An Assessment of Land Use and Socioeconomic Forecasts in the Baltimore Region (1981)

 ©Antti Talvitie, Michael Morris, Mark Anderson, 2016

An Assessment of Land Use and Socioeconomic Forecasts in the Baltimore Region

Transportation Research Record (1981) (with M. Morris and M. Anderson).

Antti Talvitie (aptalvitie(at)gmail.com)

Michael Morris and Mark Anderson

ABSTRACT

Accuracy of forecasts for population, labor force, employment, and car ownership from 1962 to 1975 in the Baltimore area are examined. Comparisons are made at three levels of zonal aggregation-city and suburbs, traffic districts, and traffic zones. The lack of information about household size and household income made inferences from the results incomplete. The results show that regionwide forecasts were accurate for all the variables except population. However, allocation of these forecasts between city and suburbs, to traffic districts, and to traffic zones was quite inaccurate. The correlation coefficient between predicted and actual changes varied from 0.93 to 0.17 for the city zones and from 0.28 to 0.02 for the suburban zones. The corresponding ranges at the traffic-district level were from 0.86 to 0.61 and from 0.36 to 0.30, respectively. The results in the paper point toward large errors and uncertainties in the independent variables of traditional traveldemand models.

An Equilibrium Model System For Transportation Corridors (1980)

 

©Antti Talvitie, Ibrahim Hasan

An Equilibrium Model System For Transportation Corridors

Transportation Research-B, Vol. 14B, pp. 165-174, 1980, Pergamon Press. (with I. Hasan).

Antti Talvitie (aptalvitie(at)gmail.com)

State University of New York, Buffalo, NY 14214, U.S.A.

and

Ibrahim Hasan

University of California, Berkeley, CA 94721, U.S.A.

ABSTRACT

The paper describes a method for equilibrating travel demand and transport levei of service when both demand and service levels are expressed by means of equations. Following the non-rigorous presentation of the method, its application as part of a complete model system in a transportation corridor study is discussed.

Models for Transportation Level of Service (1980)

 

©Antti Talvitie and Youssef Dehghani, 1980

Models for Transportation Level of Service

Transportation Research-B, Vol. 14B, pp. 87-99, 1980, Pergamon Press. (with Y. Dehghani)

Antti Talvitie (aptalvitie(at)gmail.com)
and Youssef Dehghani

State University of New York at Buffalo, Buffalo, NY 14214, U.S.A.

ABSTRACT

The paper describes the development of models for predicting travel times of door to door trips for both transit and automobile trips. The models for access times have a distribution associated with them and permit a truly disaggregate assignment of travel time components. The equations for linehaul travel time of the highway using modes (bus, auto) are volume dependent and can thus be used in equilibrating travel demand and level of service. All the models are related directly to transportation policy options-changing bus line spacings, bus headways, number of (priority) lanes, etc.-and translate the effects of such policies into specific values of the level-of-service attributes without the need to code networks and run paths. The use of the models in a practical application is also discussed.

Inaccurate or Incomplete Data as a Source of Uncertainty in Econometric or Attitudinal Models of Travel Behavior (1979)

©Antti Talvitie, 1973

Inaccurate or Incomplete Data as a Source of Uncertainty in Econometric or Attitudinal Models of Travel Behavior

New Horizons in Travel Behavior, Brög, W., A.H. Meyburg, and P. Stopher, Eds. D.C. Heath, Lexington, MA. 1979.

Antti Talvitie (aptalvitie(at)gmail.com)

ABSTRACT

The chapter discusses the uncertainties and errors in level-of-service data, in land-use and socioeconomic data, and in behavior data, and their effects on models and forecasts of travel behavior. Evidence is shown to suggest that there are substantial errors in transportation level-of-service data and in forecast land-use and socioeconomic data. Of the service variables, the excess time components and auto costs are especially poorly approximated. There also is uncertainty about what car costs ought to be calculated, and how. It is shown that these decisions affect the choice models significantly. The allocation of land-use and socioeconomic variables to traffic zones is done quite inaccurately, even though the totals for the region may be predicted well. Population forecasts, which may mean household-size forecasts, appear to be subject to a large degree of uncertainty. Finally, the chapter discusses briefly the uncertainties present in travel-behavior interviews. It is claimed that intrasubjective and intersubjective uncertainties are inevitable in any interview and that their effects are many and substantial but presently unknown.

Comparison of Observed and Coded Network Travel Time and Cost Measurements (1979)

 

©Antti Talvitie, Youssef Dehghani, 1979

Comparison of Observed and Coded Network Travel Time and Cost Measurements

Transportation Research Record 723, pp. 46-51, Washington, D.C. 1979 (with Y. Dehghani).

Antti Talvitie and Youssef Dehghani,

State University of New York, Buffalo

ABSTRACT

The paper compares two types of measurements of trip times: those provided by the standard network algorithms are compared with trip-time components observed along the traveler's path from home to work and back. The two types of measurements are found to be different. The root mean square errors of the network measurements with respect to observed values are very large (75-135 percent of the mean value) for the non-line-haul travel time components. The means and the variances of the network measured variables, as a rule, are much smaller than the variances or means of the manually coded observed-travel times. Coefficients estimated by using the two types of data are not numerically similar. Statistical tests show that at least the alternative-specific constants' and the level-of-service variables' coefficients are different in the models developed by using the two types of data. Finally, the effect of substantial errors in level-of-service measurements on travel forecasts is discussed. It is also shown that good (short-run) travel forecasts can be obtained from the network-based models provided that consistent network coding conventions are followed and incremental forecasts are avoided.