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Current and potential negative effects of autonomous vehicles
Abstract and Figures
There is a general enthusiastic approach toward autonomous vehicles, e.g. they are claimed to be the breakthrough solution for a drastic reduction of road accidents, largely caused by human errors. However, their current and potential negative effects have not been adequately addressed yet: decreasing driving skills, new “automotive digital divide”, additional reaction time, “last mile” issue for automated HGVs are only some examples of still pending issues that can jeopardize the expected advantages. This paper analyzes the levels of automated driving defined by SAEJ3016 according to the current literature and resumes the main issues not yet adequately solved, in order to give a clear picture of the current and potential negative effect of each level, starting from “Level 2 - Partial automation” up to “level 4 –High automation”. Level 5 is not analyzed because its deployment appears too far in the time and there are not enough data for an effective discussion. The position of the automotive industry and its need to re-invent the business is related to the present market approach and may have a relevant influence on the incoming paradigm shift.
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... If such cars become widespread, it might help to eliminate road accidents due to human errors. However, a country's laws and ethics need to be changed to include fully automatically driven cars, for example, the degree of acceptance of automatically driven cars by the people and taking responsibility in an event of an accident (Hulse et al., 2018;Nunes et al., 2018;Polidori et al., 2018;Meder et al., 2019;Taeihagh and Lim, 2019). Therefore, although the technological progress in the field of automobile engineering is remarkable, it might take more time to popularize fully automatically driven cars among people. ...
In this study, we discuss the psychological acceptability of an utterance strategy used by the Driving Support Agent (DSA). Previous literature regarding DSA suggests that the adoption of a small robot as a form will increase acceptability. However, the agent’s utterance has been reported as a problem faced by the user. Therefore, in this study, we designed the agent’s utterance using politeness strategy as described by Brown and Levinson’s famous sociolinguistics and pragmatics theory and analyzed its acceptability through a participant-based experiment. In this experiment, we used positive and negative politeness strategies (PPS and NPS, respectively). In general, PPS is utilized to reflect the desire to be liked/recognized by others, whereas NPS is utilized to reflect the need for not wanting to be disturbed by others. Based on our results, PPS was rated high compared to NPS (n = 197). Therefore, many participants highly evaluated PPS. However, there was a group of participants who appreciated NPS. There were also participants who evaluated the two strategies equally. The number of participants in these three groups was observed at 4:1:1. This result contributes as an index on the utterance design of the DSA.
Two track tests were performed using European cab over vehicles in a two vehicle platoon to determine the aerodynamic benefits of driving in a platoon. The first test, performed in January tested following distances of 10, 20, 30, 40 & 50 m. As the adaptive cruise control was inoperative, the distance was measured using radar, and manually controlled. Weather conditions were wintery and wind speeds were above average, leading to yaw angles of 5°. Fuel measurements using CAN bus data showed that the leading vehicle experienced no savings for following distances other than 10 m. For the following vehicle, at the largest distance of 50 m savings of 9.0 ± 2.8% were achieved. Decreasing the distance to 40, 30 and 20 m did not yield any significant savings over a following distance of 50 m. At a separation distance of 10 m the savings increased somewhat to 10.6 ± 3.1%.
The second experiment was conducted during August, with more stable conditions. Wind speeds were low, and the resulting experienced yaw angles were below 2°. During the second test, the adaptive cruise control was used to maintain the distance. The distances of the first test were repeated with an additional distance of 70 m. The results showed similar results for the Leading vehicle, no significant savings for any of the separation distances except the 10 m separation distance, which resulted in a saving of 4.0 ± 0.7%. The savings achieved with the following vehicle were generally higher than those achieved in the first test. For 50, 40, 30 and 20 m the results were around 1.5% higher than in Test 1. For 10 m separation distance, the result achieved (10.1 ± 0.9%) was lower than the result at 20 m distance, and similar to the value achieved in Test 1. The authors suggest that the difference results between the two tests can be attributed to the difference in wind conditions, and the resulting difference in yaw angles. As there were significant differences between the two tests in weather and road conditions and setup, such as different tractor and trailers, distance control method, the authors cannot determine a single cause. The results achieved with the leading vehicle match the results of literature well. For the following vehicle there is more spread in the existing work, and the data matches the lower end of the spread well. The authors conclude that for the range of separation distances tested the leading vehicle gains from the closer following distances, but that for the following vehicle close proximity platooning has a limited potential for improving fuel consumption over current day legal platooning distances.
Among the major topics regarding the protection of roads, restraint systems still represent a big opportunity in order to increase safety performances. When accidents happen, in fact, the infrastructure can substantially contribute to the reduction of consequences if its marginal spaces are well designed and/or effective restraint systems are installed there. Nevertheless, basic concepts and technology of road safety barriers have not significantly changed for the last two decades. The paper proposes a new approach to the study aimed to define possible enhancements of restraint safety systems performances, by using new materials and defining innovative design principles. In particular, roadside systems can be developed with regard to vehicle-barrier interaction, vehicle-oriented design (included low-mass and extremely low-mass vehicles), traffic suitability, user protection, working width reduction. In addition, thanks to sensors embedded into the barriers, it is also expected to deal with new challenges related to the guidance of automatic vehicles and I2V communication.
IntroductionThis paper builds our knowledge of truck driver behaviour in and experience of automated truck platooning, focusing on the effect of partially and fully automated truck platoons on driver workload, trust, acceptance, performance, and sleepiness. Methods
Twenty-four male drivers experienced three conditions in a truck driving simulator, i.e., baseline, partial automation, and full automation: the baseline condition was driving with standard cruise control; partial automation was automated longitudinal control ten metres behind the truck in front, with the driver having to steer; and full automation was automated longitudinal and lateral control. Each condition was simulated in three situations: light traffic, heavy traffic, and heavy traffic plus fog. ResultsThe experiment demonstrated that automation affects workload. For all workload measures, partial automation produced higher workload than did the full-automation or baseline condition. The two measures capturing trust, i.e., the Human Trust in Automated Systems Scale (HTASS) and Cooper–Harper Scales of Workload, Temporal Load, Situation Awareness, and Trust, were consistent and indicated that trust was highest under the baseline condition, with little difference between partial and full automation. Driver acceptance of both levels of automation was lower than acceptance of baseline. Drivers rated their situation awareness higher for both partial and full automation than for baseline, although both levels of automation led to higher sleepiness. Conclusions
Workload was higher for partial than for full automation or the baseline condition. Trust and acceptance were generally highest in the baseline condition, and did not differ between partial and full automation. Drivers may believe that they have more situation awareness during automated driving than they actually do. Both levels of automation led to a higher degree of sleepiness than in the baseline condition. The challenge when implementing truck platooning is to develop a system, including human–machine interaction (HMI), that does not overburden the driver, properly addresses driver sleepiness, and satisfies current legislation. The system also must be trusted and accepted by drivers. To achieve this, the development of well-designed HMI will be crucial.
Theories and models usually adopted in designing roads, especially for safety verifications, are based on the hypothesis of a single vehicle that follows a trajectory matching with the road axle. This condition can be expressed as "road following" model and it determines many important design parameters, like curvature, design speed, superelevation, lane placement, sight distances, characteristics of transition curves, etc.. In real conditions, vehicles on a road section travel along trajectories always different from the road axle, so, in order to ensure that theoretical models can be effective, it is important to evaluate how a reference trajectory, on particular road elements, can statistically represent the population of users. In this way, it will be possible to design the road axle on the basis of this reference trajectory and consequently develop road design processes. To deal with these problems, it is useful to perform some surveys on trajectories of vehicles on real road elements, but the statistical analysis of the data needs specific procedures to extract trajectories that have a formal geometric expression and correctly represent the scattering of vehicles' position. The article presents a statistics based method, proposed with the aim to obtain the reference trajectories on road sections starting from surveys over real exercise conditions; the method was tested on case studies regarding two ramp terminals, that are particularly interesting because when the infrastructure present special geometrical or physical features the vehicle trajectories are influenced by them.
This paper outlines the results of a driving simulator study conducted for the European CityMobil project, which was designed to investigate the effect of a highly automated driving scenario on driver behaviour. Drivers' response to a number of 'critical' scenarios was compared in manual driving with that in automated driving. Drivers were in full control of the vehicle and its manoeuvres in the manual driving condition, whilst control of the vehicle was transferred to an 'automated system' in the automated driving condition. Automated driving involved the engagement of lateral and longitudinal controllers, which kept the vehicle in the centre of the lane and at a speed of 40 mph, respectively. Drivers were required to regain control of the driving task if the automated system was unable to handle a critical situation. An auditory alarm forewarned drivers of an imminent collision in such critical situations. Drivers' response to all critical events was found to be much later in the automated driving condition, compared to manual driving. This is thought to be because drivers' situation awareness was reduced during automated driving, with response only produced after drivers heard the alarm. Alternatively, drivers may have relied too heavily on the system, waiting for the auditory alarm before responding in a critical situation. These results suggest that action must be taken when implementing fully automated driving to ensure that the driver is kept in the loop at all times and is able to respond in time and appropriately during critical situations. OBJECTIVES This paper presents the results of one of the studies conducted for the EU funded project CityMobil, the main aim of which has been to introduce advanced urban transport systems on a large scale. One objective of CityMobil has been to investigate the human factors issues associated with future developments in urban public transport, where the driving task may become much more automated. The experiment described here investigated some of the issues associated with 'dual-mode' driving, where a particular vehicle can either be driven in manual mode (with all aspects of driving controlled by the driver) or in an automated mode, where the vehicle is effectively driven by means of various automated systems which control its longitudinal and lateral position within the road and with respect to other traffic. Such dual-mode vehicles can be driven on equipped 'eLanes' (Flemisch, 2005; Schieben et al., 2008) and consist of longitudinal and lateral guidance systems, radars for obstacle detection, vehicle to infrastructure communication systems and a human-machine interface. Today's vehicles are already equipped with a variety of warning and assistance systems, and the utilisation of various automated systems such as Adaptive Cruise Control (ACC), Lane
The work described assesses the impact of inter-vehicle communication systems on road safety. A simple model is used to assess the reduction in accident risk if the response time of drivers is improved by state of the art technology. The currently available techniques for inter-vehicle communication, based either on direct communication between vehicles or on vehicle-to-infrastructure and vice versa, are briefly examined in order to provide an overview of the recent proposals the world of electronics and telecommunications has made available to the transport industry concerning safety. A method to assess safety, based on a parameter called risk index (RI), is then proposed in order to evaluate to what extent the use of vehicle-to-vehicle and vehicle-to-infrastructure communication technologies can actually increase road safety.
The geometric design principles traditionally hypothesize that trajectories of vehicles can be assumed corresponding to the road longitudinal axle of the road or, more correctly, to the median line of each allowed lane. In real conditions, instead, vehicles always travel along trajectories each other different; the variability is due to dynamic actions affecting the motion and, in a great measure, because the control of vehicle trajectories, performed by users, is not perfect. In order to consider if theoretical models can be effective for safety and comfort verifications in the design process, it is important to evaluate how a reference trajectory can statistically represent the whole population of road users. In fact, the difference between a real trajectory of a generic vehicle and the theoretical one can emphasize the safety problems related to geometric characteristics of roads. To deal with these problems, it appears interesting to analyse the dispersion of trajectories in various road sections; in this way, in fact, the “reference trajectory” along a road alignment can be recognized by means of a statistical approach. Starting from surveys on real road elements, the paper presents a method aimed to obtain trajectories that have formal geometric expression and that can correctly represent the scattering of vehicles’ position because reference lines are defined after a statistical analysis of collected data.
Human perception-brake reaction time (RT) studies have reported a wide variety of results. By analyzing a large number of data sets, however, it is possible to estimate times under specific conditions. The most important variable is driver expectation, which affects RTs by a factor of 2. When fully aware of the time and location of the brake signal, drivers can detect a signal and move the foot from accelerator to brake pedal in about 0.70 to 0.75 sec. Response to unexpected, but common signals, such as a lead car's brake lights, is about 1.25 sec, whereas RTs for surprise events, such as an object suddenly moving into the driver's path, is roughly 1.5 sec. These times are modulated somewhat by other factors, including driver age and gender, cognitive load, and urgency.
-6 scenarios self-driving cars still can't handle -Business insider UK aug 25
- D Muoio
Muoio,D.-6 scenarios self-driving cars still can't handle -Business insider UK aug 25, 2016 -http://uk.businessinsider.com/autonomouscar-limitations-2016-8?r=US&IR=T