scholarly journals Evaluation of ACC Vehicles in Mixed Traffic: Lane Change Effects and Sensitivity Analysis

2005 ◽  
Vol 6 (1) ◽  
pp. 79-89 ◽  
Author(s):  
P.A. Ioannou ◽  
M. Stefanovic
Keyword(s):  
Sensitivity Analysis ◽  
Lane Change ◽  
Mixed Traffic ◽  
Traffic Lane

Cellular Automata–Based Modeling and Simulation of a Mixed Traffic Flow of Manual and Automated Vehicles

2017 ◽  
Vol 2622 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Da Yang ◽  
Xiaoping Qiu ◽  
Lina Ma ◽  
Danhong Wu ◽  
Liling Zhu ◽  
...  
Keyword(s):  
Reaction Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Lane Change ◽  
Mixed Traffic ◽  
Automated Vehicles ◽  
Obvious Effect ◽  
Mixed Traffic Flow ◽  
Automated Vehicle

In recent years, automated vehicles have been developing rapidly, and some automated vehicles have begun to drive on highways. The market share of automated vehicles is expected to increase and will greatly affect traffic flow characteristics. This paper focuses on the mixed traffic flow of manual and automated vehicles. The study improves the existing cellular automaton model to capture the differences between manual vehicles and automated vehicles. Computer simulations are employed to analyze the characteristic variations in the mixed traffic flow under different automated vehicle proportions, lane change probabilities, and reaction times. Several new conclusions are drawn in the paper. First, with the increment of the proportion of automated vehicles, freeway capacity increases; the capacity increment is more significant for single-lane traffic than for two-lane traffic. Second, for single-lane traffic flow, reducing the reaction time of the automated vehicle can significantly improve road traffic capacity—as much as doubling it—and reaction time reduction has no obvious effect on the capacity of the two-lane traffic. Third, with the proportion increment of automated vehicles, lane change frequency reduces significantly. Fourth, when the density is 15 < ρ < 55 vehicles/km, the addition of 20% automated vehicles to a traffic flow that consisted of only manual vehicles can decrease congestion by up to 16.7%.

scholarly journals Human-Like Lane Change Decision Model for Autonomous Vehicles that Considers the Risk Perception of Drivers in Mixed Traffic

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2259 ◽  
Author(s):  
Chang Wang ◽  
Qinyu Sun ◽  
Zhen Li ◽  
Hongjia Zhang
Keyword(s):  
Risk Perception ◽  
Autonomous Vehicles ◽  
Decision Model ◽  
Signal Detection Theory ◽  
Critical Issue ◽  
Lane Change ◽  
Mixed Traffic ◽  
Driving System ◽  
Lane Changes ◽  
The Subject

Determining an appropriate time to execute a lane change is a critical issue for the development of Autonomous Vehicles (AVs).However, few studies have considered the rear and the front vehicle-driver’s risk perception while developing a human-like lane-change decision model. This paper aims to develop a lane-change decision model for AVs and to identify a two level threshold that conforms to a driver’s perception of the ability to safely change lanes with a rear vehicle approaching fast. Based on the signal detection theory and extreme moment trials on a real highway, two thresholds of safe lane change were determined with consideration of risk perception of the rear and the subject vehicle drivers, respectively. The rear vehicle’s Minimum Safe Deceleration (MSD) during the lane change maneuver of the subject vehicle was selected as the lane change safety indicator, and was calculated using the proposed human-like lane-change decision model. The results showed that, compared with the driver in the front extreme moment trial, the driver in the rear extreme moment trial is more conservative during the lane change process. To meet the safety expectations of the subject and rear vehicle drivers, the primary and secondary safe thresholds were determined to be 0.85 m/s2 and 1.76 m/s2, respectively. The decision model can help make AVs safer and more polite during lane changes, as it not only improves acceptance of the intelligent driving system, but also further ensures the rear vehicle’s driver’s safety.

Sensitivity Analysis of Vehicle Parameters for Heading Angle Control of an Unmanned Ground Vehicle

2014 ◽  
Author(s):  
Shubhashisa Sahoo ◽  
Shankar C. Subramanian ◽  
Suresh Srivastava
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Dynamic Performance ◽  
Measurement Unit ◽  
Lane Change ◽  
Actual System ◽  
Magic Formula ◽  
Actuator Dynamics ◽  
Wide Range ◽  
Heading Angle

Even if there are many software and mathematical models available in the literature to analyze the dynamic performance of Unmanned Ground Vehicles (UGVs), it is always difficult to identify or collect the required vehicle parameters from the vehicle manufacturer for simulation. In analyzing the vehicle handling performance, a difficult and complex task is to use an appropriate tire model that can accurately characterize the ground-wheel interaction. Though, the well-known ‘Magic Formula’ is widely used for this purpose, it requires expensive test equipment to estimate the Magic Formula coefficients. The design of longitudinal and lateral controllers plays a significant role in path tracking of an UGV. Though the speed of the vehicle may remain almost constant in most of the maneuvers such as lane change, Double Lane Change (DLC), step steer, cornering, etc., design of the lateral controller is always a challenging task as it depends on the vehicle parameters, road information and also on the steering actuator dynamics. Although a mathematical model is an abstraction of the actual system, the controller is designed based on this model and then deployed on the real system. In this paper, a realistic mathematical model of the vehicle considering the steering actuator dynamics has been developed by calculating the cornering stiffnesses from the basic tire information and the vertical load on each tire. A heading angle controller of the UGV has been considered using the Point-to-Point navigation algorithm. Then, these controllers have been implemented on a test platform equipped with an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). A wide range of experiments such as J-Turn, lane change and DLC have also been conducted for comparison with the simulation results. Sensitivity analysis has been carried out to check the robustness and stability of the controller by varying the cornering stiffness of tires, the most uncertain parameter. The longitudinal speed of the vehicle is assumed to vary between a minimum value of 1.4 m/s and a maximum value of 20 m/s. It has been found that when the vehicle is moving at a constant velocity of 3.2 m/s, a heading angle change of 20 degrees can be achieved within 3 seconds with 2% steady state error using a proportional controller. It was observed that at lower speeds, the controller is more sensitive to the steering actuator dynamics and at higher speeds, the controller is more sensitive to the cornering stiffness of tires.

scholarly journals Applying Machine Learning to Develop Lane Control Principles for Mixed Traffic

2021 ◽  
Vol 13 (14) ◽  
pp. 7656
Author(s):  
Tien-Pen Hsu ◽  
Ku-Lin Wen ◽  
Taiyi Zhang
Keyword(s):  
Regression Tree ◽  
Control Policy ◽  
Classification And Regression Tree ◽  
Mixed Traffic ◽  
Practical Applications ◽  
Traffic Lane ◽  
Before And After ◽  
Accident Data ◽  
Equivalent Property ◽  
Road Segments

The mixed traffic environment often has high accident rates. Therefore, many motorcycle-related traffic improvements or control methods are employed in countries with mixed traffic, including slow-traffic lanes, motorcycle two-stage left turn areas, and motorcycle waiting zones. In Taiwan, motorcycles can ride in only the two outermost lanes, including the curb lane and a mixed traffic lane. This study analyzed the new motorcycle-riding space control policy on 27 major arterial roads containing 248 road segments in Taipei by analyzing before-and-after accident data from the years 2012–2018. In this study, the equivalent-property-damage-only (EPDO) method was used to evaluate the severity of crashes before and after the cancelation of the third lane prohibition of motorcycles (TLPM) policy. After EPDO analysis, the random forest analysis method was used to screen the crucial factors in accidents for specific road segments. Finally, a classification and regression tree (CART) was created to predict the accident improvement effects of the road segments with discontinued TLPM in different situations. Furthermore, to provide practical applications, this study integrated the CART results and the needs of traffic authorities to determine four rules for canceling TLPM. In the future, on the accident-prone road segment with TLPM, the inspection of the four rules can provide the authority to decide whether to cancel TLPM to improve the accident or not.

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.

scholarly journals Cellular Automata Model for Mixed Traffic Flow with Lane Changing Behavior

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Devaraj Hanumappa ◽  
Parthasarathy Ramachandran
Keyword(s):  
Cellular Automata ◽  
Cell System ◽  
Flow Density ◽  
Lane Change ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Change Behavior ◽  
Traffic Stream ◽  
Lane Width ◽  
Indian Cities

Indian cities are seen with predominantly mixed traffic plying on the streets. Modeling the mixed traffic involving vehicles characterised of different speed, length, and width is a challenging issue. Based on the finer cell system of cellular automata (CA) models, this paper proposes to evaluate the mixed traffic behavior with cars and motorcycles for intermediate lane width, which is more common in Indian cities. The maximum car flow is observed (even with the presence of motorcycles) in the results which is higher than the Na-Sch model for cars. This increase is mainly due to the changing behavior. The car flow decreases as the density of the motorcycle increases. Furthermore, the paper proposes to evaluate the effect of lane change behavior on the speed and flow of the traffic stream using the fundamental diagrams of speed flow density curves. The simulation result suggests that lane change probability has little effect on the speed and flow of the traffic stream.

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