Determinants of a safe interaction between Vulnerable Road Users and Automated Vehicles using Fuzzy Cognitive Mapping

Determinants of a safe interaction between Vulnerable Road Users and Automated Vehicles using Fuzzy Cognitive Mapping

Arends, Erik (TU Delft Civil Engineering and Geosciences; TU Delft Transport and Planning)

Hagenzieker, Marjan (mentor)
Annema, Jan Anne (graduation committee)
Nuñez Velasco, Pablo (graduation committee)
de Kievit, Eric (graduation committee)

Delft University of Technology

Transport, Infrastructure and Logistics

2017-08-17

The technology of automated driving systems that assist the human driver are in ongoing development and could potentially improve traffic safety and efficiency. At this moment, a lot of research into automated vehicles is carried out. The City of Amsterdam wants to know what impact AVs can have on traffic safety in their city. Most studies focus on the technology of the vehicle itself and its impact on society. An increasing number of studies is focussing on the human aspects, although most of these researches focus on the driver, while questions remain unanswered on vulnerable road users. At this moment, it is challenging to gain insights in the system of interaction. Due to the still-evolving technology of AVs, the impact on traffic safety cannot be accurately predicted. City of Amsterdam want to start pilots to test AVs on the public roads in order to gain insight in te system of a safe mutual interaction between automated vehicles and vulnerable road users.

First, the system of interaction needs to be known. Using the methodology of Fuzzy Cognitive Mapping (FCM), the determinants and behaviour of the system is identified. FCM is a fairly new method in the field of transport planning, but showed potential for this specific research in which scientific data is limited. The original approach to develop a FCM model is adapted. Therefore, the time it took to develop a conceptual FCM model during a workshop could have been limited and disadvantages of one strategy is balanced or mitigated with the advantages of other stragegies. This research is therefore also assessing if FCM can be a useful method in the field of transport planning.

The FCM model that describes that system of interaction is developed via a literature study and subsequent workshop. This resulted in a model of 21 determinants with 72 connections or relationships. Computations showed that the most important (key) determinants were the following concepts: Safe crossing behaviour, VRU friendly road design, AV friendly road design, Intelligent infrastructure and Identification and recognition. These key determinants, who each describe an idea of something formed by mentally combining all its characteristics or particulars, are considered most important in the system of interaction and should therefore be first be researched in pilots.

The results of the workshop and computations provide a first glance at the system and results. Interviews provided extensive state-of-the-art knowledge on the key determinants. The findings from the interviews are translated into an advice for the City of Amsterdam te develop and execute pilots. These pilots should be able to answer the most important and relevant research questions on the safe mutual interaction between automated vehicles and vulnerable road users in the urban environment.

FCM is found to be useful in the field of transport planning for specific case in which scientific research is limited, with a lack of quantitative data, but available qualitative data from professionals and where human behaviour plays an important role. For the still developing technology of automated driving systems, the method can be useful for as long as quantitative data is not available. As soon as such data is available, other methods are found to be more useful.

Automated vehicles
Vulnerable Road User
Determinants
Interactions
Fuzzy Cognitive Mapping
Urban Environment
Amsterdam

http://resolver.tudelft.nl/uuid:d6cb95fd-8a6d-4f94-8d37-37b8ee40f5ae

52.3616815, 4.9077197

Student theses

master thesis

© 2017 Erik Arends