Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

Human factors studies are becoming more and more crucial in the automotive sector due to the need to evaluate the drivers reactions to the increasingly sophisticated driving assistant technologies. Driving simulators allow performing this kind of study in a controlled and safe environment. However, the driving simulation's Level of Detail (LOD) can affect the users perception of driving scenarios and make an experimental campaigns outcomes unreliable. This paper proposes a study investigating possible correlations between drivers behaviors and emotions, and simulated driving scenarios. Four scenarios replicating the same real area were built with four LODs from LOD0 (only the road is drawn) to LOD3 (all buildings with real textures for facades and roofs are inserted together with items visible from the road). 32 participants drove in all the four scenarios on a fixed-base driving simulator; their performance relating to the vehicle control (i.e. speed, trajectory, brake and gas pedal use, and steering wheel), their physiological data (electrodermal activity, and eye movements), their subjective perceptions, opinions and emotional state (questionnaires concerning the research and Self-Assessment Manikin Scale) were measured. The results showed that drivers behavior changes in a very complex way. Geometrical features of the route and environmental elements constrain much more driving behavior than LOD does, as observed for vehicle trajectory and speed; skin conductance and gas pedal appear to be more sensitive to LODs. Gaze position changes according to LODs, but differently for rectilinear and curvilinear segments. Pupil diameter increases with higher LODs. Emotions are not affected by LODs. Generally, different signals showed different correlations with the LOD level, suggesting that future studies should consider their measures while modeling the virtual scenario. It is hypothesized that scenario realism is more relevant during leisurely environmental interaction, whilst simulator fidelity is crucial in task-driven interactions.

With the development of the autonomous vehicle, traditional testing tools and methods for the automotive industry can no longer meet the needs of autonomous vehicle testing. Simulation test has huge technical advantages in test efficiency and test cost, etc. It is an important method for future testing and verification of autonomous vehicles, and its key technologies have become focal points for research. By investigating the current research and development progress of the autonomous vehicle platform, this paper presents and summarizes the simulation elements, analyzes the problems faced by the autonomous vehicle platform, and prospects the future work.

Every year approximately more than one million people die on world’s road. Human factors are the largest contributing factors to the traffic crashes and fatality, and recent researches have identified drivers’ cognitive aspect as the major cause of human errors in 80% of crash events. Thus, the development of countermeasures to manage drivers’ cognitive aspect is an important challenge to address. Driver-Assistance Systems have been developed and integrated into vehicles to acquire data about the environment and the driver, and to communicate information to the driver, usually via the senses of vision and hearing. Unfortunately, these senses are already subjected to high demands, and the visual and auditory stimuli can be underestimate or considered as annoying. However, other sensory channels could be used to elicit the drivers’ cognitive aspect. In particular, smell can impact on various aspects of humans’ psychological state, such as people’s attention level, and can induce activation states in people. The research presented in this paper aims at investigating whether olfactory stimuli, instead of auditory ones, can be used to influence the cognitive aspect of the drivers. For this purpose, an experimental framework has been set up and experimental testing sessions have been performed. The experimental framework is a multisensory environment consisting of an active stereo-projector and a screen used for displaying a video that reproduces a very monotonous car trip, a seating-buck for simulating the car environment, a wearable Olfactory Display, in-ear earphones and the BioGraph Infiniti system for acquiring the subjects’ physiological data. The analysis of the data collected in the testing sessions shows that, in comparison to the relaxation state, olfactory stimuli are effective in increasing subjects’ attention level more than the auditory ones.

Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

The control shifting between a human driver and a semi-autonomous vehicle is one of the most critical scenarios in the road-map of autonomous vehicle development. This paper proposes a methodology to study driver's behaviour in semi-autonomous driving with physiological-sensors-integrated driving simulators. A virtual scenario simulating take-over tasks has been implemented. The behavioural profile of the driver has been defined analysing key metrics collected by the simulator namely lateral position, steering wheel angle, throttle time, brake time, speed, and the take-over time. In addition, heart rate and skin conductance changes have been considered as physiological indicators to assess cognitive workload and reactivity. The methodology has been applied in an experimental study which results are crucial for taking insights on users’ behaviour. Results show that individual different driving styles and performance are able to be distinguished by calculating and elaborating the data collected by the system. This research provides potential directions for establishing a method to characterize a driver's behaviour in a semi-autonomous vehicle.