Document Type

Closed Project

Publication Date

Fall 2017

Instructor

Antonie Jetter

Course Title

Front End Management of New Product Development

Course Number

ETM 543/643

Subjects

Technology -- Management, Autonomous vehicles -- Applications to traffic congestion, New products -- Management, Emerging technologies, Disruptive technologies -- Management

Abstract

Continuing population growth and urbanization are projected to add 2.5 billion people to the world’s urban population by 2050. It is evident that this will increase traffic congestion especially in the urban areas, which will bring economic, safety, environmental and quality of life challenges. There are various organizations looking for possible solutions to reduce the impact of future congestion by long term planning, most of these studies don’t take into account emergence of disruptive technologies. The concept of a connected autonomous vehicle (CAV) is an emerging technology [3] which may contribute to the solution of this problem through adoption. This paper aims to shed light on effect of different levels of CAV adoption on congestion through scenario planning with fuzzy cognitive mapping. Different future scenarios on CAV adoption based on research and development being done on CAV technology are run through a fuzzy cognitive model of congestion developed through detailed literature review. Results indicate CAV adoption provides an opportunity for reducing congestion. Therefore suggesting, investing in CAV enabling upgrades of existing roads, and giving incentives for CAV adoption, is a viable option for city planners’ and local governments’ project portfolios to reduce congestion.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Comments

This project is only available to students, staff, and faculty of Portland State University

Persistent Identifier

http://archives.pdx.edu/ds/psu/23254

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