Making roads safer: a vehicle blind spot alert system co-designed with end-users
Resumo
The number of traffic accidents involving motorcycles has been increasing in Brazil recently. Many accidents are caused by drivers who do not see motorcycles approaching in the vehicle blind spots. Advanced Driver Assistance Systems (ADAS) installed in vehicles can be used to mitigate this problem. However, the development of ADASs often focuses on security issues and does not consider the user experience with the ADASs interface. In this paper, we present the design of an alerting system that warns drivers about collision risks when motorcycles are identified in vehicle blind spots. Our proposal alerts drivers by using visual and haptic interaction modes. The vehicle blind spot alert system was conceived in a co-design session with the participation of 9 end-users who produced 3 low-fidelity (lo-fi) prototypes. After, these lo-fi prototypes were analyzed and compiled generating a high-fidelity (hi-fi) prototype containing haptic and visual alerting features implemented and installed in a car for testing. The alert system was evaluated by 20 end-users concerning their experience with the different warning modes. The results showed that for both the visual and haptic modes, users could recognize and understand the alerts without employing a great effort in the information interpretation. This result reinforces the idea that ADASs should provide simple interpretative interfaces because drivers' interaction with these systems should be a secondary activity since their concentration must be on driving.
Palavras-chave:
Notification System, User Experience, Advanced Driver Assistance System, Co-design approach, Situation Awareness
Referências
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Hanna Braun, Magdalena Gärtner, Sandra Trösterer, Lars EM Akkermans, Marije Seinen, Alexander Meschtscherjakov, and Manfred Tscheligi. 2019. Advanced driver assistance systems for aging drivers: Insights on 65+ drivers’ acceptance of and intention to use ADAS. In Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 123–133.
Jessica B. Cicchino. 2018. Effects of blind spot monitoring systems on police-reported lane-change crashes. Traffic Injury Prevention 19, 6 (2018), 615–622. DOI: 10.1080/15389588.2018.1476973 PMID: 29927678.
Ricardo Barbosa da Silva. 2020. Motoboys in Sao Paulo, Brazil: Precarious work, conflicts and fatal traffic accidents by motorcycle. Transportation Research Interdisciplinary Perspectives 8 (2020), 100261. DOI: 10.1016/j.trip.2020.100261
Gelcino de Paula Brito, José Antônio Ferreira Borges, and Gabriel Fernandes Garcia Nogueira. 2014. Analysis of Blind Areas in Different Categories of Vehicles Considering the Evolution of Projects and Legislation. In SAE Technical Paper Series. SAE International. DOI: 10.4271/2014-36-0281
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Anna-Katharina Frison and Andreas Riener. 2022. The “DAUX Framework”: a need-centered development approach to promote positive user experience in the development of driving automation. In User experience design in the era of automated driving. Springer, 237–271.
Anna-Katharina Frison, Philipp Wintersberger, Tianjia Liu, and Andreas Riener. 2019. Why do you like to drive automated? a context-dependent analysis of highly automated driving to elaborate requirements for intelligent user interfaces. In Proceedings of the 24th international conference on intelligent user interfaces. 528–537.
Anna-Katharina Frison, Philipp Wintersberger, and Andreas Riener. 2019. Resurrecting the ghost in the shell: A need-centered development approach for optimizing user experience in highly automated vehicles. Transportation research part F: traffic psychology and behaviour 65 (2019), 439–456.
Jeff Gothelf and Josh Seiden. 2013. Lean UX: Applying Lean Principles to Improve User Experience. O’Reilly Media. 26–29 pages.
Timo Günthner and Heike Proff. 2021. On the way to autonomous driving: How age influences the acceptance of driver assistance systems. Transportation research part F: traffic psychology and behaviour 81 (2021), 586–607.
SangHyun Han, Jinhuk Jeong, and SukHyun Seo. 2018. A Methodology of UX Design of Touch-based Automotive Headunit by Minizing Driver’s Distraction. In 2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE). IEEE, 276–280.
Martina Hasenjäger, Martin Heckmann, and Heiko Wersing. 2019. A survey of personalization for advanced driver assistance systems. IEEE Transactions on Intelligent Vehicles 5, 2 (2019), 335–344.
Marc Hassenzahl and Noam Tractinsky. 2006. User experience - a research agenda. Behaviour & Information Technology 25, 2 (2006), 91–97. DOI: 10.1080/01449290500330331
ISO Central Secretary. 2008. Intelligent transport systems — Lane change decision aid systems (LCDAS) — Performance requirements and test procedures. Standard. International Organization for Standardization, Geneva, CH.
ISO Central Secretary. 2019. Ergonomics of human-system interaction — Part 210: Human-centred design for interactive systems. Standard. International Organization for Standardization, Geneva, CH.
Paul Kaufmann and Andreas Riener. 2018. Evaluation of driving performance and user experience of different types of speedometer. In Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 110–114.
Ann-Kathrin Kraft, Christian Maag, Maria Isabel Cruz, Martin Baumann, and Alexandra Neukum. 2020. The effect of visual HMIs of a system assisting manual drivers in manoeuvre coordination in system limit and system failure situations. Transportation research part F: traffic psychology and behaviour 74 (2020), 81–94.
Jonathan Lazar, Jinjuan Heidi Feng, and Harry Hochheiser. 2017. Research Methods in Human Computer Interaction (second edition ed.). Morgan Kaufmann, Boston. 508 pages.
Shuo Li, Phil Blythe, Weihong Guo, and Anil Namdeo. 2019. Investigation of older drivers’ requirements of the human-machine interaction in highly automated vehicles. Transportation research part F: traffic psychology and behaviour 62 (2019), 546–563.
Xiaomeng Li, Atiyeh Vaezipour, Andry Rakotonirainy, Sébastien Demmel, and Oscar Oviedo-Trespalacios. 2020. Exploring drivers’ mental workload and visual demand while using an in-vehicle HMI for eco-safe driving. Accident Analysis & Prevention 146 (2020), 105756.
Michael J. Muller. 1991. PICTIVE—an Exploration in Participatory Design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New Orleans, Louisiana, USA) (CHI ’91). Association for Computing Machinery, New York, NY, USA, 225–231. DOI: 10.1145/108844.108896
Frederik Naujoks, Katharina Wiedemann, Nadja Schömig, Sebastian Hergeth, and Andreas Keinath. 2019. Towards guidelines and verification methods for automated vehicle HMIs. Transportation research part F: traffic psychology and behaviour 60 (2019), 121–136.
Julia Orlovska, Fjollë Novakazi, Bligård Lars-Ola, MariAnne Karlsson, Casper Wickman, and Rikard Söderberg. 2020. Effects of the driving context on the usage of Automated Driver Assistance Systems (ADAS) -Naturalistic Driving Study for ADAS evaluation. Transportation Research Interdisciplinary Perspectives 4 (2020), 100093. DOI: 10.1016/j.trip.2020.100093
Sara Paiva, Xabiel García Pañeda, Victor Corcoba, Roberto García, Próspero Morán, Laura Pozueco, Marina Valdés, and Covadonga del Camino. 2021. User Preferences in the Design of Advanced Driver Assistance Systems. Sustainability 13, 7 (Apr 2021), 3932. DOI: 10.3390/su13073932
SAE International. 2018. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Technical Report. Society of Automobile Engineers. 1–5 pages. [link]
Eduardo Navarra Satuf, Eugenius Kaszkurewicz, Roberto Schirru, and Mario Cesar Mello Massa de Campos. 2016. Situation awareness measurement of an ecological interface designed to operator support during alarm floods. International Journal of Industrial Ergonomics 53 (2016), 179–192. DOI: 10.1016/j.ergon.2016.01.002
Lenise Menezes Seerig, Giancarlo Bacchieri, Gustavo Giacomelli Nascimento, Aluisio J D Barros, and Flávio Fernando Demarco. 2016. Use of motorcycle in Brazil: users profile, prevalence of use and traffic accidents occurrence - a population-based study. Ciencia e Saude Coletiva 21, 12 (Dec. 2016), 3703–3710. DOI: 10.1590/1413-812320152112.28212015
Stephen J Selcon and RM Taylor. 1990. Evaluation of the Situational Awareness Rating Technique(SART) as a tool for aircrew systems design. AGARD, Situational Awareness in Aerospace Operations 8 p(SEE N 90-28972 23-53) (1990).
Helen Sharp, Yvonne Rogers, and Jennifer Preece. 2019. Interaction design: beyond human-computer interaction. John Wiley & Sons.
Yiting Shen and Wei Qi Yan. 2018. Blind Spot Monitoring Using Deep Learning. In 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). 1–5. DOI: 10.1109/IVCNZ.2018.8634716
Brian Still and Kate Crane. 2017. Fundamentals of user-centered design: A practical approach. CRC Press.
Xu Sun, Shi Cao, and Pinyan Tang. 2021. Shaping driver-vehicle interaction in autonomous vehicles: How the new in-vehicle systems match the human needs. Applied ergonomics 90 (2021), 103238.
Leslie Gayle Tudor, Michael J. Muller, Tom Dayton, and Robert W. Root. 1993. A Participatory Design Technique for High-Level Task Analysis, Critique, and Redesign: The CARD Method. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, 4 (1993), 295–299. DOI: 10.1177/154193129303700409
Claes Wohlin, Per Runeson, Martin Höst, Magnus C Ohlsson, Björn Regnell, and Anders Wesslén. 2012. Experimentation in software engineering. Springer Science & Business Media.
Sunkil Yun, Takaaki Teshima, and Hidekazu Nishimura. 2019. Human–machine interface design and verification for an automated driving system using system model and driving simulator. IEEE Consumer Electronics Magazine 8, 5 (2019), 92–98.
Kristin Braa. 1996. Influencing qualities of information systems-future challenges for participatory design. In PDC - Open Journal Systems, Vol. 4. 163–172. [link]
Hanna Braun, Magdalena Gärtner, Sandra Trösterer, Lars EM Akkermans, Marije Seinen, Alexander Meschtscherjakov, and Manfred Tscheligi. 2019. Advanced driver assistance systems for aging drivers: Insights on 65+ drivers’ acceptance of and intention to use ADAS. In Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 123–133.
Jessica B. Cicchino. 2018. Effects of blind spot monitoring systems on police-reported lane-change crashes. Traffic Injury Prevention 19, 6 (2018), 615–622. DOI: 10.1080/15389588.2018.1476973 PMID: 29927678.
Ricardo Barbosa da Silva. 2020. Motoboys in Sao Paulo, Brazil: Precarious work, conflicts and fatal traffic accidents by motorcycle. Transportation Research Interdisciplinary Perspectives 8 (2020), 100261. DOI: 10.1016/j.trip.2020.100261
Gelcino de Paula Brito, José Antônio Ferreira Borges, and Gabriel Fernandes Garcia Nogueira. 2014. Analysis of Blind Areas in Different Categories of Vehicles Considering the Evolution of Projects and Legislation. In SAE Technical Paper Series. SAE International. DOI: 10.4271/2014-36-0281
Felipe dos Santos, Pedro Lisboa, Herick Ribeiro, Pietro Campos, Lester Faria, and Luciana Zaina. 2023. Enhancing Driver Safety: a user-centered alert system to notify motorcycles in blind spot. em revisão 1, 1 (2023), 1–1.
Anna-Katharina Frison and Andreas Riener. 2022. The “DAUX Framework”: a need-centered development approach to promote positive user experience in the development of driving automation. In User experience design in the era of automated driving. Springer, 237–271.
Anna-Katharina Frison, Philipp Wintersberger, Tianjia Liu, and Andreas Riener. 2019. Why do you like to drive automated? a context-dependent analysis of highly automated driving to elaborate requirements for intelligent user interfaces. In Proceedings of the 24th international conference on intelligent user interfaces. 528–537.
Anna-Katharina Frison, Philipp Wintersberger, and Andreas Riener. 2019. Resurrecting the ghost in the shell: A need-centered development approach for optimizing user experience in highly automated vehicles. Transportation research part F: traffic psychology and behaviour 65 (2019), 439–456.
Jeff Gothelf and Josh Seiden. 2013. Lean UX: Applying Lean Principles to Improve User Experience. O’Reilly Media. 26–29 pages.
Timo Günthner and Heike Proff. 2021. On the way to autonomous driving: How age influences the acceptance of driver assistance systems. Transportation research part F: traffic psychology and behaviour 81 (2021), 586–607.
SangHyun Han, Jinhuk Jeong, and SukHyun Seo. 2018. A Methodology of UX Design of Touch-based Automotive Headunit by Minizing Driver’s Distraction. In 2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE). IEEE, 276–280.
Martina Hasenjäger, Martin Heckmann, and Heiko Wersing. 2019. A survey of personalization for advanced driver assistance systems. IEEE Transactions on Intelligent Vehicles 5, 2 (2019), 335–344.
Marc Hassenzahl and Noam Tractinsky. 2006. User experience - a research agenda. Behaviour & Information Technology 25, 2 (2006), 91–97. DOI: 10.1080/01449290500330331
ISO Central Secretary. 2008. Intelligent transport systems — Lane change decision aid systems (LCDAS) — Performance requirements and test procedures. Standard. International Organization for Standardization, Geneva, CH.
ISO Central Secretary. 2019. Ergonomics of human-system interaction — Part 210: Human-centred design for interactive systems. Standard. International Organization for Standardization, Geneva, CH.
Paul Kaufmann and Andreas Riener. 2018. Evaluation of driving performance and user experience of different types of speedometer. In Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 110–114.
Ann-Kathrin Kraft, Christian Maag, Maria Isabel Cruz, Martin Baumann, and Alexandra Neukum. 2020. The effect of visual HMIs of a system assisting manual drivers in manoeuvre coordination in system limit and system failure situations. Transportation research part F: traffic psychology and behaviour 74 (2020), 81–94.
Jonathan Lazar, Jinjuan Heidi Feng, and Harry Hochheiser. 2017. Research Methods in Human Computer Interaction (second edition ed.). Morgan Kaufmann, Boston. 508 pages.
Shuo Li, Phil Blythe, Weihong Guo, and Anil Namdeo. 2019. Investigation of older drivers’ requirements of the human-machine interaction in highly automated vehicles. Transportation research part F: traffic psychology and behaviour 62 (2019), 546–563.
Xiaomeng Li, Atiyeh Vaezipour, Andry Rakotonirainy, Sébastien Demmel, and Oscar Oviedo-Trespalacios. 2020. Exploring drivers’ mental workload and visual demand while using an in-vehicle HMI for eco-safe driving. Accident Analysis & Prevention 146 (2020), 105756.
Michael J. Muller. 1991. PICTIVE—an Exploration in Participatory Design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New Orleans, Louisiana, USA) (CHI ’91). Association for Computing Machinery, New York, NY, USA, 225–231. DOI: 10.1145/108844.108896
Frederik Naujoks, Katharina Wiedemann, Nadja Schömig, Sebastian Hergeth, and Andreas Keinath. 2019. Towards guidelines and verification methods for automated vehicle HMIs. Transportation research part F: traffic psychology and behaviour 60 (2019), 121–136.
Julia Orlovska, Fjollë Novakazi, Bligård Lars-Ola, MariAnne Karlsson, Casper Wickman, and Rikard Söderberg. 2020. Effects of the driving context on the usage of Automated Driver Assistance Systems (ADAS) -Naturalistic Driving Study for ADAS evaluation. Transportation Research Interdisciplinary Perspectives 4 (2020), 100093. DOI: 10.1016/j.trip.2020.100093
Sara Paiva, Xabiel García Pañeda, Victor Corcoba, Roberto García, Próspero Morán, Laura Pozueco, Marina Valdés, and Covadonga del Camino. 2021. User Preferences in the Design of Advanced Driver Assistance Systems. Sustainability 13, 7 (Apr 2021), 3932. DOI: 10.3390/su13073932
SAE International. 2018. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Technical Report. Society of Automobile Engineers. 1–5 pages. [link]
Eduardo Navarra Satuf, Eugenius Kaszkurewicz, Roberto Schirru, and Mario Cesar Mello Massa de Campos. 2016. Situation awareness measurement of an ecological interface designed to operator support during alarm floods. International Journal of Industrial Ergonomics 53 (2016), 179–192. DOI: 10.1016/j.ergon.2016.01.002
Lenise Menezes Seerig, Giancarlo Bacchieri, Gustavo Giacomelli Nascimento, Aluisio J D Barros, and Flávio Fernando Demarco. 2016. Use of motorcycle in Brazil: users profile, prevalence of use and traffic accidents occurrence - a population-based study. Ciencia e Saude Coletiva 21, 12 (Dec. 2016), 3703–3710. DOI: 10.1590/1413-812320152112.28212015
Stephen J Selcon and RM Taylor. 1990. Evaluation of the Situational Awareness Rating Technique(SART) as a tool for aircrew systems design. AGARD, Situational Awareness in Aerospace Operations 8 p(SEE N 90-28972 23-53) (1990).
Helen Sharp, Yvonne Rogers, and Jennifer Preece. 2019. Interaction design: beyond human-computer interaction. John Wiley & Sons.
Yiting Shen and Wei Qi Yan. 2018. Blind Spot Monitoring Using Deep Learning. In 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). 1–5. DOI: 10.1109/IVCNZ.2018.8634716
Brian Still and Kate Crane. 2017. Fundamentals of user-centered design: A practical approach. CRC Press.
Xu Sun, Shi Cao, and Pinyan Tang. 2021. Shaping driver-vehicle interaction in autonomous vehicles: How the new in-vehicle systems match the human needs. Applied ergonomics 90 (2021), 103238.
Leslie Gayle Tudor, Michael J. Muller, Tom Dayton, and Robert W. Root. 1993. A Participatory Design Technique for High-Level Task Analysis, Critique, and Redesign: The CARD Method. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, 4 (1993), 295–299. DOI: 10.1177/154193129303700409
Claes Wohlin, Per Runeson, Martin Höst, Magnus C Ohlsson, Björn Regnell, and Anders Wesslén. 2012. Experimentation in software engineering. Springer Science & Business Media.
Sunkil Yun, Takaaki Teshima, and Hidekazu Nishimura. 2019. Human–machine interface design and verification for an automated driving system using system model and driving simulator. IEEE Consumer Electronics Magazine 8, 5 (2019), 92–98.
Publicado
16/10/2023
Como Citar
LISBOA, Pedro; DOS SANTOS, Felipe; RIBEIRO, Herick; CAMPOS, Pietro; ZAINA, Luciana.
Making roads safer: a vehicle blind spot alert system co-designed with end-users. In: SIMPÓSIO BRASILEIRO SOBRE FATORES HUMANOS EM SISTEMAS COMPUTACIONAIS (IHC), 22. , 2023, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
