scholarly journals Traffic Conflict Analysis of Motor Vehicles and Nonmotor Vehicles Based on Improved Cellular Automata

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Chenhao Dong ◽  
Rongguo Ma ◽  
Yujie Yin ◽  
Borui Shi ◽  
Wanting Zhang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Motor Vehicle ◽  
Motor Vehicles ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
The Road ◽  
Physical Isolation ◽  
Traffic Environment ◽  
Electric Bicycles

In recent years, with the rapid development of China’s logistics industry and urban service industry, electric bicycles have gradually become an important means of transportation in cities due to their flexibility, green technology, and low operating costs. Because electric bicycles travel though motor vehicle lanes and nonmotor vehicle lanes, the conflict between motor and nonmotor vehicles has become increasingly prominent, and the safety situation is not optimistic. However, most theories and models of mixed traffic flow are based on motor vehicles and bicycles and few involve electric bicycles. To explore the traffic safety situation in an urban mixed traffic environment, this paper first uses cellular automata (CA) to establish a three-strand mixed traffic flow model of motor vehicles, electric bicycles, and bicycles and verifies the reliability of the model by using a MATLAB simulation based on the actual survey data. Then, using the technology of traffic conflicts and the conflict rate as the index to evaluate the traffic safety situation, the change in the conflict rate with different road occupancies and different proportional coefficients of motor vehicles is studied. In the end, the conflict rate is compared between the mixed traffic flow and the setting of a physical isolation divider, which provides some suggestions on when to set a physical isolation divider to separate motor vehicles from nonmotor vehicles. The results show that in a mixed traffic environment, the conflict rate first increases and then decreases with increasing road occupancy and reaches a peak when the road occupancy is 0.6. In addition, in mixed traffic environments, the conflict rate increases with an increasing proportional coefficient of the motor vehicle. When the road occupancy rate is within the range of [0.6, 0.9] or when the proportional coefficient of motor vehicle is between [0.8, 0.9], a physical isolation divider can be set to separate motor vehicles and nonmotor vehicles from the space to improve traffic safety.

CELLULAR AUTOMATON MODELS FOR MIXED TRAFFIC FLOW CONSIDERING PASSAGE WAY OF EMERGENCY VEHICLE

2013 ◽  
Vol 27 (08) ◽  
pp. 1350052 ◽  
Author(s):  
HAN-TAO ZHAO ◽  
HONG-YAN MAO ◽  
RUI-JIN HUANG
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Average Density ◽  
Vehicle Speed ◽  
Emergency Vehicle ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
The Road ◽  
Emergency Vehicles ◽  
Computer Numerical Simulation

Two kinds of cellular automaton models are proposed for mixed traffic flow with emphasis on emergency vehicles. By analyzing the characteristics of ordinary vehicles in giving way to emergency vehicles, the rules for changing lanes are modified. Computer numerical simulation results indicate that an emergency vehicle without changing lanes can enhance speed with density lower than 0.1, while its speed can be enhanced by changing lane with density greater than 0.1. Meanwhile, vehicle speed and density within a certain range around emergency vehicles are lower than the road section average velocity and average density. The passage way of emergency vehicle that facilitate lane change causes less interference than that of an emergency vehicle which is unable to change lane. The study found that the physical characteristics of traffic flow when there are emergency vehicles are significantly different from routine traffic flow. Emergency vehicles can facilitate their passage by changing lanes at a medium or high density.

Optimization of Signal Timing for the Mixed Traffic Flow in Vissim Simulation Environment

2012 ◽  
Vol 253-255 ◽  
pp. 1726-1730
Author(s):  
Jian Gang Qiao ◽  
Pei Hu ◽  
Dan Yu
Keyword(s):  
Traffic Flow ◽  
Conversion Factor ◽  
Motor Vehicles ◽  
Signal Timing ◽  
Mixed Traffic ◽  
Simulation Environment ◽  
Mixed Traffic Flow ◽  
Signal Time

In order to improve the capacity of urban roads and alleviate the intersections’ congestion, this paper analyses the characteristics of mixed traffic flow in China, considers non- motor vehicles’ impact to the intersections, uses definite number of conversion to convert non-motor vehicles to motor vehicles, and then recomposes the F-B signal timing formula based on the traditional F-B signal timing method. By an example and Vissim simulation, a reasonable conversion factor is computed, The recomposed F-B signal time formula can reduce the delay and improve the efficience of the intersections, providing a new idea to signal timing under the mixed traffic flow.

scholarly journals Modified Motor Vehicles Travel Speed Models on the Basis of Curb Parking Setting under Mixed Traffic Flow

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Zhenyu Mei ◽  
Jun Chen
Keyword(s):  
Traffic Flow ◽  
Travel Speed ◽  
The Other ◽  
Motor Vehicles ◽  
Model Parameters ◽  
Mixed Traffic ◽  
Ongoing Controversy ◽  
Urban Streets ◽  
Urban Street ◽  
Mixed Traffic Flow

The ongoing controversy about in what condition should we set the curb parking has few definitive answers because comprehensive research in this area has been lacking. Our goal is to present a set of heuristic urban street speed functions under mixed traffic flow by taking into account impacts of curb parking. Two impacts have been defined to classify and quantify the phenomena of motor vehicles' speed dynamics in terms of curb parking. The first impact is called Space impact, which is caused by the curb parking types. The other one is the Time impact, which results from the driver maneuvering in or out of parking space. In this paper, based on the empirical data collected from six typical urban streets in Nanjing, China, two models have been proposed to describe these phenomena for one-way traffic and two-way traffic, respectively. An intensive experiment has been conducted in order to calibrate and validate these proposed models, by taking into account the complexity of the model parameters. We also provide guidelines in terms of how to cluster and calculate those models' parameters. Results from these models demonstrated promising performance of modeling motor vehicles' speed for mixed traffic flow under the influence of curb parking.

scholarly journals A Vision-Based Video Crash Detection Framework for Mixed Traffic Flow Environment Considering Low-Visibility Condition

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Chen Wang ◽  
Yulu Dai ◽  
Wei Zhou ◽  
Yifei Geng
Keyword(s):  
Image Enhancement ◽  
Traffic Flow ◽  
Motor Vehicle ◽  
Detection Performance ◽  
Mixed Traffic ◽  
Model Framework ◽  
High Detection Rate ◽  
Mixed Traffic Flow ◽  
Flow Environment ◽  
Low Visibility

In this paper, a vision-based crash detection framework was proposed to quickly detect various crash types in mixed traffic flow environment, considering low-visibility conditions. First, Retinex image enhancement algorithm was introduced to improve the quality of images, collected under low-visibility conditions (e.g., heavy rainy days, foggy days and dark night with poor lights). Then, a Yolo v3 model was trained to detect multiple objects from images, including fallen pedestrians/cyclists, vehicle rollover, moving/stopped vehicles, moving/stopped cyclists/pedestrians, and so on. Then, a set of features were developed from the Yolo outputs, based on which a decision model was trained for crash detection. An experiment was conducted to validate the model framework. The results showed that the proposed framework achieved a high detection rate of 92.5%, with relatively low false alarm rate of 7.5%. There are some useful findings: (1) the proposed model outperformed empirical rule-based detection models; (2) image enhancement method can largely improve crash detection performance under low-visibility conditions; (3) the accuracy of object detection (e.g., bounding box prediction) can impact crash detection performance, especially for minor motor-vehicle crashes. Overall, the proposed framework can be considered as a promising tool for quick crash detection in mixed traffic flow environment under various visibility conditions. Some limitations are also discussed in the paper.

scholarly journals Cellular Automata Based Modeling for Evaluating Different Bus Stop Designs in China

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Haoyang Ding ◽  
Wei Wang ◽  
Tianming Luo ◽  
Zhen Yang ◽  
Ye Li ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Motor Vehicle ◽  
Motor Vehicles ◽  
Inflow Rate ◽  
Passenger Transport ◽  
Transport Capacity ◽  
Mixed Traffic Flow ◽  
Bus Stop ◽  
Traffic Conflicts ◽  
Bus Stops

A cellular automaton model is proposed to simulate mixed traffic flow composed of motor vehicles and bicycles near bus stops. Three typical types of bus stops which are common in China are considered in the model, including two types of curbside bus stops and one type of bus bay stops. Passenger transport capacity of three types of bus stops, which is applied to evaluate the bus stop design, is calculated based on the corresponding traffic flow rate. According to the simulation results, the flow rates of both motor vehicles and bicycles exhibit phase transition from free flow to the saturation one at the critical point. The results also show that the larger the interaction between motor vehicle and bicycle flow is near curbside bus stops, the more the value of saturated flows drops. Curbside bus stops are more suitable when the conflicts between two flows are small and the inflow rate of motor vehicles is low. On the contrary, bus bay stops should be applied due to their ability to reduce traffic conflicts. Findings of this study can provide useful suggestions on bus stop selection considering different inflow rate of motor vehicles and bicycles simultaneously.

Research on the characteristics of mixed traffic flow based on an improved bicycle model

SIMULATION ◽  
2017 ◽  
Vol 94 (5) ◽  
pp. 451-462
Author(s):  
Peng Dong ◽  
Xifu Wang ◽  
Lifen Yun ◽  
Hongqiang Fan
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Traffic Accidents ◽  
Urban Traffic ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
The Road ◽  
Bicycle Model ◽  
Human Powered ◽  
Self Protection

Mixed traffic flow is a main feature of urban traffic in developing countries. Mixed bicycle flow includes human-powered and electric-powered bicycles and plays an important role in this mixed traffic flow. In mixed bicycle flow, cyclist behavior is flexible and variable. Cyclists move arbitrarily in the road and may influence the vehicle flow at intersections. Therefore, we first propose an improved bicycle model that can reproduce the main features of cyclist behavior, such as overtaking and self-protection. Then a simulation model based on the improved bicycle model is proposed to research the characteristics of mixed traffic flow in intersections. The conflict avoidance rules are then applied in the simulation model to eliminate traffic accidents. The simulation results indicate that the improved bicycle model is practical and that the density–velocity diagram of bicycle flow is similar to real traffic data. The existence of bicycle flow decreases vehicle velocity and worsens traffic flow in mixed traffic flow. However, the influence of bicycle flow might disappear at a particular vehicle density.

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