Traffic Safety Evaluation of Uncontrolled Intersections using Surrogate Safety Measures under Mixed Traffic Conditions

2015 ◽  
Vol 2512 (1) ◽  
pp. 81-89 ◽  
Author(s):  
P. Vedagiri ◽  
Deepak V. Killi
Keyword(s):  
Traffic Safety ◽  
Safety Evaluation ◽  
Mixed Traffic ◽  
Safety Measures ◽  
Traffic Conditions ◽  
Management Measures ◽  
Large Populations ◽  
Accident Data ◽  
Surrogate Safety Measures ◽  
The Impact

In the developing world, with increases in population, the number of vehicles is increasing tremendously. Traffic safety on roads has become a major concern even with advancements in technology and infrastructure. Traffic safety assessments and accident prediction based on accident data is a reactive approach. There are known drawbacks related to the reliability of accident data, especially in developing countries with large populations, such as India. It is, however, unethical to wait for accidents to occur before drawing statistically accurate conclusions regarding safety impacts. To overcome this impediment, one needs to develop accurate models that rely on surrogate safety measures (SSMs) for effective safety evaluations. The main advantage associated with the use of these models is that they can model crashes more frequently than in the real world and thereby imply an efficient and more statistically reliable proximal measure of traffic safety. The objective of this study is to examine the impact of management measures on traffic safety at a three-arm uncontrolled intersection with the use of microsimulation modeling under mixed traffic conditions. This examination was done by developing a unique methodology of measuring one SSM, postencroachment time (PET). This paper describes improvement in the accuracy of crash predictions by proposing a methodology to calculate PET.

scholarly journals PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 48-56
Author(s):  
Sankaran Marisamynathan ◽  
Perumal Vedagiri
Keyword(s):  
Safety Evaluation ◽  
Pedestrian Safety ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Mixed Traffic ◽  
Model Framework ◽  
Safety Measures ◽  
Severity Level ◽  
Traffic Conditions ◽  
Surrogate Safety Measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

Operational safety of automated and human driving in mixed traffic environments: A perspective of car-following behavior

2021 ◽  
pp. 1748006X2110506
Author(s):  
Tao Li ◽  
Xu Han ◽  
Jiaqi Ma ◽  
Marilia Ramos ◽  
Changju Lee
Keyword(s):  
Traffic Safety ◽  
Risk Mitigation ◽  
Safety Evaluation ◽  
Mixed Traffic ◽  
Trajectory Data ◽  
Road Transportation ◽  
Baseline Model ◽  
Car Following ◽  
On The Road ◽  
The Impact

The advent of automated vehicles (AVs) will provide opportunities for safer, smoother, and smarter road transportation. During the transition from the current human-driven vehicle (HV) to a fully AV traffic environment, there will be a mixed traffic flow including both HVs and AVs. The impact of introducing AVs into existing traffic, however, has not yet been fully understood. In this paper, we advance this understanding by conducting mixed traffic safety evaluation from the perspective of car-following behavior using real-world AV operational data of mixed traffic. To understand how the AVs impact other vehicles on the road, we analyzed the operational behaviors of HV-following-HV, AV-following-HV, and HV-following-AV. A selected car-following model is calibrated, and results show that there are significant differences between the HV-following-HV and the other two groups, indicating safe AV behavior and changes in HV behavior (i.e. less aggressive, safer) after the introduction of AVs into the traffic. Additionally, to understand AV behavioral safety, we investigate behavior predictions (one of the most critical inputs for AVs to make car-following decisions) of AVs and their surrounding vehicles using a mature baseline model and a new Conditional Variational Autoencoder (CVAE) framework. The result shows potential risks of inaccurate predictions of the baseline model and the necessity to consider additional factors, such as vehicle interactions and driver behavior, into the prediction for risk mitigation. Arterial vehicle trajectory data from the Lyft Level 5 Dataset is applied to test the proposed methodological framework to understand the car-following safety risks of HVs and AVs in the mixed traffic stream.

scholarly journals The Impact of Truck Proportion on Traffic Safety Using Surrogate Safety Measures in China

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Shengdi Chen ◽  
Shiwen Zhang ◽  
Yingying Xing ◽  
Jian Lu ◽  
Yichuan Peng ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Traffic Flow ◽  
Traffic Safety ◽  
Variation Coefficient ◽  
Support Vector ◽  
Safety Measures ◽  
Speed Variation ◽  
Surrogate Safety Measures ◽  
The Impact ◽  
The Relationship

The purpose of this study is to investigate the impact of the truck proportion on surrogate safety measures to explore the relationship between truck proportion and traffic safety. The relationship between truck proportion and traffic flow parameters was analyzed by correlation and partial correlation analysis, and the value of the 85th percentile speed minus the 15th percentile speed (85%V–15%V) and the speed variation coefficient were selected as surrogate safety measures to explore the impact of truck proportion on traffic status. The k-means algorithm and the support vector machine were employed to evaluate traffic status on a freeway under different truck proportions in different periods. The major results are that the relationship between truck proportion and the value of 85%V–15%V and the speed variation coefficient is consistent in different aggregation periods. With increasing truck proportion, the value of 85%V–15%V, as well as the speed variation coefficient, increases initially and then decreases. In addition, the traffic flow status tends to be dangerous when the truck proportion ranges from 0.4 to 0.6 and when the value of 85%V–15%V and the speed variation coefficient are above 42 km/h and 0.223, respectively. While the truck proportion is from 0.1 to 0.3 and from 0.7 to 0.9, the traffic flow is relatively safe on the condition that the value of 85%V–15%V and the speed variation coefficient were under 42 km/h and 0.223, respectively. Therefore, the relationship between truck proportion and traffic safety could be well revealed by two surrogate safety measures, that is, the value of 85%V–15%V and the speed variation coefficient. In addition, the k-means algorithm and the support vector machine can well reveal the impact of truck proportion on traffic safety in different periods. The findings of this study indicate a need for decreasing the disturbance of mixed traffic and the impact of the truck proportion on traffic safety status.

scholarly journals Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon

2020 ◽  
Vol 12 (23) ◽  
pp. 9955
Author(s):  
Fan Ding ◽  
Jiwan Jiang ◽  
Yang Zhou ◽  
Ran Yi ◽  
Huachun Tan
Keyword(s):  
Traffic Safety ◽  
Feedforward Control ◽  
Safety Evaluation ◽  
Evaluation Framework ◽  
Active Safety ◽  
Automated Vehicles ◽  
Safety Measures ◽  
Car Following ◽  
Surrogate Safety Measures ◽  
Connected Automated Vehicles

With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

Study on Road Traffic Safety Evaluation Based on Improved Bayes Model

2011 ◽  
Vol 97-98 ◽  
pp. 489-493
Author(s):  
Yao Ping Li ◽  
Jian Lin Li ◽  
Bin Li ◽  
Li Wei Hu
Keyword(s):  
Traffic Safety ◽  
Empirical Bayes ◽  
Safety Management ◽  
Road Traffic ◽  
Safety Evaluation ◽  
Road Traffic Safety ◽  
Accident Probability ◽  
Probability Prediction ◽  
Accident Data ◽  
The Impact

he traditional safety evaluation methods are mostly based on historical accident data, which belong to the macroscopical level and have obvious defects in traffic safety management. This paper established accident Probability Density Function by using Kernel Density Estimation (KDE), proposed Accident Probability Prediction (APP) model based on Empirical Bayes (EB) method for considering the impact of accident location characteristics and historical data. The paper also established the method for road traffic safety micro-evaluation by adopting Traffic Accident Probabilities of Equivalent ten thousand Cars (TAPEC) indicator, and a comparative evaluation was conducted by the proposed method against cumulative frequency curve method. Through analyzing accident data collected from the G301, the results show that the proposed method is more reliable and can access to the transformation priorities of potentially dangerous road sections. So it can provide theoretical basis for checking the dangerous sections and improving accident prevention and response.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

AHP to Appraise the Traffic Safety of the Express Way

2011 ◽  
Vol 48-49 ◽  
pp. 157-163
Author(s):  
Dan Yu ◽  
Yi Hu Wu ◽  
Zhi Xiang Hou ◽  
Wen Jun Liu ◽  
Ji Guang Zhang
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Safety Evaluation ◽  
Evaluation Index System ◽  
The Road ◽  
Comprehensive Evaluation Model ◽  
The Impact ◽  
Fuzzy Interval

The internal structure of the road safety system is extremely complex and it is affected by a lot of factors, each factor weights can not be fully established. In this article, we expressed the attribute value with a fuzzy interval number, the comprehensive appraise to the impact of traffic safety with emphasis on "people", "car" "road" in the "road". First of all, establishing evaluation index system, and form the judging matrix by AHP; then, it can be acquired a method of traffic safety evaluation by using the comprehensive evaluation model of the fuzzy interval.

scholarly journals Analysis of Children’s Traffic Behaviour at Signalized Crosswalks as a Precondition for Safe Children Routes Design: A Case Study from Croatia

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Irena Ištoka Otković ◽  
Aleksandra Deluka-Tibljaš ◽  
Sanja Šurdonja
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Daily Basis ◽  
Children And Adolescent ◽  
Traffic Conditions ◽  
Road Users ◽  
Design Speed ◽  
Pedestrian Infrastructure ◽  
The Impact

Children pedestrians represent road users with some specifics because of which it is important to study and take into account their traffic behaviour when traffic infrastructure is designed. Design should ensure and enhance their traffic safety because for decades, traffic accidents have been among the first few causes of children and adolescent mortality. Pedestrian speed is one of the important inputs when pedestrian infrastructure, especially crosswalks, is designed. On corridors where children are expected on a daily basis as independent pedestrians, the infrastructure should be adjusted to their characteristics and needs. The results of a study conducted in two Croatian cities of a similar size but of different urban and traffic conditions are presented in this paper. This study aimed at establishing and analysing children’s pedestrian speed while crossing the signalized crosswalk in the buffer area of elementary schools, mostly on primary roads in the school vicinity. Children aged 5–15 were observed, and accordingly V15, V50, and V85 speeds were established on the basis of altogether 600 measurements. Speed was established for children walking individually, in a group and supervised by adults, and of a different age, and based on their gender, the impact of infrastructural elements on their speed in traffic was also analysed. Significant differences were found between children’s speed measured in similar conditions in analysed cities and between some of the analysed groups. This fact proves that when improving conditions for children’s independent movement, it is important to consider their specifics in order to ensure safe design adjusted to children’s needs and limitations. As design speed in this paper, 15 percentile speed (V15) is considered. Suggestions on how to establish children pedestrian speed for design of routes regularly used by school children are proposed as well as some inputs elicited from the study done in Croatia are presented.

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