What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys

2022 ◽  
Vol 176 ◽  
pp. 121454
Author(s):  
Yingying Xing ◽  
Huiyu Zhou ◽  
Xiao Han ◽  
Meng Zhang ◽  
Jian Lu
Keyword(s):  
Comparative Analysis ◽  
Autonomous Vehicles ◽  
Road Users ◽  
Vulnerable Road Users

scholarly journals Autonomous Vehicles and Vulnerable Road-Users—Important Considerations and Requirements Based on Crash Data from Two Countries

2021 ◽  
Vol 11 (7) ◽  
pp. 101
Author(s):  
Andrew Paul Morris ◽  
Narelle Haworth ◽  
Ashleigh Filtness ◽  
Daryl-Palma Asongu Nguatem ◽  
Laurie Brown ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Red Light ◽  
Road User ◽  
Red Light Running ◽  
Crash Data ◽  
Passenger Vehicles ◽  
Road Users ◽  
Vulnerable Road User ◽  
Vulnerable Road Users ◽  
Road Intersections

(1) Background: Passenger vehicles equipped with advanced driver-assistance system (ADAS) functionalities are becoming more prevalent within vehicle fleets. However, the full effects of offering such systems, which may allow for drivers to become less than 100% engaged with the task of driving, may have detrimental impacts on other road-users, particularly vulnerable road-users, for a variety of reasons. (2) Crash data were analysed in two countries (Great Britain and Australia) to examine some challenging traffic scenarios that are prevalent in both countries and represent scenarios in which future connected and autonomous vehicles may be challenged in terms of safe manoeuvring. (3) Road intersections are currently very common locations for vulnerable road-user accidents; traffic flows and road-user behaviours at intersections can be unpredictable, with many vehicles behaving inconsistently (e.g., red-light running and failure to stop or give way), and many vulnerable road-users taking unforeseen risks. (4) Conclusions: The challenges of unpredictable vulnerable road-user behaviour at intersections (including road-users violating traffic or safe-crossing signals, or taking other risks) combined with the lack of knowledge of CAV responses to intersection rules, could be problematic. This could be further compounded by changes to nonverbal communication that currently exist between road-users, which could become more challenging once CAVs become more widespread.

Approaching autonomous driving with cautious optimism: analysis of road traffic injuries involving autonomous vehicles based on field test data

2020 ◽  
pp. injuryprev-2019-043402
Author(s):  
Wanbao Ye ◽  
Chuanlin Wang ◽  
Fuxiang Chen ◽  
Shuzhen Yan ◽  
Liping Li
Keyword(s):  
Traffic Safety ◽  
Autonomous Vehicles ◽  
Road Traffic ◽  
Statistical Significance ◽  
Autonomous Driving ◽  
Road Traffic Injuries ◽  
Road Traffic Safety ◽  
Road Users ◽  
Vulnerable Road Users ◽  
Poor Lighting

ObjectivesTo examine the patterns and associated factors of road traffic injuries (RTIs) involving autonomous vehicles (AVs) and to discuss the public health implications and challenges of autonomous driving.MethodsData were extracted from the reports of traffic crashes involving AVs. All the reports were submitted to the California Department of Motor Vehicles by manufacturers with permission to operate AV test on public roads. Descriptive analysis and χ2 analysis or Fisher’s exact test was conducted to describe the injury patterns and to examine the influencing factors of injury outcomes, respectively. Binary logistic regression using the Wald test was employed to calculate the OR, adjusted OR (AOR) and 95% CIs. A two-tailed probability (p<0.05) was adopted to indicate statistical significance.Results133 reports documented 24 individuals injured in 19 crashes involving AVs, with the overestimated incidence rate of 18.05 per 100 crashes. 70.83% of the injured were AV occupants, replacing vulnerable road users as the leading victims. Head and neck were the most commonly injured locations. Driving in poor lighting was at greater risk of RTIs (AOR 6.37, 95% CI 1.47 to 27.54). Collisions with vulnerable road users or incidents happening during commute periods led to a greater number of victims (p<0.05). Autonomous mode cannot perform better than conventional mode in road traffic safety to date (p=0.468).ConclusionsPoor lighting improvement and the regulation of commute-period traffic and vulnerable road users should be strengthened for AV-related road safety. So far AVs have not demonstrated the potential to dramatically reduce RTIs. Cautious optimism about AVs is more advisable, and multifaceted efforts, including legislation, smarter roads, and knowledge dissemination campaigns, are fairly required to accelerate the development and acceptance.

scholarly journals Generation of Pedestrian Crossing Scenarios Using Ped-Cross Generative Adversarial Network

2021 ◽  
Vol 11 (2) ◽  
pp. 471
Author(s):  
James Spooner ◽  
Vasile Palade ◽  
Madeline Cheah ◽  
Stratis Kanarachos ◽  
Alireza Daneshkhah
Keyword(s):  
Autonomous Vehicles ◽  
Generative Adversarial Networks ◽  
Automated Driving ◽  
Real World Data ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Road Users ◽  
Vulnerable Road Users ◽  
Human Pose ◽  
Pedestrian Crossing

The safety of vulnerable road users is of paramount importance as transport moves towards fully automated driving. The richness of real-world data required for testing autonomous vehicles is limited and furthermore, available data do not present a fair representation of different scenarios and rare events. Before deploying autonomous vehicles publicly, their abilities must reach a safety threshold, not least with regards to vulnerable road users, such as pedestrians. In this paper, we present a novel Generative Adversarial Networks named the Ped-Cross GAN. Ped-Cross GAN is able to generate crossing sequences of pedestrians in the form of human pose sequences. The Ped-Cross GAN is trained with the Pedestrian Scenario dataset. The novel Pedestrian Scenario dataset, derived from existing datasets, enables training on richer pedestrian scenarios. We demonstrate an example of its use through training and testing the Ped-Cross GAN. The results show that the Ped-Cross GAN is able to generate new crossing scenarios that are of the same distribution from those contained in the Pedestrian Scenario dataset. Having a method with these capabilities is important for the future of transport, as it will allow for the adequate testing of Connected and Autonomous Vehicles on how they correctly perceive the intention of pedestrians crossing the street, ultimately leading to fewer pedestrian casualties on our roads.

scholarly journals Pedestrian and Cyclist Detection and Intent Estimation for Autonomous Vehicles: A Survey

2019 ◽  
Vol 9 (11) ◽  
pp. 2335 ◽  
Author(s):  
Sarfraz Ahmed ◽  
M. Nazmul Huda ◽  
Sujan Rajbhandari ◽  
Chitta Saha ◽  
Mark Elshaw ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Pedestrian Detection ◽  
Accurate Method ◽  
Single Shot ◽  
Road Users ◽  
Recent Developments ◽  
Tracking Motion ◽  
Vulnerable Road Users ◽  
Fast Region

As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection and intent estimation to increase the safety of autonomous vehicles, for both the driver and other road users. Understanding the intentions of the pedestrian/cyclist enables the self-driving vehicle to take actions to avoid incidents. To make this possible, development of methods/techniques, such as deep learning (DL), for the autonomous vehicle will be explored. For example, the development of pedestrian detection has been significantly advanced using DL approaches, such as; Fast Region-Convolutional Neural Network (R-CNN) , Faster R-CNN and Single Shot Detector (SSD). Although DL has been around for several decades, the hardware to realise the techniques have only recently become viable. Using these DL methods for pedestrian and cyclist detection and applying it for the tracking, motion modelling and pose estimation can allow for a successful and accurate method of intent estimation for the vulnerable road users. Although there has been a growth in research surrounding the study of pedestrian detection using vision-based approaches, further attention should include focus on cyclist detection. To further improve safety for these vulnerable road users (VRUs), approaches such as sensor fusion and intent estimation should be investigated.

Pedestrians/Bicyclists and Autonomous Vehicles: How Will They Communicate?

2018 ◽  
Vol 2672 (22) ◽  
pp. 58-66 ◽  
Author(s):  
Sergiu C. Stanciu ◽  
David W. Eby ◽  
Lisa J. Molnar ◽  
Renée M. St. Louis ◽  
Nicole Zanier ◽  
...  
Keyword(s):  
Interpersonal Communication ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Connected Vehicle ◽  
Road Users ◽  
Search Terms ◽  
Roadway Safety ◽  
Vulnerable Road Users ◽  
Vital Component ◽  
Communication Methods

Interpersonal roadway communication is a vital component of the transportation system. Road users communicate to coordinate movement and increase roadway safety. Future autonomous vehicle research needs to account for the role of interpersonal roadway communication. This literature review synthesizes research on interpersonal interaction between drivers, bicyclists, and pedestrians while also directing attention to implications for autonomous and connected vehicle research. Articles were collected from TRID, PsycINFO, Google Scholar, and ScienceDirect using search terms relevant to driving, communication, and vulnerable road users. The synthesis documents that interpersonal communication not only takes place but is also an important and understudied aspect of safe roadway travel. The review also found that road users employ a variety of communication methods that include gestures, facial expressions, and built-in vehicular devices. Comprehension of messages is influenced by several factors including culture, context, and experience. These results shed light on potential issues and challenges of interpersonal communication and the introduction of autonomous vehicles to the roadway.

scholarly journals The Role of Human Operators in Safety Perception of AV Deployment—Insights from a Large European Survey

2020 ◽  
Vol 12 (21) ◽  
pp. 9166
Author(s):  
Miltos Kyriakidis ◽  
Jaka Sodnik ◽  
Kristina Stojmenova ◽  
Arnór B. Elvarsson ◽  
Cristina Pronello ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Online Survey ◽  
The Elderly ◽  
The Public ◽  
Road Users ◽  
Gender Education ◽  
Vulnerable Road Users ◽  
Human Operators ◽  
Willingness To Use ◽  
Transport Problems

Autonomous vehicles are anticipated to play an important role on future mobility offering encouraging solutions to today’s transport problems. However, concerns of the public, which can affect the AVs’ uptake, are yet to be addressed. This study presents relevant findings of an online survey in eight European countries. First, 1639 responses were collected in Spring 2020 on people’s commute, preferred transport mode, willingness to use AVs and demographic details. Data was analyzed for the entire dataset and for vulnerable road users in particular. Results re-confirm the long-lasting discourse on the importance of safety on the acceptance of AVs. Spearman correlations show that age, gender, education level and number of household members have an impact on how people may be using or allowing their children to use the technology, e.g., with or without the presence of a human supervisor in the vehicle. Results on vulnerable road users show the same trend. The elderly would travel in AVs with the presence of a human supervisor. People with disabilities have the same proclivity, however their reactions were more conservative. Next to safety, reliability, affordability, cost, driving pleasure and household size may also impact the uptake of AVs and shall be considered when designing relevant policies.

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