Cross-generational acceptance of and interest in advanced vehicle technologies: A nationwide survey

The number of older drivers on the roadways is increasing; at the same time, technology in the automotive environment is rapidly evolving. To investigate the potential impact of these converging changes, this study used a cross-generational approach to compare driver attitudes toward advanced automotive technologies. Approximately 1000 drivers between the ages of 18 and 85 located across the United States responded to a survey about their opinions regarding general technology, advanced in-vehicle technology, and near-horizon connected vehicle systems. Participant responses were categorized using a generational construct, sorting responses not only by age but by shared life experiences (e.g. economic circumstances, involvement in wartime activities, cultural movements, etc.). The oldest generation (the “Silent” generation) exhibited the least interest in and comfort with advanced technology, although they owned and used advanced in-vehicle technology at approximately the same rates as the two middle generations. The youngest generation (the “Millennial” generation) was most likely to be interested in and comfortable with technology, but was least likely to own vehicles with advanced technology. All participants expressed interest in safety-related connected vehicle systems, but less so in infotainment applications. Reservations regarding data security and system cost were shared across generations. These findings are framed in the context of an aging population with unique driving and vehicle needs, and provide information that may assist both with vehicle technology design aspects and the proposed large-scale implementation of connected vehicle systems, including considerations for seniors and emphasis on safety systems and data security.     

The electric vehicle: A new driving experience involving specific skills and rules

The arrival of the electric vehicle (EV) on the market is one consequence of government measures to improve air quality and reduce CO² emissions. However, the EV has specific properties of use associated with its limited range and relative silence compared to normal vehicles, influencing the mobility behaviours of drivers and requiring them to develop some new driving abilities. This paper examines the behavioural modifications brought about by daily use of an electric vehicle at three different levels of driving activity: strategic, tactical and operational. The study collected and analyzed the self-reported behaviours (via questionnaires and travels dairies) of 36 Parisian private drivers, each of whom drove for six months an electric MINI E prototype. The results of the study show that driving an EV requires a learning phase to acquire the skills and knowledge necessary to operate the vehicle. At the strategic level of driving, drivers take into account the restricted range of the EV, implement a daily charge process, and develop new behaviours related to trip planning. The study also examines driver behaviour at the tactical level, in terms of driver interactions with other road users to deal with the silent nature of the EV, and at the operational level of driving, in terms of braking behaviour to master the regenerative braking function of the EV. The paper discusses the interactions between these three levels of driving activity.     

Should drivers be informed about the equipment of drivers with green light optimal speed advisory (GLOSA)?

Previous research demonstrated that green light optimal speed advisory (GLOSA) affects driving behavior at signalized intersections: On the one hand, drivers assisted with GLOSA show more energy-efficient and eco-friendly driving. Following unequipped vehicles’ drivers (UVDs) also adapt their driving behavior to the assisted one. On the other hand, safety issues can be found in encounters with UVDs who also perceive assisted driving behavior negatively. Therefore, in a multi-driver simulator study (N = 60 participants sorted in groups of n = 2 UVDs), we tested whether informing UVDs about the GLOSA of an assisted driver results in more behavioral adaptation of UVDs to the assisted driving behavior, less safety issues, and less frustration of UVDs. Two UVDs followed a lead vehicle driven by a confederate. The confederate was equipped with GLOSA and knew when traffic lights switched from green to red and, consequently, slowed down when approaching a green traffic light. The degree of information UVDs received was manipulated: The group “no information” did not receive any information. The group “information” knew about the equipment of the assisted confederate with GLOSA and the group “detailed information” received additional information about its functionality and benefit. Results show that UVDs of the group “detailed information” adapted their driving behavior to the assisted driver. However, these UVDs also showed smaller minimum time-to-collision (TTC) values indicating safety issues. Results are discussed and implications made with regard to providing information to UVDs and to further investigate these challenges in the context of autonomous vehicles.     

Do sport modes cause behavioral adaptation?

A key question in transportation research is whether drivers show behavioral adaptation, that is, slower or faster driving, when new technology is introduced into the vehicle. This study investigates behavioral adaptation in response to the sport mode, a technology that alters the vehicle’s auditory, throttle-mapping, power-steering, and chassis settings. Based on the literature, it can be hypothesized that the sport mode increases perceived sportiness and encourages faster driving. Oppositely, the sport mode may increase drivers’ perceived danger, homeostatically causing them to drive more slowly. These hypotheses were tested using an instrumented vehicle on a test track. Thirty-one drivers were asked to drive as they normally would with different sport mode settings: Baseline, Modified Throttle Mapping (MTM), Artificial Engine Sound enhancement (AESe), MTM and AESe combined (MTM-AESe), and MTM, AESe combined with four-wheel steering, increased damping, and decreased power steering (MTM-AESe-4WS). Post-trial questionnaires showed increased perceived sportiness but no differences in perceived danger for the three MTM conditions compared to Baseline. Furthermore, compared to Baseline, MTM led to higher vehicle accelerations and, with a smaller effect size, a higher time-percentage of driving above the 110 km/h speed limit, but not higher cornering speeds. The AESe condition did not significantly affect perceived sportiness, perceived danger, and driving speed compared to Baseline. These findings suggest that behavioral adaptation is a functional and opportunistic phenomenon rather than mediated by perceived sportiness or perceived danger.     

PTSD and Emotional Distress Symptoms Measured After a Motor Vehicle Accident: Relationships with Pain Coping Profiles

This study explored differences among pain patients classified as Dysfunctional, Interpersonally Distressed, and Adaptive Copers on the Multidimensional Pain Inventory with respect to PTSD symptomatology, anxiety, and depression. Eighty-five patients with pain complaints who had experienced a serious motor vehicle accident were classified into these three pain coping categories and assessed using clinician and self-report measures. Results indicated that patients classified as Adaptive Copers (n = 24) showed less PTSD symptomatology, anxiety, and depressed mood, relative to individuals classified as Dysfunctional (n = 36) and as Interpersonally Distressed (n = 25), who did not differ on these dimensions. Emotional responses during the accident (fear, helplessness, danger, perceived control, and certainty that one would die) did not differentiate the groups. Pain profiles contributed to the prediction of self-reported PTSD symptoms, controlling for state anxiety. These data suggest that pain patients with both Dysfunctional and Interpersonally Distressed coping profiles are at elevated risk for a range of posttrauma problems following a serious motor vehicle accident.     

Investigating driver reactions to movements of autonomous vehicle in permitted right turn through driving simulator experiments

Traffic safety has always been a hot topic for human-driven (HDV) and autonomous vehicles (AV) mixed flow. The conflict between permitted right-turn vehicles (PRT) and opposing through vehicles (TH) at signalized intersections (left-handed traffic) is extraordinarily critical. AVs with aggressive behaviors are able to accept short gap time without losing safety. However, such a turning maneuver may lead to dangerous feelings and cause unexpected reactions of approaching drivers. This study aims to investigate and model drivers’ reactions in TH movements to PRT AVs considering the trust degree of drivers to AVs. Questionnaire surveys and driving simulator experiments were conducted for 41 participants. Results reveal that the right turn timing of PRT AV will significantly influence drivers’ reactions. Basically, TH drivers will brake with a high probability under the situation of small expected post encroachment time (PET). It is also found that female drivers and drivers with low trust in AVs are more vigilant to PRT AVs than other drivers. Based on this finding a two-layer model for reproducing TH drivers’ reactions to PRT AVs is proposed. The first layer is to determine the braking decision and the second layer is to calculate the parameters of braking behaviors (brake lag, braking time, and speed drop). The significance and coefficients variables in these models proved that the trust in AV will influence drivers’ decisions and braking behaviors (brake lag and braking time). The more the drivers trust AVs, the smaller the expected PET to AVs they can accept for passing without braking, and the more gently they will brake (longer brake lag and shorter braking time) due to the cutting in of PRT AVs. This effect will become significant after drivers have experienced several interactions with AVs.     

Experimental evidence supporting simpler Action Point paradigms for car-following

The Action Point theory is one of the paradigms that can be applied to understand and reproduce car-following behaviour. Several different approaches to this theory have been proposed, some more simple and others more complex. In particular, the reference point in this field is still the paradigm from Wiedemann, which requires the identification of four action-point thresholds. In this paper we review Action Point theories in order to highlight similarities and differences and to ascertain whether all the thresholds proposed by Wiedemann actually bind the driving behaviour. Based on a large-scale experiment in which car-following data were collected, we identified all candidate action points assuming that the more complex (four-threshold) theory holds. Then we tested these points with respect to the large data set of available observations, in order to check whether actual actions are performed at the points. The results show that very often simpler approaches better match the observed data and that in order to explain car-following behaviour it is sufficient in most cases to refer to two thresholds. The results obtained by real-world observation were also tested in virtual environments (two different kinds of driving simulators) and were confirmed.     

The impact of motor vehicle injury on distress: Moderators and trajectories over time

Research reveals that motor vehicle injuries (MVIs) can result in severe and debilitating psychological distress. Yet, not every person who has sustained a MVI suffers psychologically. It appears that risk of distress varies by demographic and psychosocial characteristics. The present study aimed to explore the trajectories of post-MVI distress and the effect of pre-MVI psychological functioning on post-MVI distress. Hierarchical linear modeling was used to explore the longitudinal dataset from the Canadian National Population Health Survey. Participants were assessed up to nine years post-MVI. Post-MVI distress increased over time. Men experienced greater overall distress than women and a greater increase in distress over time. Pre-MVI distress predicted post-MVI distress. This relationship was strongest for those with greater pre-MVI alcohol consumption. At low levels of pre-MVI distress, greater pre-MVI alcohol consumption was related to lower post-MVI distress, but at high levels of pre-MVI distress, greater pre-MVI alcohol consumption predicted increased post-MVI distress. Those with partners experienced less distress than the unpartnered. This study supports the general findings of other post-MVI and post-trauma studies, although the current study’s main and interaction effects reveal more complex and nuanced relationships among variables in their prediction of post-MVI psychological distress.     

Understanding charging behaviour of electric vehicle users

We examined the psychological dynamics underlying charging behaviour of electric vehicle (EV) users. Data from 79 EV users were assessed in a 6-month EV field study. On average, users charged their EV three times per week, drove 38 km per day, and they typically had a large surplus of energy remaining upon recharging. Based on first findings concerning charging style among mobile phone users, we hypothesized that user–battery interaction style (UBIS) is a relevant variable for understanding charging behaviour of EV users. We developed measures to assess UBIS. Results show that it is a relatively temporally stable characteristic which also shows some cross-device consistency. As predicted by our conceptual model, UBIS and comfortable range explain the charge level at which people typically recharged. UBIS was related to users’ confidence in their mental model of range dynamics, the utilization of range, and to excess energy from renewable sources. This research has implications for optimizing sustainability of electric mobility systems.     

The Safe-Range-Inventory (SRI): An assistance tool for optimizing the charging infrastructure for electric vehicles

Electric Vehicles (EVs) are propagated as an essential solution for reducing the carbon footprint of traffic activities. One essential barrier to the adoption of electromobility strategies in everyday life is the very limited driving range of typical EVs. A dense and reliable network of electric charging stations would enable safer and longer ranges. Modern fast-charging technologies provide additional possibilities to tactically and quickly re-charge EVs, but high implementation costs make it necessary to establish a mixed infrastructure consisting of cheap-but-slow and expensive-but-fast charging stations. We utilized the so-called Safe-Range-Inventory (SRI), a multidimensional assessment tool for capturing multi-facets of subjective range safety assessments. Using scenarios with different infrastructure settings, we revealed that the addition of just one fast-charging option drastically lowers range anxiety even under relatively short emergency range conditions. Additional fast-charging options did not have strong positive effects on the assessments but would amass very high costs. The SRI can assist in the planning of electric charging infrastructures in order to find the right balance between range safety and installation and maintenance costs.