Study of traffic flow characteristics using different vehicle-following models under mixed traffic conditions

2016 ◽  
Vol 10 (2) ◽  
pp. 92-103 ◽  
Author(s):  
Gowri Asaithambi ◽  
Venkatesan Kanagaraj ◽  
Karthik K. Srinivasan ◽  
R. Sivanandan
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Mixed Traffic ◽  
Traffic Conditions ◽  
Traffic Flow Characteristics

TRAFFIC DYNAMICS IN A TWO-LANE MIXED TRAFFIC SYSTEM: EFFECT OF FOUR LANE CHANGING REGULATIONS

2008 ◽  
Vol 19 (11) ◽  
pp. 1705-1715 ◽  
Author(s):  
WEI-WEI ZHANG ◽  
RUI JIANG ◽  
YAO-MING YUAN ◽  
QING-SONG WU
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Flow Characteristics ◽  
Mixed Traffic ◽  
Traffic Dynamics ◽  
System Effect ◽  
Lane Changing ◽  
Traffic System ◽  
Mixed Traffic Flow ◽  
Traffic Flow Characteristics

This paper investigates traffic dynamics of two-lane mixed traffic flow system composed of cars and buses, which are characterized by different lengths and different maximum velocities. Four lane changing regulations are studied, which reveals effect of lane changing ban, symmetric and asymmetric lane changing rules on traffic flow characteristics (flow rate, carry capability, lane changing frequency, and lane usage). We expect that our results could be useful for traffic management.

scholarly journals Capacity Estimation of Multilane Highways under Heterogeneous Traffic Conditions using Micro-Simulation Technique

2020 ◽  
Vol 12 (01) ◽  
pp. 20-25
Author(s):  
Tanumoy Ghosh ◽  
Sudip Kumar Roy ◽  
Subhamay Gangopadhyay
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Simulation Models ◽  
Heterogeneous Traffic ◽  
Traffic Condition ◽  
Traffic Conditions ◽  
Geometric Conditions ◽  
Micro Simulation ◽  
Traffic Flow Characteristics

The behavior of a driver of any vehicle is important in estimating heterogeneous traffic conditions with no strict lane discipline. In the present study, a micro-simulation model is used to analyze the mixed traffic condition with different drivers’ behavior parameters. The field data collected on traffic flow characteristics of multilane highways are used in the calibration and validation of the simulation model. Out of the ten coefficient of correlation (CC) parameters in the simulation model, five are used in the present study to make a model of simulation for heterogeneous traffic; the other five parameters are not considered for testing their influence on simulated capacity values as they represent very typical behavior of a driver, either in car-following, or in free-flow conditions. Two separate simulation models are made by changing the CC (CC0, CC1, CC2, CC7, and CC8) parameters, each for a four-lane divided and a six-lane divided highway as the geometric conditions of the roads and the traffic flow is different for both the cases. These models are then applied on two other sections of a four-lane divided and a six-lane divided highway to validate the parameters of the model developed earlier for other sections.

scholarly journals Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives

2021 ◽  
Vol 13 (19) ◽  
pp. 11052
Author(s):  
Mohammed Al-Turki ◽  
Nedal T. Ratrout ◽  
Syed Masiur Rahman ◽  
Imran Reza
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Flow Characteristics ◽  
Driving Behavior ◽  
Mixed Traffic ◽  
Traffic Characteristics ◽  
Traffic Environment ◽  
Traffic Flow Characteristics ◽  
The Impact

Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses on reviewing the expected impacts under a mixed traffic environment of AVs and regular vehicles (RVs) considering different AV characteristics. The paper includes a policy implication discussion for possible actual future practice and research interests. The AV implementation has positive impacts on the traffic flow, such as improved traffic capacity and stability. However, the impact depends on the factors including penetration rate of the AVs, characteristics, and operational settings of the AVs, traffic volume level, and human driving behavior. The critical penetration rate, which has a high potential to improve traffic characteristics, was higher than 40%. AV’s intelligent control of operational driving is a function of its operational settings, mainly car-following modeling. Different adjustments of these settings may improve some traffic flow parameters and may deteriorate others. The position and distribution of AVs and the type of their leading or following vehicles may play a role in maximizing their impacts.

scholarly journals Semi-Continuous Spatial Statistical Analysis Using AIS Data for Vessel Traffic Flow Characteristics in Fairway

2021 ◽  
Vol 9 (4) ◽  
pp. 378
Author(s):  
Jong Kwan Kim
Keyword(s):  
Statistical Analysis ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Automatic Identification ◽  
Identification System ◽  
Spatial Statistical Analysis ◽  
Traffic Characteristics ◽  
Traffic Distribution ◽  
Traffic Flow Characteristics ◽  
Marine Accidents

As high vessel traffic in fairways is likely to cause frequent marine accidents, understanding vessel traffic flow characteristics is necessary to prevent marine accidents in fairways. Therefore, this study conducted semi-continuous spatial statistical analysis tests (the normal distribution test, kurtosis test and skewness test) to understand vessel traffic flow characteristics. First, a vessel traffic survey was conducted in a designated area (Busan North Port) for seven days. The data were collected using an automatic identification system and subsequently converted using semi-continuous processing methods. Thereafter, the converted data were used to conduct three methods of spatial statistical analysis. The analysis results revealed the vessel traffic distribution and its characteristics, such as the degree of use and lateral positioning on the fairway based on the size of the vessel. In addition, the generalization of the results of this study along with that of further studies will aid in deriving the traffic characteristics of vessels on the fairway. Moreover, these characteristics will reduce maritime accidents on the fairway, in addition to establishing the foundation for research on autonomous ships.

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