Straight Vehicles Research Articles

Study on Aerodynamic Characteristics Between Right Turning Vehicles and Straight Running Vehicles

The dynamic meshing technology in computational fluid dynamics (CFD) is used to simulate the transient overtaking process of right turning vehicles and straight running vehicles. The characteristic of flow field around the vehicle model and the variation trend of lateral force and yawing moment are obtained. The research shows that when the speed of the straight vehicle increases, its lateral force and the yawing moment of both vehicles increase, while the lateral force of the right turning vehicle increases first and then decreases; The turning radius of the right turning vehicle increases, the lateral force of the two vehicles and the yawing moment of the straight vehicle decrease linearly, and the yawing moment of the right turning vehicle increases linearly.

Game Algorithm of Intelligent Driving Vehicle Based on Left-Turn Scene of Crossroad Traffic Flow.

Vehicle networking and autonomous driving are hot areas of scientific research today, and they complement each other and play an important role in people's intelligent travel. Intelligent driving vehicle can enhance road safety, effectively reduce traffic flow and fuel consumption, and promote the overall social development. It has great application value in urban traffic system. The traffic condition of a city directly affects the economic development of the city and the improvement of people's quality of life. As the “core” of the urban traffic network, intersections are the frequent places where traffic jams occur. Game theory, as a win-win theory, mainly solves the problem of multiperson and multi-objective with contradictory objective functions and can be used to study the optimal signal control strategy. Aiming at this problem, the potential conflict behaviors of intelligent driving vehicles when turning left at urban intersections are analyzed and a decision model is established. A long-term trajectory prediction model of straight vehicles is established based on the Gaussian process regression model (GPR) considering the vehicle motion pattern. Combined with trajectory prediction, a decision-making process (model) for intelligent driving vehicles based on conflict resolution and a multifactor driving action selection method are proposed. A coordination algorithm based on game theory is designed for conflicting vehicles. The proposed algorithm is verified by the self-developed intelligent vehicle hardware simulation platform. The simulation results show that the PID method based on digital identification and positioning makes the intelligent vehicle obtain good system step response, can improve the disturbance tracking ability of intersection turning analysis, meet the requirements of turning control system, and reduce the complexity and randomness of parameter design, which is better than the traditional fuzzy control method.

Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network

To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme.

Reinforcement-Learning-Based Decision and Control for Autonomous Vehicle at Two-Way Single-Lane Unsignalized Intersection

Intersections have attracted wide attention owing to their complexity and high rate of traffic accidents. In the process of developing L3-and-above autonomous-driving techniques, it is necessary to solve problems in autonomous driving decisions and control at intersections. In this article, a decision-and-control method based on reinforcement learning and speed prediction is proposed to manage the conjunction of straight and turning vehicles at two-way single-lane unsignalized intersections. The key position of collision avoidance in the process of confluence is determined by establishing a road-geometry model, and on this basis, the expected speed of the straight vehicle that ensures passing safety is calculated. Then, a reinforcement-learning algorithm is employed to solve the decision-control problem of the straight vehicle, and the expected speed is optimized to direct the agent to learn and converge to the planned decision. Simulations were conducted to verify the performance of the proposed method, and the results show that the proposed method can generate proper decisions for the straight vehicle to pass the intersection while guaranteeing preferable safety and traffic efficiency.

Tandem Design of Bus Priority Based on a Pre-Signal System

Giving buses priority is an important measure to improve the attractiveness of public transport and to reduce urban traffic congestion. Reducing bus service delays as much as possible will have a positive impact on urban traffic. Based on the pre-signal system, a bus at an intersection with a left-turn special phase is optimized by “tandem design”. The design model is applied to the entrance of an intersection to study the process of vehicle arrival and departure at the main signal and pre-signal, and to calculate and analyze the delay changes of buses, straight social vehicles (meaning vehicles other than those required to be open to traffic) and left-turn vehicles before and after the adoption of “tandem design”. The results show that when the vehicle capacity at the intersection is saturated, the delays to buses and the delays of left-turn vehicles will be significantly reduced once the “tandem design” is adopted at the entrance of a cross intersection with a special left-turn phase. However, it has little effect on the delay of straight-on vehicles; with this system, the total delay experienced by straight vehicles will be reduced to one cycle.

Robust Dual Quadric Initialization for Forward-Translating Camera Movements

Herein, we present a novel approach for monocular dual quadric initialization that combines three-dimensional (3D) map points with two-dimensional (2D) object detection for forward-translating camera movements. The traditional approach using 2D detection bounding boxes in multiple views fails in straight vehicle motion scenarios as object observation is limited to few frames. Although single image initialization is possible when multiple constraints are introduced, such initialization is based on strong assumptions. In this letter, we incorporate constraints from 3D map points with single-view 2D object detection to robustly initialize the dual quadric. Constraints from 3D map points are converted to planar constraints from their convex hull. Together with the projective planar constraints from bounding boxes, the proposed method can infer accurate dual quadric parameters. Further, comparison studies with the state of the art (SOTA) show that the proposed approach achieves the same accuracy of center localization but outperforms the existing methods in shape estimation and success ratio of initialization. The proposed method dose not rely on assumptions of dimension and pose of 3D objects; hence, it is more generic and accurate. Based on the KITTI raw dataset, the initialization success ratio is up to 97.7% with an average position error of 1.58 m, and 2D IoU of 80% when the number of map points per object accumulates to 60. When applied to the TUM RGB-D dataset, the proposed approach yields an initialization success ratio of 92.7% when the number of map points per object accumulates to 30, revealing a 16.2% increment compared with the SOTA using an RGB-D camera. Finally, we integrate the initialization method into a simultaneous localization and mapping system.

Collision Risk Analysis of Design for Traffic Signal Phasing-Sequence at Signalized Intersection

To improve the traffic safety at the two-phase intersection, collision risk value between the left-turn vehicle and the straight vehicle in the opposite direction could be used to judge their order. Based on the safety and risk, this method analyzed the process of conflict, modified the operating parameters and then collision risk analysis model was proposed. In the paper, one practical example was given. The result shows that the method can be applied to design the signal phasing-sequence of traffic at signalized intersection, which not only improve safety theory but also provide the theoretical basis for security information service.

Game Theory Modelling for Vehicle U-Turn Behavior and Simulation Based on Cellular Automata

In order to analyze the effect of U-turn vehicle on traffic performance, the work develops a game theory-based description of drivers’ interactions in U-turn scene, considering the decision-making uncertainty. The hybrid strategy of the game is obtained. The relevant parameters of model are calibrated by collected video data in Changchun, China. A two-way four-lane cellular automaton model with the game model imbedded is constructed for identifying the effect of U-turn vehicle on traffic performance. The influencing factors are identified with their correlation analyzed by numerical simulation of different traffic conditions. According to the simulation results, U-turn traffic has a significant influence on traffic delay in the lane of same direction, compared with opposite direction. The severity of conflict between vehicles is classified and the causes are identified by analyzing the arrival rate of the U-turn vehicle and the conflicting straight vehicle and the relationship with one another. In addition, the threshold of traffic flow causing traffic conflict and traffic delay are proposed. The results show that the proposed models reconstructed the traits of traffic flow and conflict phenomenon in the presence of U-turn vehicles on road section.

Preempt or yield? An analysis of driver’s dynamic decision making at unsignalized intersections by classification tree

For developing countries and regions, due to less construction of stop signs and roundabouts, as well as limited regulation of driving courtesy, safety issues at unsignalized intersections require harder concern. In China, drivers rarely stop completely at unsignalized intersections, but gradually enter and dynamically make their decisions to yield or preempt by gaming with other vehicles. Wrong decisions made in this quick process often lead to accidents. In this study, we aimed to explore how straight drivers dynamically made decisions when encountered merging vehicles at unsignalized intersections in China. By video graphing traffic scenarios, 150 cases of merging traffic were selected at a 4-legged unsignalized intersection in Kunming City. Motion parameters of the vehicles were extracted from video detection software. By modeling the motion parameters to a classification tree, the decision moment of straight drivers’ yielding/preemptive decision and the motion parameters which influenced drivers’ decision significantly were identified. Results showed that straight drivers made yielding/preemptive decisions 1.3–1.5s before reaching the merging point. Speed difference between the straight vehicle and the turning vehicle was the most important factor to impact straight driver’s decision-making. Turning vehicle’s speed and distance to the merging point also impacted straight driver’s decision. Moreover, a U-shape curve was found when plotted the minimum gap between the two vehicles by the speed difference of the two vehicles at the decision moment (1.3s). The accurate motion parameters found in this study helped to develop driver’s thorough behavior model at unsignalized intersections, and suggest safety measures further.

Traffic Impact Analysis of Urban Intersections with Comprehensive Waiting Area on Urban Intersection based on PARAMICS

To improve the traffic operation and take advantage of the space resource, left-turn vehicles waiting area and straight vehicles waiting area are adopted separately at intersection at home and abroad, but there is not much research for using left-turn and straight waiting area together at the same intersection. Research using simulation software PARAMICS combining with programming API to simulate a specific comprehensive waiting area in Guangzhou city under nine different traffic volumes for three conditions: following control strategy, underutilizing control strategy and without control strategy. By evaluating the following four indexes: link delay, queue length, link average speed and passing vehicles, the simulation results indicate that the improving effect of following control strategy is superior to the underutilizing control strategy. Implementing comprehensive waiting area and in conjunction with the following control strategy can improve traffic operation when traffic volume is larger than the surveyed situation volume while the improvement is more effectively when traffic volume continues to increase. Setting comprehensive waiting area cannot improve intersection traffic operation but will worsen the traffic operation when traffic volume is less than the surveyed situation volume.

Optimization of Variable Guiding Lanes'Function at Signalized Intersections

This paper brings forward a method to improve the efficiency of the variable guiding lanes. It shows the proper time to change the direction of variable guiding lanes, and a new method to clean out the vehicles on the variable guiding lanes. In condition of a low flow of left-turning vehicle but a high flow of straight vehicle, or the opposite situation, the directions of the variable guiding lanes are different. In the certain of the signal cycle, we changed the direction and gave the proper time to clean out vehicle on the variable guiding lanes, and then the vehicle of different directions can run smoothly. Furthermore, it decreases the delay of the whole intersection and the risk of conflicts.

Analysis on Capacity and LOS of Signalized Intersection in Slight Snowy Weather

In order to evaluate traffic operation status of signalized intersection in slight snowy weather, it was studied that the influence of slight snow on capacity and level of service (LOS) of signalized intersection. Data of timing, vehicle’s starting loss time, saturated headway of straight vehicle and delay of one signalized intersections in sunny and slight snowy weather were observed by video method. Stop-line method was adopted to calculate the capacity of signalized intersection and LOS was evaluated by American standard. It showed that capacity of signalized intersection decreased by 7% and LOS declined one level in slight snowy weather compared with on sunny weather.

Turning at Intersections and Pedestrian Injuries

Objective. To evaluate if precrash vehicle movement is associated with the severity of pedestrian injury. Methods. We used comprehensive information on pedestrian, vehicle, and injury-related characteristics gathered in the Pedestrian Crash Data Study (PCDS), conducted by the National Highway Traffic Safety Administration (NHTSA) (1994–1998). The odds ratio of severe injuries (injury severity score ≥ 15) and crash fatality rate for right- and left-turn collisions at intersection compared with straight vehicle movement were compared using a logistic regression model and taking into consideration the type of vehicle and age of the pedestrians as potential effect modifiers. Later we evaluated the intermediate effect of impact speed on the association by adding it to the logistic regression model. Results. Of 255 collisions eligible for this analysis, the proportion of pedestrian hit during straight movement, right turns, and left turns were 48%, 32%, and 10%, respectively. Sixty percent of the pedestrians in left-turn crashes and 67% of them in right-turn collisions were hit from their left side. For straight movements the pedestrians were equally likely to be struck beginning from the left or right side of the street. After adjustment for pedestrian's age, vehicle movement was a significant predictor of severe injuries (p < 0.0001) and case fatality (p = 0.003). The association between vehicle precrash movement and severe injuries (p = 0.551) and case fatality (p = 0.912) vanished after adjusting for impact speed. This indicated that the observed association was probably the result of the difference in impact speed and not the precrash movement of the vehicle. Conclusion. Pedestrian safety interventions that aim at environmental modifications, such as crosswalk repositioning, might be the most efficient means in reducing right- or left-turn collisions at intersection, while pedestrians' behavioral modifications should be the priority for alleviating the magnitude of the collisions that happen in vehicles' straight movements.