scholarly journals Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 926
Author(s):  
Huimin Ge ◽  
Mingyue Huang ◽  
Ying Lu ◽  
Yousen Yang
Keyword(s):  
Prediction Model ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Absolute Error ◽  
Vehicle Speed ◽  
Time To Collision ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Conflict Prediction

Due to the randomness and weak symmetry of traffic accidents occurring in the expressway maintenance operation area, it is difficult to use the number of traffic accidents to evaluate the safety of maintenance operation areas. In this paper, the traffic characteristics and traffic conflicts of the maintenance operation area with the lane closed on the outside of the two-way four-lane expressway are studied. By using the statistical method, the distribution of vehicle speed and time headway in different areas of the maintenance operation area are analyzed, and the queuing characteristics of vehicles in the upstream transition zone of the expressway are determined. Based on improved time to collision (TTC) model, the traffic conflict severity of expressway maintenance operation area is divided. The negative binomial distribution is used to establish a traffic conflict prediction model for the enclosed maintenance area of the outer lane of the expressway, and the validity of the traffic conflict prediction model is verified based on the average absolute error percentage (MAPE). The research results show that: when the 0 < TTC < 1.3 s, the traffic conflict is serious conflict; when 1.3 s < TTC, the traffic conflict is non-serious conflict. Furthermore, the traffic conflict prediction model has high accuracy, the MAPE of the warning area and the upstream transition area are 10.8% and 5.0%, respectively.

scholarly journals Safety Performance Evaluation of a Three-Leg Unsignalized Intersection Using Traffic Conflict Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Guoqiang Zhang ◽  
Jun Chen ◽  
Jingya Zhao
Keyword(s):  
Prediction Model ◽  
Video Camera ◽  
Conflict Analysis ◽  
Safety Performance ◽  
Time To Collision ◽  
Time Headway ◽  
Independent Variables ◽  
Minor Road ◽  
Traffic Conflicts ◽  
Traffic Conflict

Traffic conflicts were used to evaluate safety performance of a three-leg unsignalized intersection. With the aid of a video camera, data were collected at the intersection and 15-second time span was used in each observation to overcome the drawbacks of traditional methods of traffic conflict analysis. Time to collision (TTC), a widely accepted indicator, was used to identify whether an interaction between two vehicles was a traffic conflict. By using Poisson regression, a prediction model for traffic conflicts at the intersection was developed. Based upon the model, assuming that other factors remain constant, when time headway or speed of eastbound traffic on major road, which is crossed by left-turning traffic from minor road, increases, the number of traffic conflicts at the intersection decreases. When volume of left-turning traffic on minor road or speed of left-turning vehicles on minor road increases, the number of traffic conflicts at the intersection increases if other factors remain constant. Explanations for the influence of the factors, which were represented by independent variables of the prediction model, were then analyzed in detail.

scholarly journals TRAFFIC CONFLICT IDENTIFICATION OF E-BIKES AT SIGNALIZED INTERSECTIONS

Transport ◽  
2020 ◽  
Vol 0 (0) ◽  
pp. 1-14
Author(s):  
Zhaowei Qu ◽  
Yuhong Gao ◽  
Xianmin Song ◽  
Yingji Xia ◽  
Lin Ma ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Space Time ◽  
Spatial Proximity ◽  
Time To Collision ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Discriminant Analyses ◽  
Change Trend ◽  
Conflict Identification ◽  
Conflict Types

The increase of e-bikes has raised traffic conflict concerns over past decade. Numerous conflict indicators are applied to measure traffic conflicts by detecting differences in temporal or spatial proximity between users. However, for traffic environment with plenty of e-bikes, these separate space-time approaching indicators may not be applicable. Thus, this study aims to propose a multi-variable conflict indicator and build a conflict identification method for e-bikes moving in the same direction. In particular, by analysing the conflict characteristics from e-bikes trajectories, a multi-variable conflict indicator utilizing change of forecast post encroachment time, change of relative speed and change of distance is derived. Mathematical statistics and cluster discriminant analyses are applied to identify types of conflict, including conflict existence identification and conflict severity identification. The experimental results show: in mixed traffic environments with many e-bikes, compared with time-to-collision and deceleration, accuracy of identifying e-bike conflict types based on proposed method is the highest and can reach more than 90%; that is, multi-variable indicator based on time and space are more suitable for identifying e-bike conflicts than separate space-time approaching indicators. Furthermore, setting of dividing strip between motor vehicle and non-motorized vehicle has significant influence on number and change trend of conflict types. The proposed method can not only provide a theoretical basis and technical support for automated conflict detection in mixed transportation, but also give the safety optimization sequence of e-bikes at different types of intersections.

scholarly journals Development of models to study traffic accidents on the final sections of access roads to the cities: a case study of three major Iranian cities

2021 ◽  
Vol 59 (3) ◽  
pp. 129-148
Author(s):  
Mehdi Fallah Tafti ◽  
Reza Roshani
Keyword(s):  
Traffic Accidents ◽  
Probabilistic Models ◽  
Negative Binomial ◽  
Ann Model ◽  
Lighting Condition ◽  
Traffic Characteristics ◽  
Ann Models ◽  
Accident Rates ◽  
Roadway Lighting ◽  
Major Factors

The final sections of main access roads to the cities require especial attention as the frequency of accidents in these road sections are considerably higher than other parts of interurban roads. These road sections operate as an interface between the rural roads and urban streets. The previous researches available on this subject are limited and they have also mainly focused on a narrow range of factors contributing to the accidents in these areas. The main contribution of this research is to consider a relatively comprehensive range of potential factors , and to examine their impacts through the development and comparison of both conventional probabilistic models and Artificial Neural Network (ANN) models. For this purpose, information related to the main access roads of three major Iranian cities were collected. This information consisted of accident frequency data together with the field observations of traffic characteristics, road-way conditions and roadside features of these roads. Various ANN and probabilistic models were developed. The frequency of accidents, i.e. fatal, injured, or damaged accidents, was considered as the output of the developed models. The results indicated that a hybrid of ANN models, each comprised of 10 input variables representing traffic, roadway and roadside conditions, outperformed several probabilistic models, i.e. Poisson, Negative binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial models, also developed under similar conditions in this study. Moreo-ver, effective roadway width, roadway lighting condition, the standard deviation of vehicles speed, percentage of drivers violating the speed limit, average annual daily traffic, percentage of heavy goods vehicles, the density of road-side commercial and industrial landuses, the density of median U-turns, the density of local access roads, and the effective width of the left-side shoulder were identified as the most effective factors contributing to the accidents in these areas. The developed ANN model can be used as a tool to predict accident rates in these road sections, and to estimate a potential reduction in the accident rates, following any improvements in the major factors contributing to the traffic accidents in these areas.

scholarly journals Risk Factors Affecting Traffic Accidents at Urban Weaving Sections: Evidence from China

2019 ◽  
Vol 16 (9) ◽  
pp. 1542 ◽  
Author(s):  
Xinhua Mao ◽  
Changwei Yuan ◽  
Jiahua Gan ◽  
Shiqing Zhang
Keyword(s):  
Risk Factors ◽  
Traffic Accidents ◽  
Multinomial Logistic Regression ◽  
Weather Condition ◽  
Weather Conditions ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Factors Affecting ◽  
Traffic Characteristics ◽  
Rainy Weather

As a critical configuration of interchanges, the weaving section is inclined to be involved in more traffic accidents, which may bring about severe casualties. To identify the factors associated with traffic accidents at the weaving section, we employed the multinomial logistic regression approach to identify the correlation between six categories of risk factors (drivers’ attributes, weather conditions, traffic characteristics, driving behavior, vehicle types and temporal-spatial distribution) and four types of traffic accidents (rear-end, side wipe, collision with fixtures and rollover) based on 768 accident samples of an observed weaving section from 2016 to 2018. The modeling results show that drivers’ gender and age, weather condition, traffic density, weaving ratio, vehicle speed, lane change behavior, private cars, season, time period, day of week and accident location are important factors affecting traffic accidents at the weaving section, but they have different contributions to the four traffic accident types. The results also show that traffic density of ≥31 vehicle/100 m has the highest risk of causing rear-end accidents, weaving ration of ≥41% has the highest possibility to bring about a side wipe incident, collision with fixtures is the most likely to happen in snowy weather, and rollover is the most likely incident to occur in rainy weather.

scholarly journals Safety evaluation of unconventional outside left-turn lane using automated traffic conflict techniques

2016 ◽  
Vol 43 (7) ◽  
pp. 631-642 ◽  
Author(s):  
Yanyong Guo ◽  
Tarek Sayed ◽  
Mohamed H. Zaki ◽  
Pan Liu
Keyword(s):  
Urban Areas ◽  
Safety Evaluation ◽  
Signalized Intersections ◽  
Video Data ◽  
Contributing Factors ◽  
Left Turn ◽  
Time To Collision ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
The Right

The objective of this study is to evaluate the safety impacts of unconventional outside left-turn lane at signalized intersections. New designed unconventional outside left-turn lanes are increasingly used at signalized intersections in urban areas in China. The unconventional outside left-turn lane design allows an exclusive left-turn lane to be located to the right of through lanes to improve the efficiency and increase the capacity of left-turn movements. However, the design also raises some concerns regarding potential negative safety impacts. The evaluation is conducted using an automated video-based traffic conflict technique. The traffic conflicts approach provides better understanding of collision contributing factors and the failure mechanism that leads to road collisions. Traffic conflicts are automatically detected and time to collision is calculated based on the analysis of the vehicles’ positions in space and time. Video data are collected from a signalized intersection in Nanjing, China, where both traditional inside and unconventional outside left-turn lanes are installed on two intersection approaches. The other two approaches have only inside left-turn lanes. The study compared frequency and severity of conflict for left-turning vehicles as well as the percentage of vehicles involved in conflicts from the inside and outside left-turn lanes. The results show that the intersection approaches with outside left-turn lanes had considerably more conflicts compared to approaches without outside left-turn lanes. As well, the approaches with outside left-turn lanes had significantly higher conflict severity than the approaches without outside left-turn lanes. As such, it is recommended that the trade-off between the improved mobility and negative safety impact of outside left-turn lanes be carefully considered before recommending their installation.

Comparison of Traffic Conflict Indicators for Crash Estimation using Peak Over Threshold Approach

2019 ◽  
Vol 2673 (5) ◽  
pp. 493-502 ◽  
Author(s):  
Lai Zheng ◽  
Tarek Sayed
Keyword(s):  
Confidence Intervals ◽  
Signalized Intersections ◽  
Estimation Methods ◽  
Crash Data ◽  
Time To Collision ◽  
Considerable Research ◽  
Traffic Conflicts ◽  
Peak Over Threshold ◽  
Traffic Conflict ◽  
Threshold Approach

Traffic conflict techniques have drawn considerable research interest and a number of conflict indicators have been developed. Previous studies have qualitatively analyzed indicator differences from their definitions and empirically investigated their similarities based on identified traffic conflicts. This study compares conflict indicators from a validity perspective by comparing crashes estimated from conflict indicators with observed crashes. The peak over threshold (POT) approach was employed for crash estimation. Four commonly used indicators are compared: time to collision (TTC), modified time to collision (MTTC), post encroachment time (PET), and deceleration to avoid a crash (DRAC). Based on the conflict and crash data collected from three signalized intersections, POT models are developed for different thresholds in the appropriate ranges, and crash estimation methods were proposed for individual conflict indicators. The identified conflicts and estimated crashes associated with different indicators are then compared. The results show that traffic conflicts identified by the four indicators vary, with MTTC generating the most accurate crash estimates. The crash estimates from TTC and PET are also reasonable but there is a tendency of overestimation for TTC and underestimation for PET. The crash estimates of DRAC are all outside the confidence intervals of observed crashes, which is likely related to the uncertainty of vehicle braking capacity.

scholarly journals Research on Traffic Characteristics and Traffic Conflicts of the One-Way-Closure Work Zone on Freeway

2012 ◽  
Vol 5 ◽  
pp. 26-31
Author(s):  
Lai Zheng ◽  
Xiang Hai Meng
Keyword(s):  
Negative Binomial ◽  
Work Zone ◽  
Distribution Model ◽  
Erlang Distribution ◽  
Work Zones ◽  
Traffic Conditions ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
The One ◽  
Conditions Of Work

By analyzing the traffic characteristics and traffic conflicts of the typical one-way-closure work zone on four-lane freeway, the queuing characteristics of vehicles are determined, and the Erlang distribution model which can describe the distribution of time headway is calibrated. The speed distribution characteristics of each component of the work zone are concluded, and the speed limit scales for these components are put forward based on the statistic analysis. The types of traffic conflicts are firstly concluded, and then the identification method of the rear-end conflicts’ severity degree based on TTC technique as well as the prediction model of rear-end conflicts based on Negative Binomial distribution are put forward. The research results are useful to the analysis of traffic conditions of work zones, and they can also be used to evaluate the safety situations of freeway work zones

Sign in / Sign up

Export Citation Format

Share Document