Practical Method for The Estimation of Trip Generation And Trip Chaining

Konstadinos G. Goulias · Ram M. Pendyala · Ryuichi Kitamura

18 citations0/0 files storedRePEc: Research Papers in Economics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Transportation Planning and Optimization Urban Transport and Accessibility Human Mobility and Location-Based Analysis

Abstract

A model system of trip generation and trip chaining was developed by integrating concepts from activity-based analysis. The structure of the model system is recursive, depicting a sequential decision-making mechanism. The results were based on a data set from the Detroit metropolitan area. They were compared with those of a previous study that used a data set from the Netherlands. Differences were observed not only in the values of the regression parameters estimated but also in the decision mechanism inferred.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 18 citations exist upstream.

Cited by

2014A time series analysis of passenger rail demand in major Australian cities 2017Determination of Trip Attraction Rates of Shopping Centers in Uttara Area, Dhaka 2021Home-Based urban commute and Non-Commute trip generation in Less-Studied Contexts: Evidence from Cairo, Istanbul, and Tehran 2011Empirical Analysis of Commuters’ Nonwork Stop-Making Behavior in Beijing, China 2013An Empirical Analysis of the Determinants of Passenger Rail Demand in Melbourne, Australia 2018Location-based transport demand forecasting methods for suburbanized areas

Imported from OpenAlex (CC0) — nothing here is generated.