Traffic Conflict Technique Development for Traffic Safety Evaluation under Mixed Traffic Conditions of Developing Countries

2017 ◽  
Vol 5 (4) ◽  
Author(s):  
Tran Quang Vuong
Keyword(s):  
Developing Countries ◽  
Traffic Safety ◽  
Safety Evaluation ◽  
Mixed Traffic ◽  
Traffic Conditions ◽  
Traffic Conflict ◽  
Technique Development

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.

Surrogate Measures for Traffic Safety Evaluation in Developing Countries: An Application Toward Sustainable Safety

2018 ◽  
Vol 7 (3) ◽  
pp. 20170105
Author(s):  
S. M. Sohel Mahmud ◽  
Luis Ferreira ◽  
Md. Shamsul Hoque ◽  
Ahmad Tavassoli
Keyword(s):  
Developing Countries ◽  
Traffic Safety ◽  
Safety Evaluation ◽  
Surrogate Measures

scholarly journals In Search of the Consequence Severity of Traffic Conflict

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Ruoxi Jiang ◽  
Shunying Zhu ◽  
Pan Wang ◽  
QiuCheng Chen ◽  
He Zou ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Evaluation Method ◽  
Prediction Models ◽  
Safety Evaluation ◽  
Threshold Value ◽  
Two Dimensions ◽  
Trajectory Data ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Accident Data

Currently, many studies on the severity of traffic conflicts only considered the possibility of potential collisions but ignored the consequences severity of potential collisions. Aiming toward this defect, this study establishes a potential collision (serious conflict) consequences severity model on the basis of vehicle collision theory. Regional vehicles trajectory data and historical traffic accident data were obtained. The field data were brought into the conflict consequences severity model to calculate the conflict severity rate of each section under different TTC thresholds. For comparison, the traditional conflict rate of each section under different TTC thresholds that considered only the number of conflicts was also calculated. Results showed that the relationship between conflict severity rate and influencing factors was somehow different. The conflict severity rate seemed to have a higher correlation with accident rate and accident severity rate than conflict rate did. The TTC threshold value also affected the correlation between conflicts and accidents, with high and low TTC threshold indicating a lower correlation. The results showed that conflict severity rate that considered each single conflict consequence severity was a little better than the traditional conflict rate that considered only the numbers of conflicts in reflecting real risks as a new conflict evaluation indicator. The severity of traffic conflicts should consider two dimensions: the possibility and consequence of potential collisions. Based on this, we propose a new traffic safety evaluation method that takes into account the severity of the consequences of the conflict. More data and prediction models are needed to conduct more realistic and complex research in the future to ensure reliability of this new method.

Evaluation of Traffic Safety of Curved Section with Gray Theory Based on the Driving Track

2012 ◽  
Vol 588-589 ◽  
pp. 2117-2120
Author(s):  
Jian Feng Xi ◽  
Zhen Hai Gao ◽  
Bo Qi ◽  
Hai Zhu Liu
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Evaluation Method ◽  
Safety Evaluation ◽  
The Other ◽  
Evaluation Index ◽  
Gray Theory ◽  
Traffic Conflict ◽  
Curved Section

Curved section is one of the sections where happened extraordinarily serious traffic accidents in China. Until now, one kind of the traffic safety evaluation method based on the accident indexes, the other based on the non-accident indexes, just as the traffic conflict technique. But there are difficulties in collecting data when the evaluation of traffic safety on specific road sections is applied. So, one safety evaluation method for the curved sections is putting forward, in which the deviation value between the driving track and safe trajectory is used as the evaluation index, and the gray evaluation method is applied. The case study shows that, the method in this paper could be a new way for traffic safety evaluation.

The Application of Traffic Conflict Technique as a Road Safety Evaluation Method: A Case Study of Hasselt Intersection

2016 ◽  
Vol 845 ◽  
pp. 394-403 ◽  
Author(s):  
Fardzanela Suwarto ◽  
Kami Hari Basuki
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Evaluation Method ◽  
Prediction Models ◽  
Safety Evaluation ◽  
Road User ◽  
The Road ◽  
Traffic Conflict ◽  
Accident Data

The majority of traffic safety evaluations in the world generally have been conducted by colecting historical accident data. The data will then being analyzed using risk prediction models or before-after study that required an exact and reliable data. Meanwhile, the availability of accident data is rare where the rest actually consist of near-crashes and abnormal behaviour, which is mostly underreporting and lack of detail concerning the behavioural and situational of the event. Therefore, traffic conflict technique, is needed to assess traffic safety as another approach rather than waiting for several years until a number of accidents happen in a certain area. Hence the aim of this study is to make a safety evaluation towards a specific intersection in Hasselt Belgium using traffic conflict technique. The observation of conflict (near crashes) was carried out in intersection of Manteliusstraat – Dorpsstraat – Thonissenlaan in the Hasselt, Belgium. In order to differentiate slight conflict and serious conflict, the TA-value (Time of accident) was defined based on the estimated speed of the road user and estimated distance from the road user when conflict occurred. From the observation, it was found that the conflicts between car and pedestrian were the most frequent conflict, with 50% of the total conflict, and that the conflict between car with car and the conflict between car with cyclist were high in terms of severity level based on the TA-value. By taking these into consideration, it can be concluded that unsafe crossing for pedestrian and cyclist, different speed, and peak hour traffic were the causes of conflict. Therefore, it was concluded that traffic conflict technique can be used to assess and measure traffic safety in a certain road segment. Furthermore, in term of safety, the Manteliusstraat – Dorpsstraat – Thonissenlaan intersection should be modified with some alternatives; signalized intersection with toucan crossing and traffic control devices improvement

scholarly journals Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Hong Li ◽  
Sujian Li ◽  
Haijian Li ◽  
Lingqiao Qin ◽  
Shi Li ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Traffic Engineering ◽  
Driving Behavior ◽  
Signalized Intersections ◽  
Mixed Traffic ◽  
Left Turn ◽  
Security Issues ◽  
Traffic Conditions ◽  
Traffic Characteristics ◽  
Potential Applications

In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.

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