Detection and emotional evaluation of an electric vehicle’s exterior sound in a simulated environment

Electric vehicles are quiet at low speeds and thus potentially pose a threat to pedestrians’ safety. Laws are formulating worldwide that mandate these vehicles emit sounds to alert the pedestrians of the vehicles’ approach. It is necessary that these sounds promote a positive perception of the vehicle brand, and understanding their impact on soundscapes is also important. Detection time of the vehicle sounds is an important measure to assess pedestrians’ safety. Emotional evaluation of these sounds influences assessment of the vehicle brand. Laboratory simulation is a new approach for evaluating exterior automotive sounds. This study describes the implementation of laboratory simulation to compare the detection time and emotional evaluation of artificial sounds for an electric vehicle. An Exterior Sound Simulator simulated audio-visual stimuli of an electric car passing a crossroad of a virtual town at 4.47 ms-1 (10 mph), from the perspective of a pedestrian standing at the crossroad. In this environment, 15 sounds were tested using experiments where participants detected the car and evaluated its sound using perceptual dimensions. Results show that these sounds vary significantly in their detection times and emotional evaluations, but crucially that traditional metrics like dB(A) do not always relate to the detection of these sounds. Detection time and emotional evaluation do not have significant correlation. Hence, sounds of a vehicle could be detected quickly, but may portray negative perceptions of the vehicle. Simulation provides a means to more fully evaluate potential electric vehicle sounds against the competing criteria

Too sick to drive : how motion sickness severity impacts human performance

There are multiple concerns surrounding the development and rollout of self-driving cars. One issue has largely gone unnoticed - the adverse effects of motion sickness as induced by self-driving cars. The literature suggests conditionally, highly and fully autonomous vehicles will increase the onset likelihood and severity of motion sickness. Previous research has shown motion sickness can have a significant negative impact on human performance. This paper uses a simulator study design with 51 participants to assess if the scale of motion sickness is a predictor of human performance degradation. This paper finds little proof that subjective motion sickness severity is an effective indicator of the scale of human performance degradation. The performance change of participants with lower subjective motion sickness is mostly statistically indistinguishable from those with higher subjective sickness. Conclusively, those with even acute motion sickness may be just as affected as those with higher sickness, considering human performance. Building on these results, it could indicate motion sickness should be a consideration for understanding user ability to regain control of a self-driving vehicle, even if not feeling subjectively unwell. Effectiveness of subjective scoring is discussed and future research is proposed to help ensure the successful rollout of self-driving vehicles

An investigation on the effect of driver style and driving events on energy demand of a PHEV

Environmental concerns, security of fuel supply and CO2 regulations are driving innovation in the automotive industry towards electric and hybrid electric vehicles. The fuel economy and emission performance of hybrid electric vehicles (HEVs) strongly depends on the energy management system (EMS). Prior knowledge of driving information could be used to enhance the performance of a HEV. However, how the necessary information can be obtained to use in EMS optimisation still remains a challenge. In this paper the effect of driver style and driving events like city and highway driving on plug in hybrid electric vehicle (PHEV) energy demand is studied. Using real world driving data from three drivers of very different driver style, a simulation has been exercised for a given route having city and highway driving. Driver style and driving events both affect vehicle energy demand. In both driving events considered, vehicle energy demand is different due to driver styles. The major part of city driving is reactive driving influenced by external factors and driver leading to variation in vehicle speed and hence energy demand. In free highway driving, the driver choice of cruise speed is the only factor affecting vehicle energy demand

A smart driving smartphone application : real-world effects on driving performance and glance behaviours

A smart driving Smartphone application – which offers real-time fuel efficiency and safety feedback to the driver in the vehicle – was evaluated in a real-world driving study. Forty participants drove an instrumented vehicle over a 50 minute mixed route driving scenario, with 15 being selected for video data analysis. Two conditions were adopted, one a control, the other with smart driving advice being presented to the driver. Key findings from the study showed a 4.1% improvement in fuel efficiency when using the smart driving system, and an almost 3-fold reduction in time spent travelling closer than 1.5 seconds to the vehicle in front. Glance behavior results showed that drivers spent an average of 4.3% of their time looking at the system, at an average of 0.43 seconds per glance, with no glances of greater than two seconds. In conclusion this study has shown that a smart driving system specifically developed and designed with the drivers’ information requirements in mind can lead to significant improvements in real-world driving behaviours, whilst limiting visual distraction, with the task being integrated into normal driving

Exploring a cardio-thoracic hospital ward soundscape in relation to restoration

Hospitals can provide stressful experiences for both patients and medical staff. A well-designed hospital soundscape should avoid adding to negative emotional states (e.g. stress), limit any detrimental cognitive effects (e.g. attentional fatigue), and enable restoration. Experiences of the cardio-thoracic ward soundscape, in a UK public University hospital, were explored via semi-structured interviews with 11 patients and 16 nurses. Thematic coding analysis resulted in 11 key themes including notions of restoration and emotional responses. The themes were used to develop a conceptual model to describe the processes involved in the perception and evaluation of the soundscape. The language used by patients and nurses indicated the emotional response to the soundscape was at times stressful and at others potentially restorative. Coping methods of accepting and habituating to individual sounds were noted. The impact of the patients' and nurses' ability to maintain these coping strategies are discussed in relation to restoration and the temporal variation of the soundscape. A period of 'quiet time' was in operation at the hospital and the importance of this was noted through various responses relating to emotion and restoration. The results suggest the soundscape has potentially, a beneficial role in facilitating restoration thus helping patients' recovery and medical staff's ability to remain productive. This research supports the need to study hospital soundscapes further so that design implications can be considered for the production of a more restorative environment, possibly through the masking/removal of unwanted sounds and optimising positive sounds

Millimeter-wave communication for a last-mile autonomous transport vehicle

Low-speed autonomous transport of passengers and goods is expected to have a strong, positive impact on the reliability and ease of travelling. Various advanced functions of the involved vehicles rely on the wireless exchange of information with other vehicles and the roadside infrastructure, thereby benefitting from the low latency and high throughput characteristics that 5G technology has to offer. This work presents an investigation of 5G millimeter-wave communication links for a low-speed autonomous vehicle, focusing on the effects of the antenna positions on both the received signal quality and the link performance. It is observed that the excess loss for communication with roadside infrastructure in front of the vehicle is nearly half-power beam width independent, and the increase of the root mean square delay spread plays a minor role in the resulting signal quality, as the absolute times are considerably shorter than the typical duration of 5G New Radio symbols. Near certain threshold levels, a reduction of the received power affects the link performance through an increased error vector magnitude of the received signal, and subsequent decrease of the achieved data throughput

User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Scenario description language for automated driving systems : a two level abstraction approach

The complexities associated with Automated Driving Systems (ADSs) and their interaction with the environment pose a challenge for their safety evaluation. Number of miles driven has been suggested as one of the metrics to demonstrate technological maturity. However, the experiences or the scenarios encountered by the ADSs is a more meaningful metric, and has led to a shift to scenario-based testing approach in the automotive industry and research community. Variety of scenario generation techniques have been advocated, including real-world data analysis, accident data analysis and via systems hazard analysis. While scenario generation can be done via these methods, there is a need for a scenario description language format which enables the exchange of scenarios between diverse stakeholders (as part of the systems engineering lifecycle) with varied usage requirements. In this paper, we propose a two-level abstraction approach to scenario description language (SDL) - SDL level 1 and SDL level 2. SDL level 1 is a textual description of the scenario at a higher abstraction level to be used by regulators or system engineers. SDL level 2 is a formal machine-readable language which is ingested by testing platform e.g. simulation or test track. One can transform a scenario in SDL level 1 into SDL level 2 by adding more details or from SDL level 2 to SDL level 1 by abstracting

Requirements and Sizing Investigation for Constellation Space Suit Portable Life Support System Trace Contaminant Control

The Trace Contaminant Control System (TCCS), located within the ventilation loop of the Constellation Space Suit Portable Life Support System (PLSS), is responsible for removing hazardous trace contaminants from the space suit ventilation flow. This paper summarizes the results of a trade study that evaluated if trace contaminant control could be accomplished without a TCCS, relying on suit leakage, ullage loss from the carbon dioxide and humidity control system, and other factors. Trace contaminant generation rates were revisited to verify that values reflect the latest designs for Constellation Space Suit System (CSSS) pressure garment materials and PLSS hardware. Additionally, TCCS sizing calculations were performed and a literature survey was conducted to review the latest developments in trace contaminant technologies