Lec 16, LU Part 2: Scenarios & Assessment of transportation impacts on the urban activity system

Scenarios Envision Utah’s scenarios Assessment of transportation

impacts on the urban activity system

Major findings from regional workshops“Where do we grow?” “How do we grow?”

Participants placed greater population in infill areas than in new expansion or new town areas Favored more compact growth than sprawl Bar development above the

benchline Viable agricultural lands should be

preserved in the southern part of the region. Irrigated ones in the central and northern parts of the regions Rail and other non-automobile

modes essential East-west transportation links

needed (both road and rail) Waterways should be preserved as

greenway and trail networks Minimize development on the

Wasatch Back

Participants favored the walkable development types. Emphasized the need for

better east-west transportation connections (roads and transit), and indicated a general preference for transportation systems that balance the needs of the automobile with non-auto travel modes such as walking, bicycling, and transit use

Scenarios The use of future scenarios constructed on the basis

of professional judgment, current or expected trends, and so forth. We discussed that mathematical models including simulation are not always “the” best methods.

Scenario-based analyses are often viewed as being more hypothetical or conjectural in nature than model-based forecasts. Actually the Envision Utah’s scenarios suffered from this view initially.

Visit www.calthorpe.com then choose Project/Region/Envision Utah for more info about the Wasatch Front development issues.

Step 1: Identify key variables or attributes, then within that a set of criteria

Step 2: Convene conferences or workshops of experts, citizen groups, etc. to describe the value ranges for the criteria identified in step 2. (Two regional workshops took place for the 4 scenarios of Envision Utah: “Where do we grow?” & “How do we grow?.” And many other local community workshops took place)

Attributes considered by Envision Utah

Gateway value: Personal & Community Enrichment: Open space; Learning opportunity/school quality; Institutions that foster good values; Sense of community; Natural systems; Cultural opportunities

Gateway value: Safe & Secure Environment: Crowding; Crime, Shared ideas; values & morals; Traffic safety/accidents

Personal time & opportunity: Time-consuming activities; Leisure activity accessibility; personal health

Financial security: Income levels; Affordable living; Taxation

Examples of attributes and criteria

Crowding: Housing density Traffic congestion Population density Demands on recreational resources, etc

Open space: Viewsheds % of HH within ½ mi of a park (10 min walk) % of HH within 30min of a recreational area Prime farm land

Time-consuming activities: Avg. rush hour speeds Avg. trip time, length Total VMT Congested road miles Transit ridership & services

Business & job opportunities: No. of jobs added to region Industries locating in region

Envision Utah’s 4 scenarios & impacts

Scenario A: Auto-oriented sprawl (least controlled growth)

Scenario B: Baseline (Still auto-oriented but with some plans)

Envision Utah’s 4 scenarios & impacts (cont.)

Scenario C: Focus new development in walkable communities

Scenario D: Focus new development in existing urban centers

Envision Utah’s 4 scenarios & impacts (cont.)

Two approaches for the assessment of transportation impacts (section 6.3)

What has occurred which would not

have occurred if the transportation

system change had not been

implemented?

We are interested in a with and without comparison. But this is hard to do as the book explains

Ex Post Assessment: Evaluate the current condition with the previous one. Becomes a “before” and “after” comparison. With this we cannot answer the question above.

A Priori Assessment: This assessment is focused directly at the with and without level of analysis. The major problem with this is that it can estimated impacts only by using forecasted (rather than “real”) data. Good models are needed for this.