Automated Driving System Collisions: Early Lessons

2019 ◽  
Vol 62 (2) ◽  
pp. 249-259 ◽  
Author(s):  
Wayne Biever ◽  
Linda Angell ◽  
Sean Seaman
Keyword(s):  
Human Error ◽  
Autonomous Systems ◽  
Motor Vehicles ◽  
Transportation Safety ◽  
Automated Driving ◽  
California Department ◽  
New Class ◽  
Side Impacts ◽  
Road Users ◽  
Lane Keeping

Objective This research evaluated Automated Driving Systems (ADSs) involved collisions to identify factors relevant to future ADS research and development. Background Rapidly developing ADSs promise improved safety, among other benefits. Properly applied collision research can inform ADS development, to minimize future collisions. Errors and failures that result in collisions come from sources including the system, ADS operators, and external factors including other drivers. Partially automated systems incorporate new equipment and procedures creating new sources of human error. Fully autonomous systems represent a new class of drivers that interact in unique ways. Method ADS collision reports from the California Department of Motor Vehicles and the National Transportation Safety Board were collected. An expert in human factors and collision investigation analyzed and categorized the crashes while extracting common factors. Results ADS vehicles were never at fault but were often affected from the rear during braking, turning, and gap acceptance maneuvers. Side impacts to ADS vehicles were related to passing vehicles and lane keeping behaviors. Unique incidents also provided additional insights. ADS collision rates cannot yet be determined with confidence. Conclusion Conflicts that lead to collision-involvement with ADSs may be caused by differences between ADS and human driving behavior. Conservative ADS behavior may violate the expectations of other nearby human road users. Application The findings from this work help inform the future development of ADS, as well as potentially the testing of ADS and the formation of policy to guide their future deployment.

Extracting Rules from Autonomous-Vehicle-Involved Crashes by Applying Decision Tree and Association Rule Methods

2021 ◽  
pp. 036119812110184
Author(s):  
Md Tanvir Ashraf ◽  
Kakan Dey ◽  
Sabyasachee Mishra ◽  
Md Tawhidur Rahman
Keyword(s):  
Decision Tree ◽  
Association Rule ◽  
Autonomous Vehicles ◽  
Human Error ◽  
Autonomous Vehicle ◽  
Motor Vehicles ◽  
Operational Mode ◽  
Contributing Factors ◽  
California Department ◽  
Transportation Agencies

Autonomous vehicles (AVs) can dramatically reduce the number of traffic crashes and associated fatalities by eliminating the avoidable human-error-related crash contributing factors. Many companies have been conducting pilot tests on public roads in several states in the U.S. and other countries to accelerate AV mass deployment. AV pilot operations on Californian public roads saw 251 AV-involved crashes (as of February 2020). These AV-involved crashes provide a unique opportunity to investigate AV crash risks in the mixed traffic environment. This study collected the AV crash reports from the California Department of Motor Vehicles and applied the decision tree and association rule methods to extract the pre-crash rules of AV-involved crashes. Extracted rules revealed that the most frequent types of AV crashes were rear-end crashes and predominantly occurred at intersections when AVs were stopped and engaged in the autonomous mode. AV and non-AV manufacturers and transportation agencies can use the findings of this study to minimize AV-related crashes. AV companies could install a distinct signal/display to inform the operational mode of the AVs (i.e., autonomous or non-autonomous) to human drivers around them. Moreover, the automatic emergency braking system in non-AVs could avoid a significant number of rear-end crashes as, often, rear-end crashes occurred as a result of the failure of following non-AVs to slow down in time behind AVs. Transportation agencies can consider separating AVs from non-AVs by assigning “AV Only” lanes to eliminate the excessive rear-end crashes resulting from the mistakes of human drivers in non-AVs at intersections.

scholarly journals Contrasting Perspectives on the Comfort and Safety of Pedestrians Interacting with Other Road Users

2021 ◽  
Vol 2675 (3) ◽  
pp. 33-43
Author(s):  
Alexander Bigazzi ◽  
Gurdiljot Gill ◽  
Meghan Winters
Keyword(s):  
Traffic Safety ◽  
Injury Risk ◽  
Road User ◽  
Motor Vehicles ◽  
Advisory Group ◽  
User Interactions ◽  
The Public ◽  
Road Users ◽  
Expert Assessments ◽  
Sample Representation

Assessments of interactions between road users are crucial to understanding comfort and safety. However, observers may vary in their perceptions and ratings of road user interactions. The objective of this paper is to examine how perceptions of yielding, comfort, and safety for pedestrian interactions vary among observers, ranging from members of the public to road safety experts. Video clips of pedestrian interactions with motor vehicles and bicycles were collected from 11 crosswalks and shown to three groups of participants (traffic safety experts, an engaged citizen advisory group, and members of the general public) along with questions about yielding, comfort, and risk of injury. Experts had similar views of yielding and comfort to the other two groups, but a consistently lower assessment of injury risk for pedestrians in the study. Respondent socio-demographics did not relate to perceptions of yielding, comfort, or risk, but self-reported travel habits did. Respondents who reported walking more frequently rated pedestrian comfort as lower, and respondents who reported cycling more frequently rated risk as lower for pedestrian interactions with both motor vehicles and bicycles. Findings suggest small groups of engaged citizens can provide useful information about public perspectives on safety that likely diverge from expert assessments of risk, and that sample representation should be assessed in relation to travel habits rather than socio-demographics.

scholarly journals Supervision of a self-driving vehicle unmasks latent sleepiness relative to manually controlled driving

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Erin E. Flynn-Evans ◽  
Lily R. Wong ◽  
Yukiyo Kuriyagawa ◽  
Nikhil Gowda ◽  
Patrick F. Cravalho ◽  
...  
Keyword(s):  
Human Error ◽  
Reaction Times ◽  
Modern Society ◽  
Accident Risk ◽  
Road Accidents ◽  
Automated Driving ◽  
High Prevalence ◽  
Driving Task ◽  
Sleep Deficiency ◽  
Monitoring Performance

AbstractHuman error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had more involuntary transitions to sleep, had slower reaction times and more attentional failures, and showed substantial modifications in brain synchronization during and following an autonomous drive compared to a manually controlled drive. Our findings suggest that the introduction of partial self-driving capabilities in vehicles has the potential to paradoxically increase accident risk.

scholarly journals Arduino-Based Railway Arrival Detection And Name Detection Design At A Level Crossing

2017 ◽  
Vol 1 (2) ◽  
pp. 139-147
Author(s):  
Sunaryo Sunaryo ◽  
Wawan Hermanto
Keyword(s):  
Cross Section ◽  
Transportation Safety ◽  
Design Phase ◽  
Arrival Direction ◽  
Literature Study ◽  
Level Crossing ◽  
Road Users ◽  
Arduino Microcontroller ◽  
Alternative Solutions ◽  
Section Level

Transportation safety must be obeyed by all modes of transportation. The railroad crossing is one point that has the potential for conflict between railroad shares and road users. In accordance with applicable regulations, railroad facilities are prioritized when passing level crossings. In fact, road users often try to break the rules. This research aims to present alternative solutions to improve the safety of road users and railroad lines at cross section level. This research uses a method that begins with a literature study. Next through the design phase, the prototype stage and finally the testing phase. The results of this study are the prototype of the railroad direction detector and the identification of electronic-based railways by using an Arduino Microcontroller. The result shows an LCD board that can provide information to road users for the train's arrival direction and train name. With this information it is expected that road users are more concerned with safety and can be careful when passing a level crossing.

scholarly journals An adaptive model predictive approach for automated vehicle control in fallback procedure based on virtual vehicle scheme

2019 ◽  
Vol 2 (2) ◽  
pp. 67-77
Author(s):  
Wei Xue ◽  
Rencheng Zheng ◽  
Bo Yang ◽  
Zheng Wang ◽  
Tsutomu Kaizuka ◽  
...  
Keyword(s):  
Path Planning ◽  
Human Error ◽  
Driving Safety ◽  
Planning Problem ◽  
Adaptive Model ◽  
Sensor Failure ◽  
Automated Driving ◽  
Content Type ◽  
Automated Vehicle ◽  
Virtual Vehicle

Purpose Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction. Design/methodology/approach Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes. Findings It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios. Originality/value This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

Do Autonomous Vehicle Driving Styles Affect User State?: A Preliminary Investigation

2019 ◽  
Author(s):  
Yuan Shi ◽  
Wenhui Huang ◽  
Federico Cheli ◽  
Monica Bordegoni ◽  
Giandomenico Caruso
Keyword(s):  
Driving Simulator ◽  
Autonomous Vehicle ◽  
Preliminary Investigation ◽  
Autonomous Systems ◽  
Autonomous Driving ◽  
Point Of View ◽  
Automated Driving ◽  
Perspective View ◽  
Self Assessment ◽  
Driving Experience

Abstract A bursting number of achievements in the autonomous vehicle industry have been obtained during the past decades. Various systems have been developed to make automated driving possible. Due to the algorithm used in the autonomous vehicle system, the performance of the vehicle differs from one to another. However, very few studies have given insight into the influence caused by implementing different algorithms from a human factors point of view. Two systems based on two algorithms with different characteristics are utilized to generate the two driving styles of the autonomous vehicle, which are implemented into a driving simulator in order to create the autonomous driving experience. User’s skin conductance (SC) data, which enables the evaluation of user’s cognitive workload and mental stress were recorded and analyzed. Subjective measures were applied by filling out Swedish occupational fatigue inventory (SOFI-20) to get a user self-reporting perspective view of their behavior changes along with the experiments. The results showed that human’s states were affected by the driving styles of different autonomous systems, especially in the period of speed variation. By analyzing users’ self-assessment data, a correlation was observed between the user “Sleepiness” and the driving style of the autonomous vehicle. These results would be meaningful for the future development of the autonomous vehicle systems, in terms of balancing the performance of the vehicle and user’s experience.

scholarly journals Factors related to road system organisation and its association with mortality due to motor vehicle-pedestrian collisions in Guadalajara Metropolitan Area

2019 ◽  
Vol 26 (3) ◽  
pp. 270-278
Author(s):  
Melva Guadalupe Herrera-Godina ◽  
Berenice Martínez-Melendres ◽  
Hiram René Novelo-Ramírez ◽  
Julio Cesar Dávalos-Guzmán ◽  
Alfredo Celis ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Metropolitan Area ◽  
Motor Vehicle ◽  
Temporal Analysis ◽  
Motor Vehicles ◽  
Urban Network ◽  
The Road ◽  
Road Users ◽  
Multiple Theory ◽  
Road System

IntroductionTraffic events are one of the five leading causes of mortality in Mexico. Pedestrians are one of the main road users involved in such incidents and have the highest mortality rate, which is regularly analysed in relation to vehicles and pedestrians, but not the built environment. The purpose of this study was to analyse the elements of the road system organisation that influences the mortality rate of pedestrians hit by motor vehicles in the Guadalajara Metropolitan Area.MethodWe designed a case and control study in which the cases were sites where a pedestrian died during 2012. The controls were sites close to where the death occurred, as well as those with road infrastructure characteristics similar to those where the events took place. We obtained the pedestrian data from the death certificates and assessed some of the environmental elements of the road sites. A logistic regression analysis was used to estimate OR; 95% CI.ResultsRoad system factors related with pedestrian mortality in close locations were: the presence of bus stops on intersections in one street or both, and road system features, such as the presence of traffic islands, vehicle flow and pedestrian flow.ConclusionsAccording to the urban network theory and multiple theory, the final elements resulted as risk factors due to a fault in connectivity between the nodes. A temporal analysis of urban features will help urban planners make decisions regarding the safety of pedestrians and other road users.

Relationship of Field Dependence and Motor-Vehicle-Accident Involvement

1970 ◽  
Vol 31 (1) ◽  
pp. 272-274 ◽  
Author(s):  
Richard M. Harano
Keyword(s):  
Field Dependence ◽  
Traffic Safety ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Motor Vehicles ◽  
Future Research ◽  
California Department ◽  
Research Survey ◽  
Vehicle Accident ◽  
Relationship Of

A group of 28 accident and 27 accident-free drivers were requested by the California Department of Motor Vehicles to participate in a Driver Research Survey, the purpose being to evaluate the relationship between field dependence and motor-vehicle-accident involvement. The multiple regression results indicated that field dependence was significantly related to accident involvement. The results suggest that measures of perceptual style such as field dependence may hold promise for future research in traffic safety.

scholarly journals Functional Resonance Analysis in an Overtaking Situation in Road Traffic: Comparing the Performance Variability Mechanisms between Human and Automation

Safety ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 3
Author(s):  
Niklas Grabbe ◽  
Alain Gales ◽  
Michael Höcher ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Human Error ◽  
Driving Simulator ◽  
Road Traffic ◽  
Structured Interviews ◽  
Automated Driving ◽  
Design Recommendations ◽  
Resonance Analysis ◽  
Performance Variability ◽  
Human Driver

Automated driving promises great possibilities in traffic safety advancement, frequently assuming that human error is the main cause of accidents, and promising a significant decrease in road accidents through automation. However, this assumption is too simplistic and does not consider potential side effects and adaptations in the socio-technical system that traffic represents. Thus, a differentiated analysis, including the understanding of road system mechanisms regarding accident development and accident avoidance, is required to avoid adverse automation surprises, which is currently lacking. This paper, therefore, argues in favour of Resilience Engineering using the functional resonance analysis method (FRAM) to reveal these mechanisms in an overtaking scenario on a rural road to compare the contributions between the human driver and potential automation, in order to derive system design recommendations. Finally, this serves to demonstrate how FRAM can be used for a systemic function allocation for the driving task between humans and automation. Thus, an in-depth FRAM model was developed for both agents based on document knowledge elicitation and observations and interviews in a driving simulator, which was validated by a focus group with peers. Further, the performance variabilities were identified by structured interviews with human drivers as well as automation experts and observations in the driving simulator. Then, the aggregation and propagation of variability were analysed focusing on the interaction and complexity in the system by a semi-quantitative approach combined with a Space-Time/Agency framework. Finally, design recommendations for managing performance variability were proposed in order to enhance system safety. The outcomes show that the current automation strategy should focus on adaptive automation based on a human-automation collaboration, rather than full automation. In conclusion, the FRAM analysis supports decision-makers in enhancing safety enriched by the identification of non-linear and complex risks.

scholarly journals Radio and microprocessor technology for ensuring railway transport safety.

2021 ◽  
Vol 1 ◽  
pp. 126-134
Author(s):  
Ar.A. Mukha ◽  
◽  
O.V. Fedukhin ◽  
Keyword(s):  
Information Systems ◽  
Traffic Safety ◽  
Rail Transport ◽  
Digital Information ◽  
Service Personnel ◽  
New Class ◽  
Autonomous Operation ◽  
Road Users ◽  
Microprocessor Technology ◽  
High Level

The need to minimize losses and accidents is an important factor in sustainable technical development. One of the industries characterized by a high level of danger is rail transport. This problem changes its scale with the increase in the number of vehicles, its traffic intensity and speed. Another special diffi-culty is that significant infrastructural development, which involves the construction of a large number of complex and expensive facilities such as interchanges, overpasses and underpasses, is impossible in today's economic environment. Therefore, there are some promising solutions aimed at developing and implementing a new class of systems that provide a high level of safety and are able to correct negative accident statistics and solve the problem of not harming people's lives on rail transport. The article is devoted to the problem of traffic safety at railway crossings, railway crosswalks and in the work areas of service personnel. An information approach aimed at improving traffic safety and timely informing road users about emergencies and dangerous situations in their area approach is developed in the work. It is offered to solve the mentioned above tasks at the expense of the creation of digital information systems of a new class. The main differences between the created systems are the use of microprocessor systems, wireless communications and energy-saving technologies. The systems themselves must meet modern requirements for reliability, fault tolerance, and dependability. The article describes some basic options for the implementation of control and information systems for railway crossings «Blagovist», railway crosswalks «Blagovist-Р» and for a mobile system for service personnel working on the tracks «Blago-vist-SP». The systems have technologies for autonomous operation and wireless transmission of infor-mation.

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