scholarly journals Finding the Reasons for the Delay Time in a Highway by Analyzing the Travel Time, Delay Time and Traffic Flow Data

2020 ◽  
Vol 01 (03) ◽  
pp. 76-84
Author(s):  
T M Junaid Bashar ◽  
Md. Sabbir Hossain ◽  
Shah Istiaque
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Flow ◽  
Delay Time ◽  
Speed Limit ◽  
Flow Data ◽  
Running Time ◽  
Journey Time ◽  
The Road ◽  
Total Vehicle

The objectives of this study are to show a comparison among travel time, running time, delay in peak and off-peak hours on different days of a week, and reasons behind the delay time. Moving car observer method has been carried out to count the traffic flow, journey time, running time, and delay time. Total vehicle flow, and comparative vehicle flow during the peak hour and off-peak hour for workdays and weekend days were surveyed to show a relationship between delay time and traffic flow. As the traffic flow increases the delay time also will increase. To measure the reasons behind the delay time of Fulbarigate-Daulatpur road, spot speed study was done in two intersections of the road. The 15th percentile speed for Religate intersection road is 10 K.P.H. That means 85% of vehicles tends to go faster than 10 K.P.H. in this section. And hence vehicles with less than or equal 10 K.P.H. are responsible for increasing the delay time in this area. This speed limit should be prohibited in this section to reduce delay time and congestion. For the Mohosin More road intersection, the prohibited speed is also 10 K.P.H. Easy bike and Mahindra account for the congestion of these intersections and tend to stop in these intersections to collect passengers which creates unwanted queue in this study area. Controlling traffic flow at intersections can be a possible way to reduce the congestion rate of Fulbarigate-Daulatpur road.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

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.

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.

Exploring the Value of Traffic Flow Data in Bus Travel Time Prediction

2012 ◽  
Vol 138 (4) ◽  
pp. 436-446 ◽  
Author(s):  
Ehsan Mazloumi ◽  
Sara Moridpour ◽  
Graham Currie ◽  
Geoff Rose
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Flow Data ◽  
Travel Time Prediction ◽  
Time Prediction ◽  
Bus Travel Time

scholarly journals The Sensitifity and Elastisity Model Approch to The Probality of Wooden Boat Route Selection in Archipelago Area

2021 ◽  
Vol 328 ◽  
pp. 10004
Author(s):  
Bustamin S Marsaoly ◽  
Nurmaiyasa Marsaoly ◽  
Abdul Gaus
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Delay Time ◽  
Stated Preference ◽  
Linear Regression Analysis ◽  
Service Level ◽  
Route Selection ◽  
Travel Costs ◽  
The Cross ◽  
Selection Of

This study aims to analyze the effect of travel costs Wooden Boat, travel time, delay time and service frequency on the selection of wooden ship routes using the stated preference method. Two variables, dependent and independent variables were analyzed using linear regression analysis, correlation and sensitivity model. From the results of the sensitivity analysis, the travel cost of attribute variable is the most sensitive to the probability of route selection is travel time. The changes of travel time will changes the probability of choosing a route which relatively largerer than changes the other attributes. For the elasticity analysis of the model for each attribute resulted the probability of choosing route 2 is more sensitive than route 1. This is indicated by the cross elasticity value which is greater than the direct elasticity value. The direct elasticity values for the attributes of cost, travel time, delay time, and service level are -0.5248, - 0.1667, -0.0845, and 0.1182 respectively. Meanwhile, the cross-elasticity values for the attributes of cost, travel time, delay time, and service level are -0.6477, -0.3979, -0.2016, and 0.2821

scholarly journals A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Yiliang Zeng ◽  
Jinhui Lan ◽  
Bin Ran ◽  
Yaoliang Jiang
Keyword(s):  
Traffic Flow ◽  
Incomplete Data ◽  
Road Traffic ◽  
Flow Speed ◽  
State Assessment ◽  
Assessment System ◽  
Flow Data ◽  
The Road ◽  
Traffic State ◽  
Probe Vehicle

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

scholarly journals Time-of-day Control Double-Order Optimization of Traffic Safety and Data-Driven Intersections

2019 ◽  
Vol 16 (5) ◽  
pp. 870 ◽  
Author(s):  
Chen Xu ◽  
Decun Dong ◽  
Dongxiu Ou ◽  
Changxi Ma
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Optimization Model ◽  
Delay Time ◽  
Time Of Day ◽  
Data Driven ◽  
Flow Data ◽  
Total Flow ◽  
Flow Segmentation ◽  
Division Model

This paper proposes a novel two-order optimization model of the division of time-of-day control segmented points of road intersection to address the limitations of the randomness of artificial experience, avoid the complex multi-factor division calculation, and optimize the traditional model over traffic safety and data-driven methods. For the first-order optimization—that is, deep optimization of the model input data—we first increase the dimension of traditional traffic flow data by data-driven and traffic safety methods, and develop a vector quantity to represent the size, direction, and time frequency with conflict point traffic of the total traffic flow at a certain intersection for a period by introducing a 3D vector of intersection traffic flow. Then, a time-series segmentation algorithm is used to recurse the distance amongst adjacent vectors to obtain the initial scheme of segmented points, and the segmentation points are finally divided by the combination of the preliminary scheme. For the second-order optimization—that is, model adaptability analysis—the traffic flow data at intersections are subjected to standardised processing by five-number summary. The different traffic flow characteristics of the intersection are categorised by the K central point clustering algorithm of big data, and an applicability analysis of each type of intersection is conducted by using an innovated piecewise point division model. The actual traffic flow data of 155 intersections in Yuecheng District, Shaoxing, China, in 2016 are tested. Four types of intersections in the tested range are evaluated separately by the innovated piecewise point division model and the traditional total flow segmentation model on the basis of Synchro 7 simulation software. It is shown that when the innovated double-order optimization model is used in the intersection according to the ‘hump-type’ traffic flow characteristic, its control is more accurate and efficient than that of the traditional total flow segmentation model. The total delay time is reduced by approximately 5.6%. In particular, the delay time in the near-peak-flow buffer period is significantly reduced by approximately 17%. At the same time, the traffic accident rate has also dropped significantly, effectively improving traffic safety at intersections.

scholarly journals The Effect of Posted Speed Limit on the Dispersion of Traffic Flow Speed

2019 ◽  
Vol 11 (13) ◽  
pp. 3594 ◽  
Author(s):  
Chao Gao ◽  
Jinliang Xu ◽  
Qunshan Li ◽  
Jie Yang
Keyword(s):  
Traffic Flow ◽  
Flow Speed ◽  
Traffic Volume ◽  
Free Flow ◽  
Speed Limit ◽  
Flow State ◽  
Speed Limits ◽  
Limit Values ◽  
Average Speed ◽  
The Road

Speed dispersion is an important indicator to portray the quality of traffic flow and is closely related to the road safety operation level. In order to clarify the influence of posted speed limits on the dispersion of traffic flow speed, three sections with speed limits of 80 km/h, 100 km/h and 120 km/h on the same expressway were selected for observation, and traffic volume, speed and other parameters were collected. The characteristic speeds, such as average speed, V15 and V85, were evaluation indicators, where V15 and V85 are the speeds of the 15th and 85th percentiles measured at the feature points of the road when the traffic is in a free-flow state and the weather is good. The relationship between different posted speed limit values and the above indicators was analyzed using the statistical analysis software, SPSS. The results show that the speed limit has a high correlation with the average speed of traffic flow, V15 and V85 in free-flow state, with the coefficient of determination being as high as 0.84, 0.85 and 0.92, respectively. In the restricted flow state, the factors affecting the driver’s driving speed are mainly the decrease in driving freedom caused by the increase of traffic volume rather than the speed limit value. In a free-flow state, when the posted speed limit is increased and the average speed and the V85 also increased by approximately the same magnitude. The posted speed limit values of 80 km/h, 100 km/h and 120 km/h correspond to the 90, 88 and 97 percentile speeds of the traffic flow, respectively. The higher the speed limit is, the larger the speed difference between V15 and V85 becomes. The results of the study are very useful for rationally determining the speed limit scheme under different traffic flows.

Reliability analysis of degradable networks with modified BPR

2017 ◽  
Vol 31 (36) ◽  
pp. 1750353 ◽  
Author(s):  
Yu-Qing Wang ◽  
Chao-Fan Zhou ◽  
Bin Jia ◽  
Hua-Bing Zhu
Keyword(s):  
Travel Time ◽  
Time Budget ◽  
Cumulative Distribution ◽  
Forced Flow ◽  
Probability Density Distribution ◽  
Speed Limit ◽  
The Road ◽  
The Mean ◽  
Travel Time Budget ◽  
Link Travel Time

In this paper, the effect of the speed limit on degradable networks with capacity restrictions and the forced flow is investigated. The link performance function considering the road capacity is proposed. Additionally, the probability density distribution and the cumulative distribution of link travel time are introduced in the degradable network. By the mean of distinguishing the value of the speed limit, four cases are discussed, respectively. Means and variances of link travel time and route one of the degradable road network are calculated. Besides, by the mean of performing numerical simulation experiments in a specific network, it is found that the speed limit strategy can reduce the travel time budget and mean travel time of link and route. Moreover, it reveals that the speed limit strategy can cut down variances of the travel time of networks to some extent.

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