scholarly journals Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

2020 ◽  
Vol 11 ◽  
Author(s):  
Michal Hochman ◽  
Yisrael Parmet ◽  
Tal Oron-Gilad

This study explored pedestrians’ understanding of Fully Autonomous Vehicles (FAVs) intention to stop and what influences pedestrians’ decision to cross the road over time, i.e., learnability. Twenty participants saw fixed simulated urban road crossing scenes with a single FAV on the road as if they were pedestrians intending to cross. Scenes differed from one another in the FAV’s, distance from the crossing place, its physical size, and external Human-Machine Interfaces (e-HMI) message by background color (red/green), message type (status/advice), and presentation modality (text/symbol). Eye-tracking data and decision measurements were collected. Results revealed that pedestrians tend to look at the e-HMI before making their decision. However, they did not necessarily decide according to the e-HMIs’ color or message type. Moreover, when they complied with the e-HMI proposition, they tended to hesitate before making the decision. Overall, a learning effect over time was observed in all conditions regardless of e- HMI features and crossing context. Findings suggest that pedestrians’ decision making depends on a combination of the e-HMI implementation and the car distance. Moreover, since the learning curve exists in all conditions and has the same proportion, it is critical to design an interaction that would encourage higher probability of compatible decisions from the first phase. However, to extend all these findings, it is necessary to further examine dynamic situations.

Author(s):  
Michal Hochman ◽  
Tal Oron-Gilad

This study explored pedestrians’ understanding of Fully Autonomous Vehicle (FAV) intention and what influences their decision to cross. Twenty participants saw fixed simulated urban road crossing scenes with a FAV present on the road. The scenes differed from one another in the FAV’s messages: the external Human-Machine Interfaces (e-HMI) background color, message type and modality, the FAV’s distance from the crossing place, and its size. Eye-tracking data and objective measurements were collected. Results revealed that pedestrians looked at the e-HMI before making their decision; however, they did not always make the decision according to the e-HMIs’ color, instructions (in advice messages), or intention (in status messages). Moreover, when they acted according to the e-HMI proposition, for certain distance conditions, they tended to hesitate before making the decision. Findings suggest that pedestrians’ decision making to cross depends on a combination of the e-HMI implementation and the car distance. Future work should explore the robustness of the findings in dynamic and more complex crossing environments.


Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.


2020 ◽  
Author(s):  
Baoshan Wang ◽  
Xiangfang Zeng ◽  
Jun Yang ◽  
Yuansheng Zhang ◽  
Zhenghong Song ◽  
...  

<p>Recently large-volume airgun arrays have been used to explore and monitor the subsurface structure. The airgun array can generate highly repeatable seismic signals, which can be traced to more than 200 km. And the airgun source can be ignited every 10 minutes. The airgun source makes it possible to precisely monitor subsurface changes at large scale. The spatial resolution of airgun monitoring is poor subjecting to the receiver distribution. The distributed acoustic sensing (DAS) technique provides a strategy for low-cost and high-density seismic observations. Two experiments combing DAS technique and airgun source were conducted at two sites with different settings. At the first site, a telecommunication fiber-optic cable in urban area was used. After moderate stacking, the airgun signal emerges on the 30-km DAS array at about 9 km epicentral distance. In the second experiment, a 5-km cable was deployed from the airgun source to about 2 km away. About 800-m cable was frozen into the ice above the air-gun, the rest cable was cemented on the road crossing through a fault. And the airgun has been fired continuously for more than 48 hours with one-hour interval. On the stacking multiple shots’ records, the wavefield in fault zone emerges too. These two experiments demonstrate the feasibility of using various fiber-optic cables as dense array to acquire air-gun signal in different environments and to monitor the subsurface changes.</p>


2015 ◽  
Vol 27 (6) ◽  
pp. 660-670 ◽  
Author(s):  
Udara Eshan Manawadu ◽  
◽  
Masaaki Ishikawa ◽  
Mitsuhiro Kamezaki ◽  
Shigeki Sugano ◽  
...  

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/08.jpg"" width=""300"" /> Driving simulator</div>Intelligent passenger vehicles with autonomous capabilities will be commonplace on our roads in the near future. These vehicles will reshape the existing relationship between the driver and vehicle. Therefore, to create a new type of rewarding relationship, it is important to analyze when drivers prefer autonomous vehicles to manually-driven (conventional) vehicles. This paper documents a driving simulator-based study conducted to identify the preferences and individual driving experiences of novice and experienced drivers of autonomous and conventional vehicles under different traffic and road conditions. We first developed a simplified driving simulator that could connect to different driver-vehicle interfaces (DVI). We then created virtual environments consisting of scenarios and events that drivers encounter in real-world driving, and we implemented fully autonomous driving. We then conducted experiments to clarify how the autonomous driving experience differed for the two groups. The results showed that experienced drivers opt for conventional driving overall, mainly due to the flexibility and driving pleasure it offers, while novices tend to prefer autonomous driving due to its inherent ease and safety. A further analysis indicated that drivers preferred to use both autonomous and conventional driving methods interchangeably, depending on the road and traffic conditions.


Behaviour ◽  
2017 ◽  
Vol 154 (12) ◽  
pp. 1215-1237 ◽  
Author(s):  
Kaori Mizuno ◽  
Nachiketha Sharma ◽  
Gen’ichi Idani ◽  
Raman Sukumar

Among group-living animals, some members may derive benefit by following the decisions of other members. Free-ranging wild Asian elephants in Mudumalai National Park, southern India, must often cross roads and can be disturbed by vehicles. We assessed if measures of road and traffic characteristics serve as indicators of risk, and compared behaviours of different age classes during road-crossing events. More individuals displayed excitable behaviour on wider roads. A larger number of adults entered the road first, which is considered the most dangerous position, compared with immature elephants. Immature individuals tended to move ahead of others on the road, suggesting that it is more important for immature individuals to follow adults at the beginning of a crossing than to follow along for the entire crossing. These findings may suggest that less experienced group members derive benefit by following the decisions of experienced ones under risky situations.


Author(s):  
Yiqi Gao ◽  
Theresa Lin ◽  
Francesco Borrelli ◽  
Eric Tseng ◽  
Davor Hrovat

Two frameworks based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented. A given trajectory represents the driver intent. An MPC has to safely avoid obstacles on the road while trying to track the desired trajectory by controlling front steering angle and differential braking. We present two different approaches to this problem. The first approach solves a single nonlinear MPC problem. The second approach uses a hierarchical scheme. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model in order to avoid an obstacle. At the low-level an MPC controller computes the vehicle inputs in order to best follow the high level trajectory based on a nonlinear vehicle model. This article presents the design and comparison of both approaches, the method for implementing them, and successful experimental results on icy roads.


2021 ◽  
Vol 11 (17) ◽  
pp. 7984
Author(s):  
Prabu Subramani ◽  
Khalid Nazim Abdul Sattar ◽  
Rocío Pérez de Prado ◽  
Balasubramanian Girirajan ◽  
Marcin Wozniak

Connected autonomous vehicles (CAVs) currently promise cooperation between vehicles, providing abundant and real-time information through wireless communication technologies. In this paper, a two-level fusion of classifiers (TLFC) approach is proposed by using deep learning classifiers to perform accurate road detection (RD). The proposed TLFC-RD approach improves the classification by considering four key strategies such as cross fold operation at input and pre-processing using superpixel generation, adequate features, multi-classifier feature fusion and a deep learning classifier. Specifically, the road is classified as drivable and non-drivable areas by designing the TLFC using the deep learning classifiers, and the detected information using the TLFC-RD is exchanged between the autonomous vehicles for the ease of driving on the road. The TLFC-RD is analyzed in terms of its accuracy, sensitivity or recall, specificity, precision, F1-measure and max F measure. The TLFC- RD method is also evaluated compared to three existing methods: U-Net with the Domain Adaptation Model (DAM), Two-Scale Fully Convolutional Network (TFCN) and a cooperative machine learning approach (i.e., TAAUWN). Experimental results show that the accuracy of the TLFC-RD method for the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) dataset is 99.12% higher than its competitors.


Author(s):  
Susan Signe Morrison

      To show the intellectual roots of environmental citizenship, this essay transverses literary and ecological paths by focusing on medieval pilgrimage poems. While design seems integral to the concept of pilgrimage—wayfaring from one’s home to a sacred shrine—in actuality pilgrims not infrequently wandered from the official path. Contingency, rather than randomness, acts as a dynamic agent in affecting the meanderings of the pilgim-walker.Pilgrimage practice entailed reading the landscape through slow walking. Slow pilgrimage manifests itself in major ways: the slow change in the vernacular language of fourteenth-century pilgrimage poems; the slow amendment pilgrimage is meant to spark spiritually; the slow somatic travail on the road itself; and the act of slowly reading as a form of textual wayfinding. The pilgrimage road, which amends over time, itself works within a diverse ecotone, replete with various pilgrims and pilgrimage works.Literary pilgrimage poems self-consciously commit themselves to promoting the vernacular. The ecopoetics of a specific “landguage,” the living and resilient vernacular used by medieval pilgrimage writers, sparks amendment—the spiritual change pilgrimage was meant to kindle. Amendment recurs thematically, indicating material change in the actual path walked on by historical pilgrims.Pilgrim readers undertook textual wayfaring, as do pilgrim-writers through variant texts amended by the poet himself. A strategy of slow ecopoetics authorizes the reader to co-perform the text, making author, reader, and text all kin. Just as the pilgrim presses ahead through a new space, creating the “edge effect” with each step, the pilgrim reader advances alongside the writer, co-creating a resilient literary work. Resumen          Analizando los poemas medievales del siglo XIV relacionados con la peregrinación y comparando estos con otros textos más contemporáneos, este ensayo explora cómo los elementos inherentes a la eco-poética del peregrinaje oscilan entre lo diseñado y lo casual, tanto a nivel literal como literario. Pese a que su construcción se vehicula a través del concepto de la peregrinación, con elementos temáticos basados en el viaje desde el hogar a un santuario sagrado, lo cierto es que los peregrinos frecuentemente se desviaban. La contingencia, en lugar de la casualidad, funciona como un agente dinámico que afecta a los desvíos del caminante-peregrino.El lento andar de los peregrinos contribuyó a una eco-poética de la lentitud: el  lento ejercicio de seguir el camino; el lento cambio en la lengua vernácula que se empleaba para articular la poesía de la peregrinación; la lenta transformación espiritual provocada, idóneamente, por los actos de peregrinar, caminar, o leer; y la lectura mesurada en sí hecha como forma de un lento peregrinaje.La enmienda se repite temáticamente en estos textos como concepto y término indicando cambios materiales, espirituales, lingüísticos, y poéticos—los caminos materiales modificados por los peregrinos históricos que los pisaban y seguían. Estas modificaciones corresponden de forma análoga al espectro literario, donde algunas versiones rivales de los poemas medievales sobre la peregrinación eran enmendados y editados por sus autores. Los poemas literarios de peregrinación promueven conscientemente lo vernáculo. La eco-poética de una lengua vernácula viva, o la “topo-poética”, usada por los autores medievales es lo que motiva el cambio espiritual que pretende provocar la peregrinación.Los lectores-peregrinos emprendían un deambular textual tal como hacían los autores-peregrinos por medio de los textos variados que el propio poeta modificaba. Una de las estrategias de la eco-poética lenta es permitir que el lector coopere en la interpretación del texto, avanzando así junto al autor para crear una obra literaria que responda a un público heterogéneo. Como resultado del no ser maestros del diseño sino seres errantes y contingentes del medio ambiente y de la poesía, los peregrinos—históricos y literarios—contribuyen a la existencia de una adaptabilidad vibrante, como lo ejemplifica la lenta eco-poética de la peregrinación.


2020 ◽  
Vol 9 (2) ◽  
pp. 155-191
Author(s):  
Sarah Stutts ◽  
Kenneth Saintonge ◽  
Nicholas Jordan ◽  
Christina Wasson

Roadways are sociocultural spaces constructed for human travel which embody intersections of technology, transportation, and culture. In order to navigate these spaces successfully, autonomous vehicles must be able to respond to the needs and practices of those who use the road. We conducted research on how cyclists, solid waste truck drivers, and crossing guards experience the driving behaviors of other road users, to inform the development of autonomous vehicles. We found that the roadways were contested spaces, with each road user group enacting their own social constructions of the road. Furthermore, the three groups we worked with all felt marginalized by comparison with car drivers, who were ideologically and often physically dominant on the road. This article is based on research for the Nissan Research Center - Silicon Valley, which took place as part of a Design Anthropology course at the University of North Texas.


Author(s):  
Simon Roberts

The CoDRIVE solution builds on R&amp;amp;D in the development of connected and autonomous vehicles (CAVs). The mainstay of the system is a low-cost GNSS receiver integrated with a MEMS grade IMU powered with CoDRIVE algorithms and high precision data processing software. The solution integrates RFID (radio-frequency identification) localisation information derived from tags installed in the roads around the University of Nottingham. This aids the positioning solution by correcting the long-term drift of inertial navigation technology in the absence of GNSS. The solution is informed of obscuration of GNSS through city models of skyview and elevation masks derived from 360-degree photography. The results show that predictive intelligence of the denial of GNSS and RFID aiding realises significant benefits compared to the inertial only solution. According to the validation, inertial only solutions drift over time, with an overall RMS accuracy over a 300 metres section of GNSS outage of 10 to 20 metres. After deploying the RFID tags on the road, experiments show that the RFID aided algorithm is able to constrain the maximum error to within 3.76 metres, and with 93.9% of points constrained to 2 metres accuracy overall.


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