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Safe interaction between Autonomous Vehicles (AVs) and Vulnerable Road Users
Focusing on vehicles with advanced automated driving features, that is vehicles that allow the human driver to not execute the driving task when automation is engaged , this project contributes to the overall discourse on safety of automated driving vehicles in a twofold manner. First, it critically reviews the literature on the interaction between AVs and VRUs, discusses the recent developments and identifies the most prominent research gaps. Second, it shows results of an international online survey on the VRUs expectations, preferences and concerns with respect to their interaction with AVs.
Advanced automated driving vehicles (AVs) are expected to radically transform road transport by improving safety, increasing traffic flow efficiency, enhancing mobility for all, and reducing road congestion, fuel usage and emissions. To facilitate deployment research has vastly focused on ensuring the safety of AVs operation, investigating primarily the interaction between the human driver (or user depending on the level of automation) and the AV.
In addition to the interaction between the AV and its user, the successful deployment of AVs depends also on the exchange between AVs and other road users, also known as vulnerable road users (VRUs), such as pedestrians and cyclists, as well as motor-cyclists, people with disabilities or reduced mobility and orientation. For instance, what do cyclists and pedestrians anticipate when interacting with AVs; are AVs capable of recognizing cyclists and pedestrians in time; can AVs predict accurately the intentions of VRUs; and how shall AVs communicate their intentions to VRUs? Focusing on vehicles with advanced automated driving features, that is vehicles that allow the human driver to not execute the driving task when automation is engaged , this project contributes to the overall discourse on safety of automated driving vehicles in a twofold manner. First, it critically reviews the literature on the interaction between AVs and VRUs, discusses the recent developments and identifies the most prominent research gaps. Second, it shows results of an international online survey on the VRUs expectations, preferences and concerns with respect to their interaction with AVs.
We anticipate our findings to not only provide new insights on the interaction between automated driving vehicles and vulnerable road users, but also be instrumental for policy makers and other relevant actors involved with the development of automated driving technology.
Promising candidates have a strong background in statistics, while a background in transportation modelling and familiarity with survey design are no prerequisites, but helpful.
The thesis is to be performed within the Risk and Human Reliability Group at the Paul Scherrer Institute in Villigen, Switzerland. Interested students are encouraged to submit their application to Dr. Miltos Kyriakidis*, including a resume, course list, and current grades.
Advanced automated driving vehicles (AVs) are expected to radically transform road transport by improving safety, increasing traffic flow efficiency, enhancing mobility for all, and reducing road congestion, fuel usage and emissions. To facilitate deployment research has vastly focused on ensuring the safety of AVs operation, investigating primarily the interaction between the human driver (or user depending on the level of automation) and the AV.
In addition to the interaction between the AV and its user, the successful deployment of AVs depends also on the exchange between AVs and other road users, also known as vulnerable road users (VRUs), such as pedestrians and cyclists, as well as motor-cyclists, people with disabilities or reduced mobility and orientation. For instance, what do cyclists and pedestrians anticipate when interacting with AVs; are AVs capable of recognizing cyclists and pedestrians in time; can AVs predict accurately the intentions of VRUs; and how shall AVs communicate their intentions to VRUs? Focusing on vehicles with advanced automated driving features, that is vehicles that allow the human driver to not execute the driving task when automation is engaged , this project contributes to the overall discourse on safety of automated driving vehicles in a twofold manner. First, it critically reviews the literature on the interaction between AVs and VRUs, discusses the recent developments and identifies the most prominent research gaps. Second, it shows results of an international online survey on the VRUs expectations, preferences and concerns with respect to their interaction with AVs.
We anticipate our findings to not only provide new insights on the interaction between automated driving vehicles and vulnerable road users, but also be instrumental for policy makers and other relevant actors involved with the development of automated driving technology.
Promising candidates have a strong background in statistics, while a background in transportation modelling and familiarity with survey design are no prerequisites, but helpful.
The thesis is to be performed within the Risk and Human Reliability Group at the Paul Scherrer Institute in Villigen, Switzerland. Interested students are encouraged to submit their application to Dr. Miltos Kyriakidis*, including a resume, course list, and current grades.
To provide new insights on the interaction between automated driving vehicles and vulnerable road users
To support policy makers and other relevant actors involved with the development of automated driving technology
To provide new insights on the interaction between automated driving vehicles and vulnerable road users To support policy makers and other relevant actors involved with the development of automated driving technology