Fine-tuning Casual Loop Diagram
- Christina
- Mar 15, 2019
- 4 min read
Updated: Mar 17, 2019
System Dynamics for Smart City.
The autonomous vehicles (AV) as introduced in Sidewalk Labs’ proposal will transform the design of streets and how people move around the neighbourhood. The causal loop diagram visually represents the interrelationship between fully AV and its effect on transportation infrastructure and the environment in Toronto.
I began by brainstorming nouns/noun phrases for nodes. I started listing key variables identified from the RFP as well as from external research. The variables were selected if they can be quantified and measurable. As I was organizing the variables, I decided to consider transport and environment as two separate loops. I established the cause and effect relationship between the variables from each category and started to roughly place them in the formation of a loop. The most challenging part was to ensure that the nodes are organized in a loop that connects back to where it began. For example, establishing a connection between the AV User and Air Pollution was not obvious. Therefore, although it was not evident through the initial research, Carbon Tax was added.
Based on the research on the increased sale of AV, figure 1 illustrates the rapid increase in AV users over time. Region I represents the early phases of growth effort with the introduction of AV in the market where the reinforcing engine kicks in. Region II reflects the growing gap between the reinforcing and balancing loops. Region III is where they may be several possible outcomes and that it may go through several cycles of growth and decline. NHTSA statistics shows that 94% of car accidents are caused by human error or drivers’ bad decisions. Therefore, with more AV users, there is a significant increase in road safety and a decrease in collisions.
Figure 2 demonstrates a consequent increase in carbon emissions from an increase in AV users. The fully AV could “allow groups of people currently unable to drive—such as the elderly, young, and people with disabilities—to travel alone in autonomous vehicles, putting more people on the road.” In addition, the automation can lower opportunity cost of driving that could “encourage people to take more car trips or accept longer commutes, since drivers would be able to multitask in vehicles rather than focusing on the road.” As a result, with more vehicles on the road, it can increase carbon emissions as shown in figure 2. This could raise issues such as air pollution and climate change. Consequently, the government and the policy makers may take actions to begin charging a higher carbon tax.
"Limits to Success": When the "Best of Times" becomes the "Worst of Times"
In this “Limits to Success” scenario, continued efforts initially lead to improved performance. That is, with more AV users, road safety increases. Consequently, there are fewer collisions, one of the major contributing factors to traffic congestions. With fewer traffic congestions, it will put more AV users on the road including those who could have chosen walking, cycling, or taking the subway. This system creates a reinforcing loop, resulting in the action to grow. Over time, however, the system encounters a limit which causes the performance to decline. Increase in AV users will lead to environmental harm from increased carbon emission and increased air pollution. As a result, pollution pricing system such as carbon tax may be introduced as already done in several countries including Australia, Sweden, the Netherlands and Norway. This could lead to discouraging people from using AV. This creates a balancing loop, countering the increase in AV users.
The biggest factor that is limiting success is the environmental consequences due to carbon emissions. One leverage point is the use of electric AV. Concerns regarding fuel consumption and carbon emissions can benefit from electric AV. Wadud, MacKenzie, and Leiby suggest “Automation technology could encourage the deployment of electric vehicles by eliminating an important barrier to electric vehicle adoption—the anxiety about the widespread availability of refuelling infrastructure. Fully autonomous vehicles could travel to fueling stations to fuel up on their own.” With increased electric AV users, there is a decrease in carbon emission and air pollution resulting in less environmental costs. Another leverage point is car sharing. When large numbers of people travel by AV and yet give up their ownership and start sharing rides, it can reduce emission. According to the UT Austin study, shared AVs would be in near-constant motion, picking up and dropping off multiple passengers throughout the day. The engine would stay warm with fewer cold starts which will reduce emissions.
REFERNECES
Alexander-Kearns, Myriam, Miranda Peterson, and Alison Cassady. The Impact of Vehicle Automation on Carbon Emissions. November 2016. Washington, D.C., United States.
Culver, Michelle. "Autonomous Vehicle Sales to Surpass 33 Million Annually in 2040, Enabling New Autonomous Mobility in More Than 26 Percent of New Car Sales, IHS Markit Says." January 2, 2019. Accessed March 17, 2019. https://news.ihsmarkit.com/press-release/automotive/autonomous-vehicle-sales-surpass-33-million-annually-2040-enabling-new-auto.
Fagnant, Daniel J., Kara M. Kockelman, and Prateek Bansal. "Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market." Transportation Research Record: Journal of the Transportation Research Board 2536 (2015): 98-106. doi:10.3141/2536-12.
Kerlin, Kat. "Driverless Cars Could Be a Solution to Climate Change-but Two Major Things Have to Happen." The Washington Post. November 17, 2017. Accessed March 17, 2019. https://www.washingtonpost.com/sf/brand-connect/ucdavis/driverless-cars-could-be-a-solution-to-climate-change/.
Sidewalk Labs. Sidewalk Labs Vision Sections of RFP. October 17, 2017.
U.S. Department of Transportation. Critical Reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey. February 2015. Washington, D.C., United States.
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