Mode Choice Modeling Using Personalized Travel Time and Cost Data

Abstract

The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation University Transportation Centers Program and the Florida Department of Transportation, in the interest of information exchange. The U.S. Government and the Florida Department of Transportation assume no liability for the contents or use thereof. The opinions, findings, and conclusions expressed in this publication are those of the authors and not necessarily those of the State of Florida Department of Transportation.

Ride-hailing Impacts on Transit Ridership: Chicago Case Study

“…While there is no existing literature that definitively states how ride-hailing services impact public transit ridership, many stipulate a correlation between the two, and if ride-hailing is a contributor, it is likely not acting alone. This absence of trip data has led researchers to obtain empirical data through stated preference (SP) and revealed preference (RP) surveys [8][9][10][11]. Some studies executed intercept surveys at points of interest [12], and one executing in-person interviews [13].Yet to our knowledge, there exists no research on the relationship between ride-hailing and public transit that is uses source-data.…”

“…Data processing was completed in three steps, with the ultimate output being the probability of a rider choosing public transit. This probability is derived from a multinomial nested logit (MNL) model based on the Chicago's travel behaviors in 2015 [11]. This model is descriptively explained, and its relevancy is introduced later in this section.…”

“…We compared our methodology and dataset against these models to determine which existing utility model was most suitable. We selected the multinomial nested logit (MNL) model developed by Javanmardi et al [11]. Their model was developed from a revealed preference survey using Google Maps API and RTA's Goroo TripPlanner trip data.…”

“…we used. The constant and coefficient values, and variables are mode-specific and were provided[11]. Utility of Transit, UTransit = 2.93 − 1.04 − 0.13 − 0.17 − 0The equations were executed in the respective order per trip, with Equation 6 outputting the final probability used in the analyses.…”

The welfare costs of traffic congestion in São Paulo Metropolitan Area

“…Yet a more interesting alternative has recently emerged: the use of a Google Maps API to obtain the missing data (JAVANMARDI et al, 2015;LUZ, 2017). Google Maps has made its Application Programming Interface publicly available, so it is possible to collect data from Google's data bank in a large scale.…”