Capacity of Unsignalized Intersections with Mixed Vehicle Flows

2003 ◽  
Vol 1852 (1) ◽  
pp. 265-270 ◽  
Author(s):  
Wenquan Li ◽  
Wei Wang ◽  
Dazhi Jiang
Keyword(s):  
Traffic Flow ◽  
Field Testing ◽  
Mixed Traffic ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Unsignalized Intersections ◽  
Capacity Theory ◽  
Capacity Model ◽  
Set Up ◽  
Gap Acceptance Theory

On the basis of gap-acceptance theory, mixed traffic flow composed of two representative vehicle types—heavy and light vehicles—is analyzed with probability theory. A capacity model is set up for an unsignalized intersection in which the minor-stream mixed traffic flows cross m major lanes and the traffic flow headways fit the M3 distribution; it is an extension of minor-lane capacity theory for one vehicle type and one major-stream traffic flow. A more complicated case with minor-stream flow composed of discretionary vehicle types is also considered, and the corresponding formula is given. After field testing in China, the conclusion is drawn that this model is better for analyzing Chinese traffic conditions than are other existing models.

scholarly journals Capacity Model for Single-Lane Minor Entry at Turbo-Roundabouts

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Andrea Kociánová
Keyword(s):  
Traffic Flow ◽  
Delay Model ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Mixed Traffic Flow ◽  
Traffic Lane ◽  
Unsignalized Intersections ◽  
Capacity Model ◽  
Traffic Volumes ◽  
The Right

Abstract Spirally arranged and physically separated traffic lanes in the circulatory carriageway of turbo-roundabouts force drivers to choose a particular entry lane and, subsequently, a circulatory traffic lane according to their intended destination. This specificity is taken into account in theoretical capacity models for two-lane turbo-roundabout entries typically evaluated by the lane-by-lane approach. Nevertheless, this specific path of movements is not considered in the most widely used capacity models for single-lane minor entries at oval turbo-roundabouts. In these models, only one entering traffic flow conflicted by two circulating traffic flows in front of the entry is considered. However, the entering traffic flow presents a mixed traffic flow of two movements (right-turning movement and left-turning and through movement) with different capacities due to different number of conflicting traffic streams and traffic volumes allocated into the outer and the inner circulatory lane. This fact is included in the capacity estimation for a single-lane minor entry presented in the article using the existing capacity formula for the mixed traffic flow on a shared minor lane at unsignalized intersections. The entry capacity reflects the proportion of the right-turning movement within a shared entry lane as well as the specific allocation of circulating traffic flow into the outer and the inner circulatory lane. This entry capacity is about 10 % to 30 % higher compared to a single-lane entry capacity estimated according to commonly used models described in the article. Higher entry capacity in a higher proportion of the right-turning traffic within mixed entry traffic flow is confirmed also by the results of average delays estimated by the theoretical delay model and microsimulation.

Capacity estimation of unsignalized intersections under heterogeneous traffic conditions

2020 ◽  
Vol 47 (6) ◽  
pp. 651-662
Author(s):  
Mithun Mohan ◽  
Satish Chandra
Keyword(s):  
Developing Countries ◽  
Developed Countries ◽  
Heterogeneous Traffic ◽  
Traffic Operations ◽  
Capacity Estimation ◽  
Traffic Conditions ◽  
Unsignalized Intersections ◽  
Capacity Model ◽  
Gap Acceptance Theory ◽  
Entire Procedure

Capacity of movements at unsignalized intersections are usually estimated based on gap acceptance theory and accuracy of such estimation largely depends on the extent to which its inherent assumptions are satisfied. However, owing to the typical traffic operations at intersections in developing countries, many of these assumptions remain unsatisfied and hence, estimating capacity as per the procedure laid down in the capacity manuals of developed countries will prove inaccurate. The present research focuses on developing the entire procedure for estimating the capacities of movements at unsignalized intersections dealing with heterogeneous traffic. This study is based on data collected from eight different unsignalized intersections located in various parts of India and by using Harders’ capacity model as base, the procedure to estimate the parameters of this model is revised to suit the traffic operations in developing countries and further modifies the Harders’ model using the movement capacities measured in the field.

scholarly journals Capacity of Unsignalized Intersections under Mixed Traffic Conditions

2011 ◽  
Vol 16 ◽  
pp. 676-685 ◽  
Author(s):  
Joewono Prasetijo ◽  
Mehdi Hossein Pour ◽  
Seyed Mohammad Reza Ghadiri
Keyword(s):  
Mixed Traffic ◽  
Traffic Conditions ◽  
Unsignalized Intersections

scholarly journals Capacity of Advance Right-Turn Motorized Vehicles at Signalized Intersections for Mixed Traffic Conditions

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Bing Li ◽  
Wei Cheng ◽  
Yiming Bie ◽  
Bin Sun
Keyword(s):  
Arrival Rate ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Capacity Model ◽  
Conflict Zone ◽  
Traffic Conflict ◽  
Motorized Vehicles ◽  
The Relationship ◽  
Gap Acceptance Theory

Right-turn motorized vehicles turn right using channelized islands, which are used to improve the capacity of intersections. For ease of description, these kinds of right-turn motorized vehicles are called advance right-turn motorized vehicles (ARTMVs) in this paper. The authors analyzed four aspects of traffic conflict involving ARTMVs with other forms of traffic flow. A capacity model of ARTMVs is presented here using shockwave theory and gap acceptance theory. The proposed capacity model was validated by comparison to the results of the observations based on data collected at a single intersection with channelized islands in Kunming, the Highway Capacity Manual (HCM) model and the VISSIM simulation model. To facilitate engineering applications, the relationship describing the capacity of the ARTMVs with reference to the distance between the conflict zone and the stop line and the relationship describing the capacity of the ARTMVs with reference to the effective red time of the nonmotorized vehicles moving in the same direction were analyzed. The authors compared these results to the capacity of no advance right-turn motorized vehicles (NARTMVs). The results show that the capacity of the ARTMVs is more sensitive to the changes in the arrival rate of nonmotorized vehicles when the arrival rate of the nonmotorized vehicles is 500  (veh/h)~2000  (veh/h) than when the arrival rate is some other value. In addition, the capacity of NARTMVs is greater than the capacity of ARTMVs when the nonmotorized vehicles have a higher arrival rate.

scholarly journals Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks

2020 ◽  
Vol 2020 ◽  
pp. 1-22 ◽  
Author(s):  
Bhargav Naidu Matcha ◽  
Satesh Narayana Namasivayam ◽  
Mohammad Hosseini Fouladi ◽  
K. C. Ng ◽  
Sivakumar Sivanesan ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Mixed Traffic ◽  
Lane Changing ◽  
One Dimensional ◽  
Traffic Models ◽  
Car Following ◽  
Traffic Conditions ◽  
And Mathematics

The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.

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 Effect of vehicle composition and delay on roundabout capacity under mixed traffic conditions

2016 ◽  
Vol 40 (4) ◽  
pp. 7-14 ◽  
Author(s):  
Dodappaneni Abhigna ◽  
Sindhu Kondreddy ◽  
K. V. R. Ravi Shankar
Keyword(s):  
Simulation Model ◽  
Travel Time ◽  
Andhra Pradesh ◽  
Study Data ◽  
Mixed Traffic ◽  
Capacity Estimation ◽  
Traffic Conditions ◽  
Unsignalized Intersections ◽  
The World ◽  
Estimation Models

Roundabouts are replacing conventional unsignalized intersections in many parts of the world (Polus and Shmueli, 1997). Capacity estimation is necessary for designing a new roundabout, to analyze and improve the existing roundabout facilities. There are several methods to estimate the capacity of the roundabout, but most of them are for homogeneous lane based traffic conditions and not applicable for mixed traffic conditions. This study tries to find out the applicability of the existing methods to mixed traffic conditions, identify the effect of vehicle composition, travel time and delay on capacity. In this study, data was collected from two roundabouts located in Mysore, Karnataka and Rajahmundry, Andhra Pradesh in India. Capacities for both the roundabouts are calculated using the existing methods and compared. VISSIM simulation model has been developed and analyzed for different vehicle compositions scenarios. It was observed that vehicle composition of the traffic influences the roundabout capacity. Since the entry capacity of a roundabout varies significantly with the vehicle composition of the traffic at the roundabout, it is necessary to incorporate this factor into the existing capacity estimation models.

scholarly journals Estimating Lateral Placement and Lane Indiscipline of Urban Mixed Traffic in Developing Country: An ANN Assisted Approach

2020 ◽  
Author(s):  
Harish Kumar Saini ◽  
Subhadip Biswas
Keyword(s):  
Mixed Traffic ◽  
Static And Dynamic Characteristics ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Vehicle Category ◽  
Traffic Stream ◽  
The Subject ◽  
Potential Factors ◽  
Traffic Composition ◽  
Urban Mixed Traffic

Information of lateral placement and lane indiscipline are useful in simulation of a mixed traffic stream and identifying the distressed portion of a pavement. In spite of these utilities, inadequate investigation was made to estimate the lateral placement of vehicles under prevailing traffic conditions. In a typical mixed traffic situation, vehicles having different static and dynamic characteristics take any lateral gap across the carriageway left empty by other surrounding vehicles and move in an untidy manner. It leads to variation in lateral placement of vehicles governed by the subject vehicle type. This paper explores the potential factors that influence lateral placement of vehicles and presents an Artificial Neural Network based approach to quantify lateral placement and lane indiscipline in context of undivided urban roads. Further, sensitivity analysis revealed how different traffic parameters like traffic volume, traffic composition and directional split influence lateral placement and lane indiscipline of a vehicle category.

Application of Trajectory Data for Investigating Vehicle Behavior in Mixed Traffic Environment

2018 ◽  
Vol 2672 (43) ◽  
pp. 122-133 ◽  
Author(s):  
Narayana Raju ◽  
Pallav Kumar ◽  
Aayush Jain ◽  
Shriniwas S. Arkatkar ◽  
Gaurang Joshi
Keyword(s):  
Traffic Flow ◽  
Research Work ◽  
Driving Behavior ◽  
Video Data ◽  
Hysteresis Phenomenon ◽  
Mixed Traffic ◽  
Trajectory Data ◽  
Traffic Conditions ◽  
Micro Level ◽  
Flow States

The research work reported here investigates driving behavior under mixed traffic conditions on high-speed, multilane highways. With the involvement of multiple vehicle classes, high-resolution trajectory data is necessary for exploring vehicle-following, lateral movement, and seeping behavior under varying traffic flow states. An access-controlled, mid-block road section was selected for video data collection under varying traffic flow conditions. Using a semi-automated image processing tool, vehicular trajectory data was developed for three different traffic states. Micro-level behavior such as lateral placement of vehicles as a function of speed, instant responses, vehicle-following behavior, and hysteresis phenomenon were evaluated under different traffic flow states. It was found that lane-wise behavior degraded with increase in traffic volume and vehicles showed a propensity to move towards the median at low flow and towards the curb-side at moderate and heavy flows. Further, vehicle-following behavior was also investigated and it was found that with increase in flow level, vehicles are more inclined to mimic the leader vehicle’s behavior. In addition to following time, perceiving time of subject vehicle for different leading vehicles was also evaluated for different vehicle classes. From the analysis, it was inferred that smaller vehicles are switching their leader vehicles more often to escape from delay, resulting in less following and perceiving time and aggressive gap acceptance. The present research work reveals the need for high-quality, micro-level data for calibrating driving behavior models under mixed traffic conditions.

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