Simulation-based model for surrogate safety measures analysis in automated vehicle-pedestrian conflict on an urban environment

2020 ◽  
Author(s):  
Hesham Alghodhaifi ◽  
Sridhar Lakshmanan
Keyword(s):  
Urban Environment ◽  
Safety Measures ◽  
Automated Vehicle ◽  
Simulation Based ◽  
Surrogate Safety Measures

scholarly journals Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mark Mario Morando ◽  
Qingyun Tian ◽  
Long T. Truong ◽  
Hai L. Vu
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Assessment Model ◽  
Traffic Crashes ◽  
Safety Measures ◽  
High Penetration ◽  
Simulation Based ◽  
Car Following Model ◽  
Surrogate Safety Measures ◽  
Signalised Intersection

Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p<0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p<0.05).

scholarly journals Reinstating a national simulation programme in anaesthesiology during the coronavirus pandemic

2021 ◽  
pp. bmjstel-2021-000894
Author(s):  
Sinead Campbell ◽  
Sarah Corbett ◽  
Crina L Burlacu
Keyword(s):  
Simulation Training ◽  
Online Video ◽  
Safety Measures ◽  
Face To Face ◽  
Video Assisted ◽  
Simulation Based ◽  
High Standards ◽  
Strongly Agree ◽  
Training Opportunities ◽  
Simulation Programme

BackgroundWith the introduction of strict public health measures due to the coronavirus pandemic, we have had to change how we deliver simulation training. In order to reinstate the College of Anaesthesiologists Simulation Training (CAST) programme safely, we have had to make significant logistical changes. We discuss the process of reopening a national simulation anaesthesiology programme during a pandemic.MethodsWe approached how to reinstate the programme with three distinct but intertwined projects, as in the following: (1) a survey of effects of the pandemic on training opportunities for anaesthesiology trainees, (2) proposals for methods of reinstating simulation were developed under the headings avoidance, compromise, accommodation and collaboration. A small online video-assisted simulation pilot was carried out to test the compromise method, (3) having opted for combined accommodation (onsite with smaller participant numbers and safety measures) and collaboration (with other regional centres), a postreinstatement evaluation during a 4-month period was carried out.Results(1) Eighty-five per cent of 64 trainees surveyed felt that they had missed out not only just on simulation-based education (43%) but also on other training opportunities, (2) when five trainees were asked to state on a 1 to 5 Likert scale (strongly disagree, disagree, undecided, agree and strongly agree) whether online video-assisted simulation was similar to face-to-face simulation in four categories (realism, immersion, sense of crisis and stress), only 9 (45%) of the 20 answers agreed they were similar, (3) When onsite simulation was reinstated, the majority of trainees felt that training was similar to prepandemic and were happy to continue with this format.ConclusionIn order to reinstate simulation, we have identified that accommodation and collaboration best suited the CAST while compromise failed to rank high among trainees’ preferences. Onsite courses will continue to be delivered safely while meeting the high standards our trainees have come to expect.

scholarly journals Proposing New Methods to Estimate the Safety Level in Different Parts of Freeway Interchanges

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hamid Behbahani ◽  
Sayyed Mohsen Hosseini ◽  
Alireza Taherkhani ◽  
Hemin Asadi ◽  
Seyed Alireza Samerei
Keyword(s):  
Video Processing ◽  
Prediction Models ◽  
Trajectory Data ◽  
Safety Level ◽  
Accident Prediction ◽  
Traffic Characteristics ◽  
Potential Index ◽  
Simulation Based ◽  
Surrogate Safety Measures ◽  
Different Parts

Since attention to the safety of traffic facilities including freeway interchanges has been increased during recent years, accident prediction models are being developed. Simulation-based surrogate safety measures (SSMs) have been used in the absence of real collision data. But, obtaining different outputs from different SSMs as safety indicators had led to a complexity of using them as the collision avoidance system basis. Additionally, applying SSM requires trajectory data which can be hardly obtained from video processing or calibrated microsimulations. Estimating safety level in different parts of freeway interchanges through a new proposed method was considered in this paper. Fuzzy logic was applied to combine the outputs of different SSMs, and an index called no-collision potential index (NCPI) was defined. 13608 calibrated simulations were conducted on different ramps, weaving, merge, and diverge areas with different geometrical and traffic characteristics, and NCPI was determined for every case. The geometrical and traffic characteristics formed input data of two safety estimator models developed by Artificial Neural Network and Particle Swarm Optimization. Ten freeway interchanges were investigated to calibrate the simulations and to ensure the validity of the fuzzy method and accuracy of the models. Results showed an appropriate and accurate development of the models.

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.

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