Traffic States under Influence of Different Vehicle Types on Freeway with Two Unidirectional Lanes

2013 ◽  
Vol 361-363 ◽  
pp. 1885-1890
Author(s):  
Qiang Fu ◽  
Xiao Fang Yang
Keyword(s):  
Traffic Flow ◽  
Flow Condition ◽  
Field Survey ◽  
Dynamic Change ◽  
The Self ◽  
Level Of Service ◽  
Heavy Vehicle ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Vehicle Impact

The high proportion of heavy vehicles on Chinese freeway brings important effects to the operation of freeway and makes the traffic very complex. The exhibition and mechanic of the influence between different vehicle types vary under different traffic flow and heavy vehicle proportion. In this paper, field survey was carried out and the characteristic of Chinese mixed traffic was gotten. Based on the phenomenon observed in the field survey, models were built to analysis the mechanic of the influence between different vehicle types. The influence states were divided into four aspects according to different exhibition and mechanic, that is: free flow condition, independent heavy vehicle impact, heavy vehicles and cars in different lane, drive in disorder. The influence states will transfer with the temporary variation of traffic flow composition. It is result from the self-organizing behavior of vehicles which pursue higher speed and brings dynamic change of capacity and level of service in time and space.

scholarly journals EVALUATING THE EFFECT OF HEAVY VEHICLES ON TRAFFIC PARAMETERS BY USING HEAVY VEHICLE FACTOR

2018 ◽  
Vol 6 (4) ◽  
pp. 95-104
Author(s):  
Parthkumar Patel ◽  
H.R. Varia
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Freight Transport ◽  
Heavy Vehicle ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Highway Traffic ◽  
Ideal Situation ◽  
The Impact

Safe, convenient and timely transportation of goods and passengers is necessary for development of nation. After independence road traffic is increased manifold in India. Modal share of freight transport is shifted from Railway to roadways in India. Road infrastructures continuously increased from past few decades but there is still need for new roads to be build and more than three forth of the roads having mixed traffic plying on it. The impact of freight vehicles on highway traffic is enormous as they are moving with slow speeds. Nature of traffic flow is dependent on various traffic parameters such as speed, density, volume and travel time etc. As per ideal situation these traffic parameters should remain intact, but it is greatly affected by presence of heavy vehicle in mixed traffic due to Svehicles plying on two lane roads. Heavy vehicles affect the traffic flow because of their length and size and acceleration/deceleration characteristics.  This study is aimed to analyse the impact of heavy vehicles on traffic parameters.

Multi-Lane Lane-Changing Model under the Influence of Heavy Vehicles

2013 ◽  
Vol 838-841 ◽  
pp. 2117-2120
Author(s):  
Xiao Fang Yang ◽  
Jian Rong Wang ◽  
Xin Zhu Wang
Keyword(s):  
Traffic Flow ◽  
Empirical Data ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Lane Changing ◽  
Mixed Traffic Flow ◽  
Traffic Conditions ◽  
Preceding Vehicle

This paper presents a new lane-changing model of multi-lane mixed traffic flow. The influences of heavy vehicles on lane-changing are analyzed. An improved accumulated speed benefit model is proposed in which drivers generate lane-changing intentions based on accumulated speed benefit of preceding vehicle in target lane over the preceding vehicle in current lane, not just relative to the speed and desired speed of subject vehicle. Drivers may accelerate or decelerate during lane-changing due to different traffic conditions. Simulations show that with the increase in the proportion of heavy vehicles, lane changing frequency first increases and then decreases. The model is validated with empirical data.

scholarly journals Predicting the Collisions of Heavy Vehicle Drivers in Iran by Investigating the Effective Human Factors

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hossein Naderi ◽  
Habibollah Nassiri ◽  
Farnaz Zahedieh
Keyword(s):  
Human Factors ◽  
Structural Equation ◽  
Field Survey ◽  
Response Rate ◽  
Road Traffic ◽  
Equation Modeling ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Factors Affecting ◽  
Minimum Probability

Traffic collisions are one of the most important challenges threatening the general health of the world. Iran’s crash statistics demonstrate that approximately 16,500 people lose their lives every year due to road collisions. According to the traffic police of Iran, heavy vehicles (including trailers, trucks, and panel trucks) contributed to 20.5% of the fatal road traffic collisions in the year 2013. This highlights the need for devoting special attention to heavy vehicle drivers to further explore their driving characteristics. In this research, the effect of heavy vehicle drivers’ behavior on at-fault collisions over three years has been investigated with an innovative approach of structural equation modeling (SEM) and Bayesian Network (BN). The database utilized in this research was collected using a questionnaire. For this purpose, 474 heavy vehicle drivers have been questioned in the Parviz Khan Border Market, located on the border of Iran and Iraq. The response rate of the survey was 80%. The participants answered the questions on Driver Behavior Questionnaire (DBQ) and a sleep assessing questionnaire named Global Dissatisfaction with Sleep (GSD). In this research, human factors affecting at-fault collisions of heavy vehicles were identified and their relationships with other variables were determined using the SEM approach. Then the descriptive model constructed by the SEM method was used as the basis of the BN, and the conditional probabilities of each node in the BN were calculated by the database collected by the field survey. SEM indicates that other attributes including GSD, mobile usage, daily fatigue, exposure, and education level have an indirect relation with heavy vehicle drivers’ at-fault collisions. According to the BN, if there is no information about the characteristics of a heavy vehicle driver, the driver will likely have at least one collision during the next three years with the probability of 0.17. Also, it was indicated that the minimum probability of the at-fault collision occurrence for a heavy vehicle is 0.08.

Analysis and Validation of Surrogate Safety Measures by Types of Lead and Following Vehicles

2017 ◽  
Vol 2659 (1) ◽  
pp. 137-147 ◽  
Author(s):  
Peibo Zhao ◽  
Chris Lee
Keyword(s):  
Los Angeles ◽  
Traffic Flow ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Trajectory Data ◽  
Collision Risk ◽  
Safety Measures ◽  
Mixed Traffic Flow ◽  
Vehicle Trajectory ◽  
Surrogate Safety Measures

This study analyzed rear-end collision risk in a mixed traffic flow of cars and heavy vehicles on a freeway using two surrogate safety measures: time to collision (TTC) and postencroachment time (PET). The study estimated surrogate safety measures for types of lead and following vehicles (car or heavy vehicle) by using the individual vehicle trajectory data. The vehicle trajectory data were collected from a segment of the US-101 freeway in Los Angeles, California. It was found that the distributions of TTC and PET were significantly different between types of lead and following vehicles. Also, the mean values of TTC and PET were higher for heavy vehicles following cars than for cars following cars and for cars following heavy vehicles. The study also validated TTC by using the simulated traffic data for a few minutes before the time of crashes that occurred on a section of the Gardiner Expressway in Toronto, Ontario, Canada. It was found that TTC reflects higher collision risk in the time intervals closer to the crash time and it reflects higher collision risk for the crash case than for the noncrash case. The findings suggest that the difference in rear-end collision risk between types of vehicle pairs should be considered in safety assessment of mixed traffic flow of cars and heavy vehicles.

scholarly journals Performance Analysis of a Roundabout and a 3-leg Intersection Under Heterogeneous Traffic

2020 ◽  
Vol 9 (3) ◽  
pp. 354-359
Keyword(s):  
Video Recording ◽  
Heterogeneous Traffic ◽  
Operational Performance ◽  
Level Of Service ◽  
Unstable State ◽  
Heavy Vehicle ◽  
Traffic Data ◽  
Heavy Vehicles ◽  
Close Proximity ◽  
The City

This paper addresses the analysis of the operational performance of a roundabout and a 3-legged intersection located in quite a busy area of the Aligarh city. The city has an urban population of around 0.9 million people. The roundabout and 3-legged intersection are located in the close proximity of busy commercial areas and schools. Roundabout that has been taken under consideration is un-signalized and 3- legged intersection is priority controlled. The Current study has been undertaken analyze the operational execution of the two intersections and to pave the way for forthcoming investigations related to improvement of the intersections in the Aligarh District region. Traffic data was accumulated on weekdays during peak periods (5:30 pm to 6:30 pm). Video recording was taken in consideration to accomplish this task. The traffic was categorized in 3 classes; light vehicles, heavy vehicles and bicycles. To execute the evaluation of functioning performance of both intersections, SIDRA INTERSECTION software has been used. Results have shown that both the roundabout and 3-legged intersection are operating nearly at their maximum capacities and Level of Service (LOS) is not adequate for such amount of traffic influx into both the intersections. Volume to capacity (v/c) ratio has revealed that both the roundabout and 3-legged intersection are in an unstable state and roundabout condition is worse than the 3-legged intersection as the heavy vehicle volume influx is quite higher for the roundabout

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