Poster Abstract: Hierarchical Hybrid-State Systems for Coordinated Autonomous Driving in Mixed-Traffic Urban Environments

2012 ◽  
Author(s):  
Arda Kurt ◽  
Scott Biddlestone ◽  
Keith Redmill ◽  
Umit Özgüner
Keyword(s):  
Autonomous Driving ◽  
Urban Environments ◽  
Mixed Traffic ◽  
Poster Abstract ◽  
Hybrid State

scholarly journals Factors Influencing and Contributing to Perceived Safety of Passengers during Driverless Shuttle Rides

2021 ◽  
Vol 1 (3) ◽  
pp. 657-671
Author(s):  
Claudia Luger-Bazinger ◽  
Cornelia Zankl ◽  
Karin Klieber ◽  
Veronika Hornung-Prähauser ◽  
Karl Rehrl
Keyword(s):  
Autonomous Driving ◽  
Future Research ◽  
Natural Setting ◽  
Mixed Traffic ◽  
Control Room ◽  
Driving Style ◽  
Perceived Safety ◽  
Factors Influencing ◽  
Traffic Environment ◽  
Set Up

This study investigates the perceived safety of passengers while being on board of a driverless shuttle without a steward present. The aim of the study is to draw conclusions on factors that influence and contribute to perceived safety of passengers in driverless shuttles. For this, four different test rides were conducted, representing aspects that might challenge passengers’ perceived safety once driverless shuttles become part of public transport: passengers had to ride the shuttle on their own (without a steward present), had to interact with another passenger, and had to react to two different unexpected technical difficulties. Passengers were then asked what had influenced their perceived safety and what would contribute to it. Results show that perceived safety of passengers was high across all different test rides. The most important factors influencing the perceived safety of passengers were the shuttle’s driving style and passengers’ trust in the technology. The driving style was increasingly less important as the passengers gained experience with the driverless shuttle. Readily available contact with someone in a control room would significantly contribute to an increase in perceived safety while riding a driverless shuttle. For researchers, as well as technicians in the field of autonomous driving, our findings could inform the design and set-up of driverless shuttles in order to increase perceived safety; for example, how to signal passengers that there is always the possibility of contact to someone in a control room. Reacting to these concerns and challenges will further help to foster acceptance of AVs in society. Future research should explore our findings in an even more natural setting, e.g., a controlled mixed traffic environment.

scholarly journals Seamless Vehicle Positioning by Lidar-GNSS Integration: Standalone and Multi-Epoch Scenarios

2021 ◽  
Vol 13 (22) ◽  
pp. 4525
Author(s):  
Junjie Zhang ◽  
Kourosh Khoshelham ◽  
Amir Khodabandeh
Keyword(s):  
Autonomous Driving ◽  
Measurement Model ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
High Definition ◽  
Satellite Systems ◽  
The Road ◽  
Gnss Receivers ◽  
Vehicle Positioning ◽  
Global Navigation Satellite

Accurate and seamless vehicle positioning is fundamental for autonomous driving tasks in urban environments, requiring the provision of high-end measuring devices. Light Detection and Ranging (lidar) sensors, together with Global Navigation Satellite Systems (GNSS) receivers, are therefore commonly found onboard modern vehicles. In this paper, we propose an integration of lidar and GNSS code measurements at the observation level via a mixed measurement model. An Extended Kalman-Filter (EKF) is implemented to capture the dynamic of the vehicle movement, and thus, to incorporate the vehicle velocity parameters into the measurement model. The lidar positioning component is realized using point cloud registration through a deep neural network, which is aided by a high definition (HD) map comprising accurately georeferenced scans of the road environments. Experiments conducted in a densely built-up environment show that, by exploiting the abundant measurements of GNSS and high accuracy of lidar, the proposed vehicle positioning approach can maintain centimeter-to meter-level accuracy for the entirety of the driving duration in urban canyons.

scholarly journals A Robust Registration Method for Autonomous Driving Pose Estimation in Urban Dynamic Environment Using LiDAR

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 43 ◽  
Author(s):  
Rendong Wang ◽  
Youchun Xu ◽  
Miguel Angel Sotelo ◽  
Yulin Ma ◽  
Thompson Sarkodie-Gyan ◽  
...  
Keyword(s):  
Dynamic Environment ◽  
Point Clouds ◽  
Autonomous Driving ◽  
Initial Position ◽  
Urban Environments ◽  
Data Set ◽  
Registration Method ◽  
Position Errors ◽  
Initial Errors ◽  
High Dynamic

The registration of point clouds in urban environments faces problems such as dynamic vehicles and pedestrians, changeable road environments, and GPS inaccuracies. The state-of-the-art methodologies have usually combined the dynamic object tracking and/or static feature extraction data into a point cloud towards the solution of these problems. However, there is the occurrence of minor initial position errors due to these methodologies. In this paper, the authors propose a fast and robust registration method that exhibits no need for the detection of any dynamic and/or static objects. This proposed methodology may be able to adapt to higher initial errors. The initial steps of this methodology involved the optimization of the object segmentation under the application of a series of constraints. Based on this algorithm, a novel multi-layer nested RANSAC algorithmic framework is proposed to iteratively update the registration results. The robustness and efficiency of this algorithm is demonstrated on several high dynamic scenes of both short and long time intervals with varying initial offsets. A LiDAR odometry experiment was performed on the KITTI data set and our extracted urban data-set with a high dynamic urban road, and the average of the horizontal position errors was compared to the distance traveled that resulted in 0.45% and 0.55% respectively.

scholarly journals Occlusion-Aware Risk Assessment for Autonomous Driving in Urban Environments

2019 ◽  
Vol 4 (2) ◽  
pp. 2235-2241 ◽  
Author(s):  
Ming-Yuan Yu ◽  
Ram Vasudevan ◽  
Matthew Johnson-Roberson
Keyword(s):  
Risk Assessment ◽  
Autonomous Driving ◽  
Urban Environments

scholarly journals The Model of the Optimal Number of Public Transport Vehicles in Mixed Traffic Flow Conditions: A Case Study

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Milja M. Simeunović ◽  
Vuk Z. Bogdanović ◽  
Milan M. Simeunović ◽  
Pavle M. Pitka ◽  
Zoran M. Papić ◽  
...  
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Public Transport ◽  
Transport Model ◽  
Optimal Number ◽  
Urban Environments ◽  
Mixed Traffic ◽  
Street Network ◽  
Mixed Traffic Flow ◽  
Flow Parameters

Bus passenger transport is very important for sustainable urban mobility, and due to the characteristics of the street network, it is usually realized in the conditions of mixed traffic flow. Disturbances and sudden changes of traffic flow parameters occurring in the street network in a mixed traffic flow affect the disruptions in schedule and travel time of all vehicles in the traffic flow, including public transport (PT) vehicles. In order to keep to the planned schedule in the peak hours of PT lines carried out in the conditions of mixed traffic flow, the operators introduce new vehicles or reduce the vehicles’ dwell time at terminuses, which is often impossible to do. The use of a larger number of public transport vehicles increases the fuel consumption, pollutants’ emission, and the operating costs. In this paper, a network optimization model was developed for defining the influence of the change of traffic flow parameters in a mixed traffic flow on travel time of PT vehicles. The model takes into consideration uncertain time unevenness of the change of traffic flow parameters, which enables determining the optimization of travel time and defining the necessary number of public transport vehicles for the purpose of keeping to the planned schedule. In order to develop the transport model, counting and analysis of the characteristics of traffic flow at 61 intersections on the city territory were carried out. The model was tested on bus line number 4 of PT in Novi Sad. The model showed that it is possible to achieve certain savings regarding the number of vehicles with the unchanged headway, that is, the unchanged level of service which is offered to the users. With the application of the model in real traffic conditions, significant savings, as well as operating and external costs’ reduction, can be achieved, which contributes to the sustainability of public bus transport in urban environments.

CUbE: A Research Platform for Shared Mobility and Autonomous Driving in Urban Environments

2019 ◽  
Author(s):  
Andreas Hartmannsgruber ◽  
Julien Seitz ◽  
Matthias Schreier ◽  
Matthias Strauss ◽  
Norbert Balbierer ◽  
...  
Keyword(s):  
Autonomous Driving ◽  
Urban Environments ◽  
Shared Mobility ◽  
Research Platform
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