Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting

This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at S?o Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.

Comparison of Travel Mode Choice Between Taxi and Subway Regarding Traveling Convenience

In this study, we investigate travel mode choice behavior between taxi and subway with an emphasis on the influence of traveling convenience. In the first stage, we examine the Origin-Destination(OD) points of Beijing taxi trips and compare these locations with the respective nearest subway station. Statistics reveal several interesting conclusions. First, for approximately 24.89% of all trips, no convenient subway connections exist between the OD pairs. As such, a taxi becomes the only viable choice. Second, for 80.23% of the remaining 75.11%of trips(equivalent to 60.26% of all trips), access distance from either the origin or the destination to the nearest subway station is greater than 500 meters. This phenomenon indicates that walking distance plays an important role in travel mode choice. In the second stage, we examine groups of taxi trips with similar travel distances and travel times to reveal common features. We establish a preference rule in terms of travel distance and travel time.This determines whether an individual driver will take a taxi or the subway, using a pairwise comparison-based preference regression model. Tests indicate that more than 95% of taxi trips can be correctly predicted by this preference rule. This conclusion reveals that traveling convenience dominates the travel model choice between taxi and subway. All these findings shed light on the factors that influence travel mode choice behavior.

Combinatorial Model Involving Stochastic Choices of Destination, Mode and Route

Traffic assignment models are one of the basic tools for the analysis and design of transportation systems. However, the existing models have some defects. Considering the characteristics of Chinese urban mixed traffic and the randomness of transportation information, the author develops a combinatorial model involving stochastic choices of destination, mode and route. Its uniqueness and equivalance are also proved by the optimization theory.

Modelling of Active and Latent Attributes Based on Traveler Perspectives: Case of Port City of Douala

A growing stream of study stresses the relevance of subjective elements in understanding the hierarchy of preferences that underpin individual travel behavior. The purpose of this study is to evaluate the impact of various factors on mode choice. To achieve this, a multinomial logit model (MNL) was used to analyze the relationships between mode choice and three classes of attributes;Combined Active and Latent, Active only and Latent only attributes. The data used are derived from surveys in the port city of Douala, Cameroon as a case study. Results stipulated that, the combined attributes model performed better than both active only attributes and latent only attributes models. Likewise, latent only attributes model performed better than active only attributes model. The advantage of modelling all three groups is for better selection of the most relevant attributes, and this is very relevant in understanding travel behavior of individuals and mode choice decisions.

Recent Transition in Transportation Environment in Jakarta Metropolitan Area Over Years

The Jakarta metropolitan area of Indonesia with more than 24 million populations is the capital region of one of the emerging countries.Along with economic development,the number of motorized trips,especially,use of motorcycles has been rapidly increasing.Two surveys that were conducted in 2002 and 2010,Household Travel Survey(HTS)and Commuter Travel Survey(CTS),revealed significant alteration in,for example,transportation pattern,income,mode share,mode choice,and so on in Jakarta metropolitan area.Number of population as well as number of registered vehicle is increasing.Existence of BRT also indicated changes in mode choice before and after the introduction of the BRT system in 2004.The characteristics of these preferences were also identified.

Calibration of a rule-based intelligent network simulation model

This paper is focused on calibration of an intelligent network simulation model （INS1M） with reallife transportation network to analyse the INSIM＇s feasibility in simulating commuters＇ travel choice behaviour under the influence of real-time integrated multimodal traveller information （IMTI）. A transportation network model for the central and western areas of Singapore was simulated in PARAMICS and integrated with INSIM expert system by means of an application programming interface to form the INSIM. Upon calibration, INSIM was able to realistically present complicated scenarios in which real-time IMTI was provided to commuters and the network performance measures being recorded.

Transportation Users’ Attitudes and Choices of Ride-Hailing Services in Two Cities with Different Attributes

The rapid technological developments in the 21st century created new opportunities for shared-use economy applications around the globe. Among other services, Transportation Network Companies (TNCs) like Uber and Lyft emerged in the US as a transportation alternative that offered a higher level of availability, reliability, and convenience than traditional modes. However, TNCs deployment was also blamed for increases in vehicle miles traveled (VMT) in large cities that embraced TNC services early on. Concerns about TNC adoption are also magnified by the current controversy in policy and legislation as to the regulation of TNCs. These new realizations create a need to examine the transportation users’ attitudes and perceptions regarding ride-hailing service, after nearly a decade of service in the Unites States market. In doing so, this paper compares and contrasts results from two recently completed studies aiming at creating links between socio-demographic factors and TNC use. The paper describes the methods employed to collect the data and presents findings from the analysis of 790 users’ responses in the Birmingham, AL and Miami Beach, FL markets. The study documents preferences and attitudes toward TNCs and highlights similarities and differences in travel behaviors related to local considerations. Moreover, the study uses the Least Absolute Shrinkage and Selection Operator (Lasso) method to identify predictors for TNC use based on the users’ responses in Birmingham and Miami Beach case studies. Vehicle availability and waiting time emerged as the only significant predictors for the Birmingham region whereas vehicle ownership, vehicle use, residency, and prior use of transit and TNC where some of the predictors identified for the Miami Beach area. Understanding the characteristics of TNC users and the leading reasons that drive people towards the use of TNCs services is expected to help transportation agencies and TNC providers in their efforts to plan for transportation services that meet customer needs in the future.

Integrated Network Design and Demand Forecast for On-Demand Urban Air Mobility

Urban air mobility(UAM)is an emerging concept proposed in recent years that uses electric vertical takeoff and landing vehicles(eVTOLs).UAM is expected to offer an alternative way of transporting passengers and goods in urban areas with significantly improved mobility by making use of low-altitude airspace.In addition to other essential elements,ground infrastructure of vertiports is needed to transition UAM from concept to operation.This study examines the network design of UAM on-demand service,with a particular focus on the use of integer programming and a solution algorithm to determine the optimal locations of vertiports,user allocation to vertiports,and vertiport access-and egress-mode choices while considering the interactions between vertiport locations and potential UAM travel demand.A case study based on simulated disaggregate travel demand data of the Tampa Bay area in Florida,USA was conducted to demonstrate the effectiveness of the proposed model.Candidate vertiport locations were obtained by analyzing a three-dimensional(3D)geographic information system(GIS)map developed from lidar data of Florida and physical and regulation constraints of eVTOL operations at vertiports.Optimal locations of vertiports were determined to achieve the minimal total generalized cost;however,the modeling structure allows each user to select a better mode between ground transportation and UAM in terms of generalized cost.The outcomes of the case study reveal that although the percentage of trips that switched from ground mode to multimodal UAM was small,users choosing the UAM service benefited from significant time saving.In addition,the impact of different parameter settings on the demand for UAM service was explored from the supply side,and different pricing strategies were tested that might influence potential demand and revenue generation for UAM operators.The combined effects of the number of vertiports and pricing strategies were also analyzed.The findings from this study offer in-depth planning and managerial insights for municipal decision-makers and UAM operators.The conclusion of this paper discusses caveats to the study,ongoing efforts by the authors,and future directions in UAM research.

Analysis of Transportation Users’ Preferences and Attitudes for Identifying Micro-Level Determinants of Transportation Network Companies’ (TNCs) Growth

Over the last decade, the popularity of Transportation Network Companies (TNCs) as a mode of travel has been increasing at a steady pace. This trend highlights the importance of identifying the determinants that influence transportation users to adopt TNCs as a preferred mode choice and the impacts of such preferences on their travel patterns and transportation network operation. This paper reports on a recent study undertaken in Birmingham, AL aiming at understanding and documenting the factors that influence transportation users to select TNCs (such as Uber/Lyft) for completing typical day trips. In doing so, a travel diary questionnaire survey was developed in accordance with the Institute of Transportation Engineers (ITE) Manual on Transportation Engineering Studies using the Qualtrics Research Core platform. The questionnaire was used to survey over 450 transportation users in the Birmingham Metro area. The survey participants provided detailed trip information for a typical 24-hr day along with demographic data and travel preference information. The survey responses provide high-resolution micro-level indicators of travel preferences and behaviors in a TNC-served area, which is a much-needed type of information for researchers and transportation planning agencies.

基于地理加权回归模型探索小学生通勤方式选择的区域异质性

Commuting is an important part of primary school students' travel behavior, which has been concerned for a long time. We found that the commute-mode choice behavior of primary school students in the context of regional segmentation shows strong characteristics in space, but has not yet been considered in traditional research. To fill this gap, this study summarizes the commute-mode choices of primary school students with different characteristics based on the Beijing School Commute Survey. And the geographically weighted regression(GWR) model is built to analyze the zonal heterogeneity of the impact of personal characteristics, family factors and school factors on the primary school students' commutemode choices from a low-carbon perspective. The results demonstrate that the possibility of primary school students choosing low-carbon commuting modes is positively correlated with the grade, commuting time, commuting escort type and housing category, but is inversely related with the commuting distance and the distance from the school to the city center. The coefficient estimates of explanatory variables vary across regions. Finally, we put forward policy suggestions regarding promoting the low-carbon commuting structure, such as developing the urban slow traffic system, which serve as a reference for policymakers.

MANAGING REDISTRIBUTION OF TOLL REVENUE WITH USER HETEROGENEITY

With the explicit consideration of user heterogeneity, i.e., each user has a different value of time （VOT）, this paper examines the system efficiency and social equity of toll revenue redistribution in a bi-mode transportation system. Three schemes of distributing the road toll revenue are proposed, which respectively consider efficiency, equity, as well as efficiency and equity together. With mild assumptions, we prove that the number of auto-motorists decreases and the total social cost increases with transit subsidy share when only marginal operating cost of the transit is covered by its fare. However, when average fixed cost of the transit is further covered, the total social cost is a ＂U＂ shape curve against the transit subsidy share. Numerical results show that the well designed toll revenue redistribution schemes can make the system more equitable while keeping high efficiency. With the increase of user heterogeneity, the Gini coefficient becomes larger while the total social cost goes down.