy are overcome. In this system the data of the frequency change caused by the vehicles through the coil is collected, and the function of vehicles type classification in real-time is added, which is a great improvement compared to traditional induction loop detection system of vehicles.

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Liu, Shuying, Zequn Fang, and Li Zhang. "Research on Urban Short-term Traffic Flow Forecasting Model." Journal of Physics: Conference Series 1237 (June 2019): 052026. http://dx.doi.org/10.1088/1742-6596/1237/5/052026.

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47

Konkina, A. S. "Numerical Research of the Mathematical Model for Traffic Flow." Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software" 12, no. 4 (2019): 128–34. http://dx.doi.org/10.14529/mmp190411.

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Yu, Zhiheng, Tieli Sun, Hongguang Sun, and Fengqin Yang. "Research on Combinational Forecast Models for the Traffic Flow." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/201686.

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In order to improve the prediction accuracy of the traffic flow, this paper proposes two combinational forecast models based on GM, ARIMA, and GRNN. Firstly, the paper proposes the concept of associate-forecast and the weight distribution method based on reciprocal absolute percentage error and then uses GM(1,1), ARIMA, and GRNN to establish a combinational model of highway traffic flow according to the fixed weight coefficients. Then the paper proposes the use of neural networks to determine variable weight coefficients and establishes Elman combinational forecast model based on GM(1,1), ARIMA, and GRNN, which achieves the integration of these three individuals. Lastly, these two combinational models are applied to highway traffic flow on Chongzun of China and the experimental results verify their effectiveness compared with GM(1,1), ARIMA, and GRNN.

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Luhang, Xu. "The Research of Data Mining in Traffic Flow Data." International Journal of Database Theory and Application 8, no. 4 (August 30, 2015): 19–30. http://dx.doi.org/10.14257/ijdta.2015.8.4.03.

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50

Boyarshinov, M. G., A. S. Vavilin, and E. V. Vaskina. "APPLICATION OF THE HURST INDEX TO RESEARCH THE TRAFFIC FLOW INTENSITY." Intelligence. Innovations. Investment, no. 2 (2022): 68–81. http://dx.doi.org/10.25198/2077-7175-2022-2-68.

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Abstract. The relevance of the work is due to the predictive properties of the Hurst indicator (index), which make it possible to identify the presence/absence of a trend in the observed stochastic process, which it is advisable to use when regulating and controlling traffic to reduce congestion, traffic accidents based on processing information about traffic flows coming from stationary video recording complexes of traffic violations. The object of investigation is a section of road with intensive one-way traffic, equipped with a software and hardware complex that allows measuring the characteristics of the flow of motor transport. The subject of the study is the daily intensity of the cars flow during the week, from Monday to Sunday. The purpose of this study is to identify the patterns of evolution of the indicators included in the Hurst index, based on the processing of time series of the intensity of motor transport traffic on the road network. As a theoretical and methodological approach, the rescaled range analysis, or the definition of Hurst exponent, is used. The approach developed by the authors allowed us to establish the regularities of the evolution of mean values, standard deviations, accumulated and rescaled range, Hearst exponents, which is the scientific novelty of the performed analysis. Data processing of video surveillance software and hardware complexes made it possible to construct time-dependent indicators of the intensity of car traffic on a road with a consistently high flow of vehicles connecting the central and remote areas of the city of Perm, at various intervals of averaging by days of the week. As a result of the study of time series, dependences on the time of average values, standard deviations, accumulated and rescaled ranges, Hearst exponents were obtained. It is shown that the found characteristics of the traffic flow intensity on a road with a high traffic intensity differ significantly from similar characteristics obtained earlier for roads with a relatively low intensity. The practical significance lies in the use of predictive properties of the Hurst indicator in analyzing the intensity of the flow of vehicles for predicting the movement of vehicles, controlling the operation of traffic lights, monitoring the operation of equipment, etc. The direction of further research is to obtain, process and determine rescaled ranges and Hurst exponents for time series of traffic flow intensity on other sections of the road network.

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