david pritchard. bibliography.

Notes on Miller, Kriger and Hunt, Integrated urban models for simulation of transit and land use policies [21]

I read the summary version of this report [22] several months ago. After reading about the structure of other simulations, the political and legal context, and the history of urban simulation, I returned to read this longer report.

This report forms the basis for the ILUTE project, which is now well underway. Miller et al. describe an "ideal model" for study of integrated transportation and land use, and compare five operational models.

From what they describe, it sounds like UrbanSim already meets many of the criteria of the ideal model, although I don't know all of the details. The primary remaining weakness of UrbanSim seems to be the omission of automobile ownership as a part of the model—to my mind, this is a huge weakness, one worth addressing. Auto ownership will have a large effect on housing location choice, and hence influence land use and transportation. To properly model automobile ownership does require a substantial amount of extra detail, and ILUTE's later directions into activity scheduling seem like a logical approach to understanding a household's automobile ownership needs.

• Interesting mention of the UK equivalent [30] of the American TRB panel appointed to look for the net impact of freeway construction on the environment [32]. I originally read of the TRB panel in [9], but they made no mention of the UK committee. According to the authors,

  A recent "blue ribbon" panel in the United States came to no definitive conclusion on this issue, while a similar study in the United Kingdom clearly endorsed the negative impact case. [p. 6]

• Quotes extensively from [17], discussing ISTEA and its successor, the Transportation Equity Act for the 21st Century (TEA-21) to justify need for integrated model.

• Discusses the Transport Model Improvement Program (TMIP) of the US DoT and the EPA. Six tracks: A. Outreach; B. Near-term improvements; C. Long-term improvements (via TRANSIMS project); D. Data; E. Land-Use; F. Freight.

• They identify their place as being in the land-use section. They list several areas they can contribute, and emphasize studying the role of transit in land use [p. 18].

• They performed interviews with land-use users. One interesting point: "virtually all respondents cited the need to be able to model the behavior of land markets and land rents at the microscopic level—i.e., at the level of individual households and individual land owners and developers" [p. 21]

• They've got a great overview of the literature on transportation/land use interaction. They first discuss how urban form affects travel behaviour, break it down by cause [pp. 27-39]:
  • residential density: many studies see density less of a direct explanatory variable for transit usage than [24] originally suggested, especially once other variables (such as those that follow) are included.
  • transit supply: this seems to be a better explanatory factor, but of course a supply-demand relationship exists between density and transit supply.
  • auto ownership: a frequently neglected link cause of travel behaviour. The transit/density connection outlined above leads to decisions regarding the number of automobiles a household owns, and this in turn reinforces transit usage / non-usage.
  • socio-economics: from my reading, they interpret density to be more important than socioeconomcs; they see socioeconomics affecting individuals' response to the (density in the) urban form. Consequently, they emphasise the need for good demographic models as inputs to ILUTE.
  • employment density: they see this aspect of density as understudied, and important. It is similar in many ways to residential density, with similar linkages to transit supply, etc.
  • accessibility: the literature is mixed here, likely because it often ignores connectivity, including density along travel corridors and distribution of activity destinations and origins.
  • neighbourhood design: important in its own right, but only one of many factors in a transportation-land use model.
  They also discuss how travel behaviour (specifically transit) affects urban form, on a city-by-city basis [pp. 39-47]. They conclude that

  transportation in general and rail transit in particular is a facilitator of development, not a cause: a "necessary but not sufficient condition" for development to occur. [p. 45]

  There are all sorts of good references in this section, summarized at length in Appendix A of their report. Amongst them: [7,26,28,27,5,6,15,29,11,20] and [14,16,10,13]

• Discussion of microsimulation techniques: many papers I've seen ([23,33]) and one I haven't [25].

• Population synthesis: [4,18] [p. 77]

• They also suggest using the individual lot as the unit of space, which was my hope. They agree that this can then be aggregated up to any desired level [pp. 78-79]

• They compare six existing operational models: ITLUP, MEPLAN, TRANUS, MUSSA, NYMTC-LUM and UrbanSim. NYMTC-LUM is an interesting one that I haven't read much about [1,2,3]. The comparison is highly informative, and thoroughly recommended, covering a broad range of issues. Overall, they try to avoid selecting winners or losers among the existing models; my interpretation, however, is that UrbanSim and MUSSA are closest to their vision of an integrated transportation/land use system, and NYMTC-LUM a little behind.

• UrbanSim also disaggregates to the parcel level [p. 101]

• They include an extremely useful summary of the policy capabilities of each model [pp. 119-121]. They also cite some critiques of four-stage travel models [12,19,31].
  
  

  Table 1: Policy Capabilities of Current Models - Land-Use

  Policy Category	Specific Policy	ITLUP	MEPLAN/ TRANUS	MUSSA	SYMTC-LUM	UrbanSim
  Pricing	Taxation - property taxes	N	Y	Y	Y	Y
  	Subsidies - BRZs (Business Redevelopment Zones)	N	Y	Y	Y	Y
  	Development Charges	+	Y	Y	Y	Y
  Infrastructure and Services	Public housing	N	Y	Y	Y	Y
  	Servicing land (excl. transportation; e.g., sewers, waters, wired city)	+	Y	Y	Y	Y
  	Government Buildings / other not-for-profit institutions (i.e., location of these as `seeds' / cores for development)	N	Y	Y	Y	Y
  Regulatory	Zoning (uses, densities)	+	Y	Y	Y	Y
  	Micro-design building / neighborhood issues (`shadowing,' pedestrian-scale massing, neo-traditional design, etc.)	N	N	Y	N	Y
  Education / Marketing	Changing / how to change attitudes and sensitivities (e.g., traveler `value of time' as opposed to deeply-held values)	+	+	+	+	+

  LEGEND
  Y	Explicit and normally / could be done
  N	No
  *	Implicit
  +	Can respond; but only through exogenous change in parameters.

  
  

  
  

  Table 2: Policy Capabilities of Current Models - Transportation

  Policy Category	Specific Policy	ITLUP	MEPLAN/ TRANUS	MUSSA	SYMTC-LUM	UrbanSim
  Pricing	Road tolls / congestion pricing	*	Y	*	*	*
  	Gas taxes	*	Y	*	*	*
  	Subsidies (capital, operating)	N	N	N	N	N
  	Transit fares	*	Y	*	*	*
  	Parking pricing	*	Y	*	*	*
  Infrastructure and Services	Build roads, HOV	Y	Y	Y	Y	Y
  	Build rail / dedicated transitways	+	Y	Y	Y	Y
  	Operate transit services	+	Y	Y	Y	Y
  	ITS (i.e., infrastructure technology; system optimization, TSM, etc.)	N	N	N	N	N
  	Parking	N	N	N	N	N
  Regulatory (see Note 1)	Parking provision regulations (off-street)	N	N	N	N	N
  	Rules of the road (speed limits, on-street parking, HOV lanes, traffic operations, etc.)	+	Y	Y	Y	Y
  	Non-pricing TDM (e.g., employer trip reduction programs, etc.)	N	N	N	N	N
  	Vehicle / Driver licensing (i.e., granting of access to the transportation system)	+	N	N	N	N
  	Inspection / Maintenance programs	N	N	N	N	N
  Education/Marketing	Changing / how to change attitudes and sensitivities (e.g., `traveler value of time' as opposed to deeply-held values)	+	+	+	+	+

  Note 1: The ability to address any or all of the specific regulatory policies listed in the table depends upon the travel demand forecasting model that is used. Also, whereas pricing can be considered somewhat dynamically (therefore, an `implicit' * designation), the same cannot be said for infrastructure or regulation (therefore, mostly `no' N).

  LEGEND
  Y	Explicit and normally / could be done
  N	No
  *	Implicit
  +	Can respond; but only through exogenous change in parameters.

  
  

  
  

  Table 3: Policy Capabilities of Current Models - Other

  Policy Category	Specific Policy	ITLUP	MEPLAN/ TRANUS	MUSSA	SYMTC-LUM	UrbanSim
  Pricing	Auto purchase tax	N	N	N	N	N
  	License charges	N	N	N	N	N
  	Income redistribution (e.g., progressive taxation, welfare, etc.)	+	Y	Y	Y	Y
  Infrastructure and Services	N/A	N/A	N/A	N/A	N/A	N/A
  Regulatory (see Note 1)	Air quality standards (area-wide)	N	N	N	N	N
  	Emissions standards (vehicle specific)	*	Y	Y	*	*
  	Noise	*	*	*	*	*
  	Safety (accidents)	*	*	*	*	*
  	Vehicle technology standards (e.g., must have 10% electric vehicles in CA, etc.)	N	N	N	N	N
  Education/Marketing	Changing / how to change attitudes and sensitivities (e.g., `traveler value of time' as opposed to deeply-held values)	+	+	+	+	+

  Note 1: Air quality is designated as a `no' (N), while some other policies are designated as `implicit' (*), because air quality tends to be addressed as a post-travel demand model analysis.

  LEGEND
  Y	Explicit and normally / could be done
  N	No
  *	Implicit
  +	Can respond; but only through exogenous change in parameters.

  
  

  [pp. 119-121]

• Overall summary of the models:
  • All models are sensitive to transit- and land-use interactions to varying extents. The two major limitations in this regard have been the large zones traditionally used in these models, and the level of transit representation in the travel demand component of the modeling system. Use of traffic zones in more recently developed models, plus general improvements in travel demand modeling methods, bode well for improved transit sensitivity in integrated urban models. Applications of models such as MUSSA and the NYMTC-LUM family of models to the analysis of major transit alternatives provide good examples of the usefulness of integrated urban models for transit planning.

  • All currently operational models fall short of the ideal model to varying degrees. Areas of significant shortfall in most models include:
    • excessive spatial aggregation;
    • excessive reliance on static equilibrium assumptions (with associated assumptions of large time steps and lack of path dependencies);
    • overly aggregate representations of households and firms, as well as a lack of representation of individuals as decision-making units separable from their households;
    • lack of endogenous demographic processes;
    • lack of endogenous auto ownership processes; and
    • reliance on four-stage travel demand modeling methods.

    Of the models reviewed, UrbanSim clearly comes closest to the ideal model specification with respect to most of these points, including: spatial disaggregation (use of parcels to model land development), temporal aggregation (use of one-year time steps), dynamics (disequilibrium model), detailed disaggregations of households and firms (an attribute shared by MUSSA), and use of activity-based travel models (on-going in the Honolulu application).

  • At the same time, current models individually and collectively display many strengths and generally provide a solid basis for further evolutionary improvements. Strengths include:
    • generally strong microeconomic formulations of land and housing/floorspace market processes;
    • coherent frameworks for dealing with transportation - land-use interactions;
    • multimodal transportation network analysis capabilities; and
    • experience with developing and using large-scale integrated models.

  • Despite the scope for significant evolutionary development among existing models, a "new generation" of integrated models will need to be developed in order to fully achieve the ideal model. While newer models such as MUSSA and UrbanSim point the way to more disaggregate and/or more dynamic models, much research and development must be undertaken in order to fully achieve the ideal model. This will include development of and experimentation with model structures which are explicitly designed to operate in a more disaggregate, dynamic, non-equilibrium framework.

  [pp. 127, 131]

• They discuss in detail the funding issues facing integrated model development.

• They argue in favour of a broader database for interurban comparisons, etc. See also [8].

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