scholarly journals Report on validation of the stochastic traffic simulation (Part A)

2021 ◽  
Author(s):  
Madlen Ringhand ◽  
◽  
Maximilian Bäumler ◽  
Christian Siebke ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Urban Areas ◽  
Human Subject ◽  
Driving Simulator ◽  
Traffic Simulation ◽  
Relevant Literature ◽  
Driver Behaviour ◽  
Automotive Engineering ◽  
Driving Behaviour ◽  
Simulator Study ◽  
Behaviour Models

This document is intended to give an overview of the human subject study in a driving simulator that was conducted by the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD) to provide the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD with the necessary input for the validation of a stochastic traffic simulation, especially for the parameterization, consolidation, and validation of driver behaviour models. VPSY planned, conducted, and analysed a driving simulator study. The main purpose of the study was to analyse driving behaviour and gaze data at intersections in urban areas. Based on relevant literature, a simulated driving environment was created, in which a sample of drivers passed a variety of intersections. Considering different driver states, driving tasks, and traffic situations, the collected data provide detailed information about human gaze and driving behaviour when approaching and crossing intersections. The collected data was transferred to LKT for the development of the stochastic traffic simulation.

scholarly journals Report on validation of the stochastic traffic simulation (Part B)

2021 ◽  
Author(s):  
Maximilian Bäumler ◽  
◽  
Madlen Ringhand ◽  
Christian Siebke ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Real World ◽  
Driving Simulator ◽  
Traffic Simulation ◽  
Relevant Literature ◽  
Assessment Process ◽  
Maximum Speed ◽  
Real World Data ◽  
World Data ◽  
Driving Behaviour

This document is intended to give an overview of the validation of the human subject study, conducted in the driving simulator of the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD), as well of the validation of the stochastic traffic simulation developed in the AutoDrive project by the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD. Furthermore, the evaluation process of a C-AEB (Cooperative-Automatic Emergency Brake) system is demonstrated. The main purpose was to compare the driving behaviour of the study participants and the driving behaviour of the agents in the traffic simulation with real world data. Based on relevant literature, a validation concept was designed and real world data was collected using drones and stationary cameras. By means of qualitative and quantitative analysis it could be shown, that the driving simulator study shows realistic driving behaviour in terms of mean speed. Moreover, the stochastic traffic simulation already reflects reality in terms of mean and maximum speed of the agents. Finally, the performed evaluation proofed the suitability of the developed stochastic simulation for the assessment process. Furthermore, it could be shown, that a C-AEB system improves the traffic safety for the chosen test-scenarios.

scholarly journals AN EVALUATION OF AIRPORT WAYFINDING AND SIGNAGE ON SENIOR DRIVER BEHAVIOUR AND SAFETY OF AIRPORT ROAD ACCESS DESIGN

2017 ◽  
Vol 8 (1) ◽  
pp. 108-129
Author(s):  
Nur Khairiel Anuar ◽  
Romano Pagliari ◽  
Richard Moxon
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Age Groups ◽  
Driver Behaviour ◽  
Driving Behaviour ◽  
Road Design ◽  
Driver Performance ◽  
Study Participants ◽  
The Impact ◽  
Car Driving

The purpose of this study was to investigate the impact of different wayfinding provision on senior driving behaviour and road safety. A car driving simulator was used to model scenarios of differing wayfinding complexity and road design. Three scenario types were designed consisting of 3.8 miles of airport road. Wayfinding complexity varied due to differing levels of road-side furniture. Experienced car drivers were asked to drive simulated routes. Forty drivers in the age ranges: 50 to 54, 55 to 59 and those aged over 60 were selected to perform the study. Participants drove for approximately 20 minutes to complete the simulated driving. The driver performance was compared between age groups. Results were analysed by Mean, Standard Deviation and ANOVA Test, and discussed with reference to the use of the driving simulator. The ANOVA confirmed that age group has a correlation between road design complexity, driving behaviour and driving errors.

scholarly journals Validating Driver Profiles in the Daimler Traffic Simulation

2018 ◽  
Author(s):  
Fabian Dablander
Keyword(s):  
Driving Simulator ◽  
Traffic Simulation ◽  
Scientific Practice ◽  
Empirical Studies ◽  
Hierarchical Regression ◽  
Measurement Tool ◽  
Bayesian Hierarchical ◽  
Regression Methods ◽  
Driving Behaviour ◽  
Online Appendix

Driving simulators offer benefits such as a controlled, standardized, and thus replicable environment for experiments; ease of collecting highly accurate and precise measurements; and an overall high cost-effectiveness. To reap these benefits, however, driving simulation must be a valid measurement tool — behaviour observed in the simulation should generalize to the real road. Crucial for this is the behaviour of computer-generated drivers with which the driver interacts. The Daimler traffic simulation assumes, based on empirical studies, six distinct driver profiles. Does the behaviour of computer-generated drivers resemble human driving behaviour? Two experiments were conducted. In a simulation study, we tested whether we can recover the driver profile based on simulated driving data. While driver profiles were well separated in low and medium traffic scenarios, separation decreased in high traffic scenarios. These results are discussed and further studies suggested. In a driving simulator experiment, we tested whether the aggressive and calm driver profile improved upon an older version of the traffic simulation that lacked dedicated driver profiles. 32 participants had to judge whether the driver they encountered behaved like a human or computer, and had to provide realism judgements of its driving behaviour. Using Bayesian hierarchical regression methods, we found evidence that the driving behaviour of the aggressive driver is judged to stronger resemble human driving compared to the older version; other results were equivocal. I discuss these results and suggest improvements for future studies. Finally, in an online appendix, I discuss some of the exciting changes happening in scientific practice and culture. This includes a brief sketch of the “reproducibility crisis” in psychology, a tutorial on Bayesian statistics, and three practical recommendations for applied researchers.

Effectiveness of augmented reality warnings on driving behaviour whilst approaching pedestrian crossings: A driving simulator study

2020 ◽  
Vol 147 ◽  
pp. 105760 ◽  
Author(s):  
Alessandro Calvi ◽  
Fabrizio D’Amico ◽  
Chiara Ferrante ◽  
Luca Bianchini Ciampoli
Keyword(s):  
Augmented Reality ◽  
Driving Simulator ◽  
Driving Behaviour ◽  
Simulator Study

Standard freeway merge designs support safer driver behaviour compared to taper designs: a driving simulator study

Ergonomics ◽  
2020 ◽  
Vol 63 (4) ◽  
pp. 407-420
Author(s):  
Hammad Hussain Awan ◽  
Ali Pirdavani ◽  
Muhammad Adnan ◽  
Ansar-ul-Haque Yasar ◽  
Geert Wets ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Driver Behaviour ◽  
Simulator Study

Effect of surrounding landscape on driving behaviour: A driving simulator study

2009 ◽  
Vol 29 (4) ◽  
pp. 493-502 ◽  
Author(s):  
Hans Antonson ◽  
Selina Mårdh ◽  
Mats Wiklund ◽  
Göran Blomqvist
Keyword(s):  
Driving Simulator ◽  
Driving Behaviour ◽  
Simulator Study ◽  
Surrounding Landscape
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