scholarly journals Effects of gender, age, experience, and practice on driver reaction and acceptance of traffic jam chauffeur systems

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Husam Muslim ◽  
Makoto Itoh ◽  
Cho Kiu Liang ◽  
Jacobo Antona-Makoshi ◽  
Nobuyuki Uchida
Keyword(s):  
Traffic Congestion ◽  
Simulation Experiment ◽  
Demographic Factors ◽  
Driving Simulation ◽  
Lane Change ◽  
Automated Driving ◽  
Left Hand ◽  
Traffic Jam ◽  
Automated Vehicle ◽  
The Individual

AbstractThis study conducted a driving simulation experiment to compare four automated driving systems (ADS) designs during lane change demanding traffic situations on highways while accounting for the drivers’ gender, age, experience, and practice. A lane-change maneuver was required when the automated vehicle approaches traffic congestion on the left-hand lane. ADS-1 can only reduce the speed to synchronize with the congestion. ADS-2 reduces the speed and issues an optional request to intervene, advising the driver to change lanes manually. ADS-3 offers to overtake the congestion autonomously if the driver approves it. ADS-4 overtakes the congestion autonomously without the driver’s approval. Results of drivers’ reaction, acceptance, and trust indicated that differences between ADS designs increase when considering the combined effect of drivers’ demographic factors more than the individual effect of each factor. However, the more ADS seems to have driver-like capacities, the more impact of demographic factors is expected. While preliminary, these findings may help us understand how ADS users’ behavior can differ based on the interaction between human demographic factors and system design.

Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non–Driving-Related Tasks in Automated Vehicles

2021 ◽  
pp. 001872082110562
Author(s):  
Xiaomeng Li ◽  
Ronald Schroeter ◽  
Andry Rakotonirainy ◽  
Jonny Kuo ◽  
Michael G. Lenné
Keyword(s):  
Mobile Phone ◽  
Real World ◽  
Simulation Experiment ◽  
Driving Simulator ◽  
Reaction Times ◽  
Driving Simulation ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Driver Performance ◽  
Vehicle Technology

Objective The study aims to investigate the potential of using HUD (head-up display) as an approach for drivers to engage in non–driving-related tasks (NDRTs) during automated driving, and examine the impacts on driver state and take-over performance in comparison to the traditional mobile phone. Background Advances in automated vehicle technology have the potential to relieve drivers from driving tasks so that they can engage in NDRTs freely. However, drivers will still need to take-over control under certain circumstances. Method A driving simulation experiment was conducted using an Advanced Driving Simulator and real-world driving videos. Forty-six participants completed three drives in three display conditions, respectively (HUD, mobile phone and baseline without NDRT). The HUD was integrated with the vehicle in displaying NDRTs while the mobile phone was not. Drivers’ visual (e.g. gaze, blink) and physiological (e.g. ECG, EDA) data were collected to measure driver state. Two take-over reaction times (hand and foot) were used to measure take-over performance. Results The HUD significantly shortened the take-over reaction times compared to the mobile phone condition. Compared to the baseline condition, drivers in the HUD condition also experienced lower cognitive workload and physiological arousal. Drivers’ take-over reaction times were significantly correlated with their visual and electrodermal activities during automated driving prior to the take-over request. Conclusion HUDs can improve driver performance and lower workload when used as an NDRT interface. Application The study sheds light on a promising approach for drivers to engage in NDRTs in future AVs.

scholarly journals Effects of Marking Automated Vehicles on Human Drivers on Highways

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 286 ◽  
Author(s):  
Tanja Fuest ◽  
Alexander Feierle ◽  
Elisabeth Schmidt ◽  
Klaus Bengler
Keyword(s):  
Road Traffic ◽  
Driving Behavior ◽  
Sensor Technology ◽  
Lane Change ◽  
Objective Data ◽  
Automated Vehicles ◽  
Traffic Jam ◽  
Automated Vehicle ◽  
Time Headway ◽  
First Time

Due to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as carefully as human learners do. In the same way that driving-school vehicles tend to be marked in Germany, markings for automated vehicles could also prove advantageous. To this end, a simulation study with 40 participants was conducted. All participants experienced three different highway scenarios, each with and without a marked automated vehicle. One scenario was based around some roadworks, the next scenario was a traffic jam, and the last scenario involved a lane change. Common to all scenarios was that the automated vehicles strictly adhered to German highway regulations, and therefore moved in road traffic somewhat differently to human drivers. After each trial, we asked participants to rate how appropriate and disturbing the automated vehicle’s driving behavior was. We also measured objective data, such as the time of a lane change and the time headway. The results show no differences for the subjective and objective data regarding the marking of an automated vehicle. Reasons for this might be that the driving behavior itself is sufficiently informative for humans to recognize an automated vehicle. In addition, participants experienced the automated vehicle’s driving behavior for the first time, and it is reasonable to assume that an adjustment of the humans’ driving behavior would take place in the event of repeated encounters.

scholarly journals Concept of an Ontology for Automated Vehicle Behavior in the Context of Human-Centered Research on Automated Driving Styles

Information ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 21
Author(s):  
Johannes Ossig ◽  
Stephanie Cramer ◽  
Klaus Bengler
Keyword(s):  
Driving Behavior ◽  
Automation System ◽  
Automated Driving ◽  
Driving Style ◽  
Driving Experience ◽  
Automated Vehicle ◽  
Future Design ◽  
Vehicle System ◽  
The Future ◽  
Conceptual Distinction

In the human-centered research on automated driving, it is common practice to describe the vehicle behavior by means of terms and definitions related to non-automated driving. However, some of these definitions are not suitable for this purpose. This paper presents an ontology for automated vehicle behavior which takes into account a large number of existing definitions and previous studies. This ontology is characterized by an applicability for various levels of automated driving and a clear conceptual distinction between characteristics of vehicle occupants, the automation system, and the conventional characteristics of a vehicle. In this context, the terms ‘driveability’, ‘driving behavior’, ‘driving experience’, and especially ‘driving style’, which are commonly associated with non-automated driving, play an important role. In order to clarify the relationships between these terms, the ontology is integrated into a driver-vehicle system. Finally, the ontology developed here is used to derive recommendations for the future design of automated driving styles and in general for further human-centered research on automated driving.

scholarly journals Effects of User Interfaces on Take-Over Performance: A Review of the Empirical Evidence

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 162
Author(s):  
Soyeon Kim ◽  
René van Egmond ◽  
Riender Happee
Keyword(s):  
User Interface ◽  
Situation Awareness ◽  
User Interfaces ◽  
Situational Awareness ◽  
Selection Criterion ◽  
Auditory Modality ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Positive Effects ◽  
High Urgency

In automated driving, the user interface plays an essential role in guiding transitions between automated and manual driving. This literature review identified 25 studies that explicitly studied the effectiveness of user interfaces in automated driving. Our main selection criterion was how the user interface (UI) affected take-over performance in higher automation levels allowing drivers to take their eyes off the road (SAE3 and SAE4). We categorized user interface (UI) factors from an automated vehicle-related information perspective. Short take-over times are consistently associated with take-over requests (TORs) initiated by the auditory modality with high urgency levels. On the other hand, take-over requests directly displayed on non-driving-related task devices and augmented reality do not affect take-over time. Additional explanations of take-over situation, surrounding and vehicle information while driving, and take-over guiding information were found to improve situational awareness. Hence, we conclude that advanced user interfaces can enhance the safety and acceptance of automated driving. Most studies showed positive effects of advanced UI, but a number of studies showed no significant benefits, and a few studies showed negative effects of advanced UI, which may be associated with information overload. The occurrence of positive and negative results of similar UI concepts in different studies highlights the need for systematic UI testing across driving conditions and driver characteristics. Our findings propose future UI studies of automated vehicle focusing on trust calibration and enhancing situation awareness in various scenarios.

scholarly journals Platoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategies

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2626
Author(s):  
Carlos Hidalgo ◽  
Ray Lattarulo ◽  
Carlos Flores ◽  
Joshué Pérez Rastelli
Keyword(s):  
Trajectory Planning ◽  
Traffic Congestion ◽  
Efficient Solutions ◽  
Test Case ◽  
Cruise Control ◽  
Automated Driving ◽  
Modular Architecture ◽  
The Road ◽  
Cooperative Adaptive Cruise Control ◽  
Multiple Vehicles

Currently, the increase of transport demands along with the limited capacity of the road network have increased traffic congestion in urban and highway scenarios. Technologies such as Cooperative Adaptive Cruise Control (CACC) emerge as efficient solutions. However, a higher level of cooperation among multiple vehicle platoons is needed to improve, effectively, the traffic flow. In this paper, a global solution to merge two platoons is presented. This approach combines: (i) a longitudinal controller based on a feed-back/feed-forward architecture focusing on providing CACC capacities and (ii) hybrid trajectory planning to merge platooning on straight paths. Experiments were performed using Tecnalia’s previous basis. These are the AUDRIC modular architecture for automated driving and the highly reliable simulation environment DYNACAR. A simulation test case was conducted using five vehicles, two of them executing the merging and three opening the gap to the upcoming vehicles. The results showed the good performance of both domains, longitudinal and lateral, merging multiple vehicles while ensuring safety and comfort and without propagating speed changes.

Traffic Congestion Reduction and Accident Circumvention System via Incorporation of CAV and VANET

2021 ◽  
Vol 12 (1) ◽  
pp. 53-72
Author(s):  
Mohsin Khan ◽  
Bhavna Arora
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Traffic Congestion ◽  
Ad Hoc Network ◽  
Discrete System ◽  
Ad Hoc ◽  
New Age ◽  
The Real ◽  
Automated Vehicle ◽  
The Core

Connected automated vehicle (CAV) technology is the core for the new age vehicles in research phase to communicate with one another and assimilation of vehicular ad-hoc network (VANET) for the transference of data between vehicles at a quantified place and time. This manuscript is an enactment of the algorithms associated to the maintenance of secure distance amongst vehicles, lane shifting, and overtaking, which will diminish the occurrence of collisions and congestions especially phantom jams. Those implementations are centered over CAV and VANET technology for the interconnection of the vehicles and the data transmission. The data is associated to the aspects of a vehicle such as speed, position, acceleration, and acknowledgements, which acts as the fundamentals for the computation of variables. In accordance with the environment of a particular vehicle (i.e., its surrounding vehicles), real-time decisions are taken based on the real-time computation of the variables in a discrete system.

Safety Impact of Weaving Distance on Freeway Facilities with Managed Lanes using Both Microscopic Traffic and Driving Simulations

2018 ◽  
Vol 2672 (39) ◽  
pp. 130-141 ◽  
Author(s):  
Qing Cai ◽  
Moatz Saad ◽  
Mohamed Abdel-Aty ◽  
Jinghui Yuan ◽  
Jaeyoung Lee
Keyword(s):  
Traffic Safety ◽  
Traffic Congestion ◽  
Driving Simulator ◽  
Negative Impact ◽  
Control Strategies ◽  
General Purpose ◽  
Valuable Insight ◽  
Lane Change ◽  
Simulation Studies ◽  
Managed Lanes

With the challenges of increasing traffic congestion, the concept of managed lanes (MLs) has been gaining popularity recently as a means to effectively improve traffic mobility. MLs are usually designed to be left-lane concurrent with an at-grade access/exit. Such a design forms weaving segments since it requires vehicles to change multiple general purpose lanes (GPLs) to enter or exit the ML. The weaving segments could have a negative impact on traffic safety in the GPLs. This study provides a comprehensive investigation of the safety impact of different lengths for each lane change maneuver on GPL weaving segments close to the ingress and egress of MLs through two simulation approaches: VISSIM microsimulation and driving simulator. The two simulation studies are developed based on traffic data collected from freeway I-95 in Miami, Florida. The results from the two simulation studies support each other. Based on the two simulation studies, it is recommended that 1,000 feet be used as the optimal length for per lane change at the GPLs weaving segments with MLs. The safety impact of traffic volume, variable speed limit control strategies, and drivers’ gender and age characteristics are also explored. This study can provide valuable insight for evaluating the traffic performance of freeway weaving segments with the presence of concurrent GPLs and MLs in a highway safety context. It also provides guidelines for future conversion of freeways to include MLs.

scholarly journals Two Major Elements of Life Recovery After a Disaster: Their Impacts Dependent on Housing Damage and the Contributions of Psycho-Behavioral Factors

2021 ◽  
Vol 16 (7) ◽  
pp. 1107-1120
Author(s):  
Shosuke Sato ◽  
Ryo Ishibashi ◽  
Motoaki Sugiura ◽  
◽  
Keyword(s):  
Factor Analysis ◽  
Emotional Regulation ◽  
Demographic Factors ◽  
Well Being ◽  
Major Elements ◽  
Behavioral Factors ◽  
Educational Approach ◽  
Tsunami Disaster ◽  
Housing Recovery ◽  
The Individual

Clarification of the individual factors determining the speed and quality of life recovery after massive disasters is crucial in assessing the vulnerability and resilience of individuals and communities. The research, however, remains in its infancy in that the index of life recovery per se is yet to be established; researchers have utilized different sets of variables, and their importance seems to vary across recovery phases potentially reflecting the change in housing situation. In addition, previous research on promoting factors of life recovery has primarily focused on demographic factors and inadequately addressed the psychological and behavioral factors, which has large educational and cultural implications. In this study, to address these two issues, we analyzed the survey data of the 2011 Great East Japan Earthquake and Tsunami disaster. First, from the multiple questionnaire items relevant to the situations of life recovery, we extracted the major elements by factor analysis and investigated their relationship to subjective sense of life recovery. At this time, we compared the relationships obtained between victims who lost their housing and those who did not. Then, we examined the psycho-behavioral as well as demographic factors promoting these life-recovery elements. The factor analysis provides two recovery elements: Well-being (health and social connections) and Housing Recovery (integrity of residential environment). The main determinant of subjective sense of life recovery was the housing recovery element for victims who had lost their houses, while it was the well-being element for those who did not experience housing loss. Among the demographic factors, a robust effect of income on the housing recovery element was identified in both victim groups while the effect of age and household structures on the two elements varied between groups. We clarified that different psycho-behavioral factors promoted two life-recovery elements. Across groups, contribution of leadership to the housing recovery element and that of neuroticism (negative), emotional regulation, and active well-being to the well-being element were identified. The former finding is consistent with the importance of consensus building in housing reconstruction, and the latter may reflect the role of common psycho-behavioral capacity oriented to individuals’ well-being including social aspects. The two life-recovery elements and their promoting factors thus identified may provide a parsimonious macroscopic framework for the evaluation and promotion of life recovery from disasters, and have practical utility for an educational approach to strengthening community resilience.

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