CONNECTED AND AUTOMATED VEHICLE AS A MODEL OF CHANGE IN OUR SOCIETY: ADVANCES AND PERSPECTIVES

10.6036/10266 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 450-450
Author(s):  
JOSHUÉ PÉREZ RASTELLI
Keyword(s):  
Automated Vehicles ◽  
Automated Vehicle ◽  
Complex Change ◽  
The Way

In recent years, automated vehicles (also known asautonomous vehicles), are becoming a more than obvious reality. Many of us believe that this reality is accompanied by a deeper and more complex change in our society, and in the way we understand mobility today.

scholarly journals Drivers’ Age and Automated Vehicle Explanations

2021 ◽  
Vol 13 (4) ◽  
pp. 1948
Author(s):  
Qiaoning Zhang ◽  
Xi Jessie Yang ◽  
Lionel P. Robert
Keyword(s):  
Decision Making ◽  
Middle Age ◽  
Age Groups ◽  
Design Experiment ◽  
Mixed Design ◽  
Automated Vehicles ◽  
Automated Vehicle ◽  
Automated Decision Making

Automated vehicles (AV) have the potential to benefit our society. Providing explanations is one approach to facilitating AV trust by decreasing uncertainty about automated decision-making. However, it is not clear whether explanations are equally beneficial for drivers across age groups in terms of trust and anxiety. To examine this, we conducted a mixed-design experiment with 40 participants divided into three age groups (i.e., younger, middle-age, and older). Participants were presented with: (1) no explanation, or (2) explanation given before or (3) after the AV took action, or (4) explanation along with a request for permission to take action. Results highlight both commonalities and differences between age groups. These results have important implications in designing AV explanations and promoting trust.

scholarly journals Impact of External Human–Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment

2021 ◽  
Vol 13 (15) ◽  
pp. 8396
Author(s):  
Marc Wilbrink ◽  
Merle Lau ◽  
Johannes Illgner ◽  
Anna Schieben ◽  
Michael Oehl
Keyword(s):  
Urban Traffic ◽  
Automated Vehicles ◽  
Negative Effects ◽  
Communication Tools ◽  
Automated Vehicle ◽  
Additional Information ◽  
Road Users ◽  
Vulnerable Road Users ◽  
And Behaviors ◽  
Vehicle Automation

The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.

scholarly journals Experimental Study on Different Types of Curves for Ride Comfort in Automated Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Naohisa Hashimoto ◽  
Yusuke Takinami ◽  
Makoto Yamamoto
Keyword(s):  
Traffic Accidents ◽  
Field Experiments ◽  
Ride Comfort ◽  
Vehicle Control ◽  
Automated Vehicles ◽  
Significance Level ◽  
Automated Vehicle ◽  
Driving Assistance ◽  
Human Factor Research ◽  
Automated Vehicle Control

Vehicle automation is among the best possible solutions for traffic issues, including traffic accidents, traffic jams, and energy consumption. However, the user acceptance of automated vehicles is critical and is affected by riding comfort. In addition, human factors in automated vehicle control should be clear. This study evaluates the effect of different courses on driving comfort in automated vehicles using field experiments with 25 subjects. This study focused on lateral motion, but speed control was not targeted. Further, generating a path for obstacle avoidance and lane keeping, which have several constraining conditions, was also not targeted. Rendering a comfortable path is beneficial for developing an acceptable system as a car developer and for building new curves for automated or driving assistance systems from the perspective of construction. The automated vehicle drove at a speed of 30 km/h on four courses, namely, clothoid, two types of spline curves, and arc, based on the real intersection. Each participant sat on both the driver and passenger seat and answered a questionnaire. The experimental data indicated the clothoid course to be the most comfortable, while the arc was most uncomfortable for a significance level of 1%. These tendencies are applicable to driver and passenger seats, all genders, and experiences and will be beneficial for human factor research in automated vehicle control.

Cellular Automata–Based Modeling and Simulation of a Mixed Traffic Flow of Manual and Automated Vehicles

2017 ◽  
Vol 2622 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Da Yang ◽  
Xiaoping Qiu ◽  
Lina Ma ◽  
Danhong Wu ◽  
Liling Zhu ◽  
...  
Keyword(s):  
Reaction Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Lane Change ◽  
Mixed Traffic ◽  
Automated Vehicles ◽  
Obvious Effect ◽  
Mixed Traffic Flow ◽  
Automated Vehicle

In recent years, automated vehicles have been developing rapidly, and some automated vehicles have begun to drive on highways. The market share of automated vehicles is expected to increase and will greatly affect traffic flow characteristics. This paper focuses on the mixed traffic flow of manual and automated vehicles. The study improves the existing cellular automaton model to capture the differences between manual vehicles and automated vehicles. Computer simulations are employed to analyze the characteristic variations in the mixed traffic flow under different automated vehicle proportions, lane change probabilities, and reaction times. Several new conclusions are drawn in the paper. First, with the increment of the proportion of automated vehicles, freeway capacity increases; the capacity increment is more significant for single-lane traffic than for two-lane traffic. Second, for single-lane traffic flow, reducing the reaction time of the automated vehicle can significantly improve road traffic capacity—as much as doubling it—and reaction time reduction has no obvious effect on the capacity of the two-lane traffic. Third, with the proportion increment of automated vehicles, lane change frequency reduces significantly. Fourth, when the density is 15 < ρ < 55 vehicles/km, the addition of 20% automated vehicles to a traffic flow that consisted of only manual vehicles can decrease congestion by up to 16.7%.

scholarly journals Investigating the Impacts of Road Traffic Conditions and Driver’s Characteristics on Automated Vehicle Takeover Time and Quality Using a Driving Simulator

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jaehyun Jason So ◽  
Sungho Park ◽  
Jonghwa Kim ◽  
Jejin Park ◽  
Ilsoo Yun
Keyword(s):  
Driving Simulator ◽  
Road Traffic ◽  
Vehicle Control ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Automated Vehicle ◽  
The Road ◽  
Traffic Conditions ◽  
Vehicle System ◽  
Driver’S Characteristics

This study investigates the impacts of road traffic conditions and driver’s characteristics on the takeover time in automated vehicles using a driving simulator. Automated vehicles are barely expected to maintain their fully automated driving capability at all times based on the current technologies, and the automated vehicle system transfers the vehicle control to a driver when the system can no longer be automatically operated. The takeover time is the duration from when the driver requested the vehicle control transition from the automated vehicle system to when the driver takes full control of the vehicle. This study assumes that the takeover time can vary according to the driver’s characteristics and the road traffic conditions; the assessment is undertaken with various participants having different characteristics in various traffic volume conditions and road geometry conditions. To this end, 25 km of the northbound road section between Osan Interchange and Dongtan Junction on Gyeongbu Expressway in Korea is modeled in the driving simulator; the experiment participants are asked to drive the vehicle and take a response following a certain triggering event in the virtual driving environment. The results showed that the level of service and road curvature do not affect the takeover time itself, but they significantly affect the stabilization time, that is, a duration for a driver to become stable and recover to a normal state. Furthermore, age affected the takeover time, indicating that aged drivers are likely to slowly respond to a certain takeover situation, compared to the younger drivers. With these findings, this study emphasizes the importance of having effective countermeasures and driver interface to monitor drivers in the automated vehicle system; therefore, an early and effective alarm system to alert drivers for the vehicle takeover can secure enough time for stable recovery to manual driving and ultimately to achieve safety during the takeover.

scholarly journals Predicting takeover response to silent automated vehicle failures

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242825
Author(s):  
Callum Mole ◽  
Jami Pekkanen ◽  
William Sheppard ◽  
Tyron Louw ◽  
Richard Romano ◽  
...  
Keyword(s):  
Cognitive Load ◽  
Predictive Model ◽  
Response Latency ◽  
Automated Vehicles ◽  
Experimental Examination ◽  
Response Latencies ◽  
Automated Vehicle ◽  
Failure Severity ◽  
Latency Variability ◽  
Human Monitoring

Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures.

scholarly journals Modeling Cross-National Differences in Automated Vehicle Acceptance

2020 ◽  
Vol 12 (22) ◽  
pp. 9765
Author(s):  
Shelly Etzioni ◽  
Jamil Hamadneh ◽  
Arnór B. Elvarsson ◽  
Domokos Esztergár-Kiss ◽  
Milena Djukanovic ◽  
...  
Keyword(s):  
Mode Choice ◽  
Continuous Distribution ◽  
Preference Heterogeneity ◽  
Type Model ◽  
Model Parameters ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Automated Vehicle ◽  
National Differences ◽  
Private Car

The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed.

Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time

2018 ◽  
Vol 60 (4) ◽  
pp. 465-476 ◽  
Author(s):  
Eric T. Greenlee ◽  
Patricia R. DeLucia ◽  
David C. Newton
Keyword(s):  
Safety Concern ◽  
Reaction Times ◽  
Vigilance Task ◽  
Time On Task ◽  
Vigilance Decrement ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Hazard Detection ◽  
And Performance

Objective: The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. Background: Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. Method: Participants “drove” a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. Results: As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. Conclusion: Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. Application: To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.

scholarly journals Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yong Zhang ◽  
Lei Shi ◽  
Jing Chen ◽  
Xuefeng Li
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Initial Period ◽  
Pso Algorithm ◽  
Automated Vehicles ◽  
Routing Problem ◽  
Automated Vehicle ◽  
Last Mile ◽  
The Cost

The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP) is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW) model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO) algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.

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