Public Transport Mode Share Research Articles

How electric bikes reduce car use: A dual-mode ownership perspective

Electric bikes (e-bikes) can play a vital role in sustainable transportation and reducing car dependence. However, questions persist regarding the extent to which e-bikes contribute to replacing and complementing car use and other modes, especially from dual-mode ownership (households with both cars and e-bikes) perspective. Utilizing the Household Travel Survey dataset from Jiading, Shanghai, this study reveals that: (1) e-bikes can lead up to a 19% reduction in car mode share in dual-mode ownership households compared to car-only households; (2) e-bikes encourage a greater variety of non-commuting activities compared to car-only households; (3) e-bikes have a minor negative effect on public transport mode share, while e-bikes enhance mobility for older people. Overall, these findings underscore the importance of e-bikes in reducing car dependence and achieving development goals towards sustainable transportation and age-friendly cities.

Modeling travel mode choice behavior for planned special events using CPT-based HI-MADM approach

ABSTRACT Planned special events (PSEs) can significantly increase traffic demand, posing greater challenges than daily operations. In response, host cities often invest heavily in transportation upgrades. This study proposes a model integrating cumulative prospect theory (CPT) and multiple-attribute decision-making to understand mode choice behavior of PSE attendees. This integration enables direct extraction of traveler preference information, offering a more suitable description of the decision-making process. The decision matrix considers mode and attribute heterogeneity. The reference point for CPT is derived from previous PSE trips or commutes. Furthermore, this paper assesses asymmetric nonlinear sensitivity and distorted perceptions of different attributes. Analysis of mode-choice behavior for PSE participation, using survey data from Tianjin, China, validates the approach. It better characterizes PSE choice behaviors and demonstrates varying sensitivity to gains and losses, dependent on different attributes and distances. Thus, event planners should prioritize improving travel time and convenience to increase public transport mode share.

Exploring the Macro Economic and Transport Influencing Factors of Urban Public Transport Mode Share: A Bayesian Structural Equation Model Approach

The public transportation priority strategy is a significant way to alleviate urban traffic congestion, and the urban public transport mode share (UPTMS) is a crucial indicator to measure the performance of public transportation priority strategies. To explore the influence factors of UPTMS, this study hypothesized that UPTMS is influenced by factors such as population, economy, road operation performance, public transport infrastructure, and private transport facilities, and tested the hypotheses using structural equation modeling (SEM) and Bayesian structural equation modeling (BSEM) based on urban macro economic and transport data in Guangzhou and Beijing, China. The results showed that, in the case of a small sample, BSEM is more adept at examining the correlation between the UPTMS and its influencing factors than SEM; in the Guangzhou and Beijing models, public transport infrastructure has the greatest positive and most significant impact on the UPTMS, and road operation performance has the greatest negative and most significant impact. Moreover, road operation performance is significantly improved by public transport infrastructure, while private transport facilities have a significant negative influence on road operation performance.

Analyzing Public Transport Mode Share by Generational Cohort in Montreal Canada (1998-2018)

This paper observes generational public transport mode share in Montreal, Canada by age group using five Origin-Destination Surveys from 1998 to 2018. Using total number of trips to work and school by public transport, the findings indicate that younger generations have higher public transport use in early adulthood which corresponds to higher use later in life compared to previous generations. Across generations, public transport mode share decreases significantly for individuals in their late twenties and thirties before stabilizing and, in some cases, increasing after the age of forty. For exclusively school bound trips, the findings suggest that expanding students’ discount for those 25 and older was the most impactful for students in their thirties and that return diminishes with older ages.

Estimation of urban network capacity with second-best constraints for multimodal transport systems

Transport network capacity enhancement is a significant aspect of urban transport planning and demand management, and a suitable measurement of the network capacity is of considerable importance. In this paper, the network capacity with second-best constraints (NCSC) is investigated to meet some specific development requirements of urban transport networks. Herein, the network capacity is restricted to an inferior “second-best solution”, due to various concerns/constraints regarding the public transport mode share, serviceability, and emissions, etc. For the sake of presentation, these constraints are termed as second-best constraints, and the NCSC problem can also be referred as second-best network capacity (SBNC) problem. A bi-level model is formulated to analyse the NCSC problem. The upper-level model maximizes the total origin-destination (OD) demand, which incorporates the second-best constraints into consideration. The lower-level model is a transport network equilibrium model, which measures the network performance under a given OD demand pattern. To better investigate some important second-best constraints (e.g., public transport mode share) and also the demand elasticity, the modelling framework is extended to a multimodal transport network. An exact solution method is developed for the NCSC problem; wherein, a modified improved gradient projection (MIGP) algorithm is designed for the lower-level multimodal flow equilibrium problem, and a tailored sensitivity analysis-based (SAB) method is employed for solving the NCSC problem. The proposed models and solution methods are verified by numerical examples, demonstrating that NCSC can be an efficient tool for transport planning and management.

Investigating the association between population density and travel patterns in Indian cities—An analysis of 2011 census data

Many transport planners consider urban population density to be a significant determinant of travel behaviour. Much of the evidence for this comes from research in low-density, high-income settings. The 2011 Census of India reported mode of travel to work and distance for the first time. We have used these data to investigate the effect of urban density on commute travel patterns at city-level for Indian cities. In addition, we investigated the relationship between travel behaviour and other city-level variables. Using regression, we found almost no independent effect of density on the mode share of walk, cycle, motorised two-wheelers, cars and public transport, after controlling for population and income levels for the cities. Further, it appears that once density levels are greater than ~80 persons per hectare (pph), other factors become more important in determining travel patterns in cities. This evidence has significant implications for urban planning and transport policy in Indian cities and for many other low- and middle-income cities where average density tends to be higher than ~80 pph. For these cities, growth in the use of sustainable transport may not depend on further densification of already dense cities, but on details of how neighbourhoods and streets are designed.

Accessibility matters: Exploring the determinants of public transport mode share across income groups in Canadian cities

Planning for accessibility is increasingly considered in the development of equitable plans by transport agencies and it has also been shown to exert a positive influence on public transport use. However, this influence has not been examined across income groups and in different geographic regions of varying sizes. The present study measures the relationship between accessibility and mode choice for low- and higher-income groups in eleven Canadian metropolitan regions. Our results show that the impact of accessibility on public transport mode share is stronger and non-linear for the low-income group especially in the largest metropolitan areas, where increasing accessibility past a certain optimal value will lead to a decrease in public transport mode share. However, this point occurs at the 80th percentile of existing accessibility, so improvements in mode share are nonetheless expected with improved accessibility in most areas within these regions. Moreover, in regions where an optimal value is not readily observed, improved accessibility throughout the region would lead to increased uptake of public transport for both the higher- and to a greater extent, the low-income group. Findings from this paper can be of value to transport professionals working towards meeting ridership goals around the world as comparisons between groups and across regions highlight the variation in the impacts of accessibility on mode share.

User retention tendency of bus routes based on user behavior transition in an area with low mode share of public transport

Although both public transport and private modes have their own purposes and safety issues, most people are free to choose either way to make a trip. Previous research states that increasing the mode share of public transport is an important transportation policy to improve traffic safety, and it is a key outcome of demand management indeed. However, rather than merely focusing on increasing its ridership, a more reliable way to reach for the universality of a public transport system is through its customer retention tendency. Research on satisfaction with bus service often focuses on the influence of specific variables. However, numerous variables may influence users' decision-making. To ease their work, managers have no choice but to ignore some unknown variables. Therefore, we now propose a bottom-up procedure, which needs only smart card data, to obtain the odds ratio of usage of a specific bus route. Logistic regression models are calibrated based on four behavior groups, and the significant coefficients of route variables represent the odds ratios of the bus route usage. The calibration of odds ratio does not need any individual personal or individual socio-economical information, but only smart card transaction data. This method will dramatically decrease the cost and time for data collection. Further, the procedure proposed in this study can be encapsulated in software, which managers can then use to assist their planning.

Peaking CO2 emissions for China's urban passenger transport sector

Due to economic development and urbanization, the number of car ownership continues to increase, making the urban passenger transport sector becoming an important contributor for energy consumption and CO2 emissions in China (accounting for around 20% of the total carbon emissions of the transport sector in 2016). Hence, how the urban passenger transport sector can contribute to peaking China's carbon dioxide emissions by 2030 is worthy of attention. To that end, we develop a National Energy Technology-Transport (NET-Transport) model to assess the impacts of shifting to alternative clean fuels, improving vehicle fuel efficiency, and promoting public transportation on the future energy demand and CO2 emissions for China's urban passenger transport sector. The results show that in the context of promoting the use of clean fuel vehicles and increasing vehicle fuel efficiency, CO2 emissions of China's urban passenger transport sector could reach a peak of 225 MtCO2 in 2030. If the mode share of public transport could further increase, the CO2 emissions from the urban passenger transport sector in China are possible to peak at around 2020 with the emissions ranging from 171 to 214 MtCO2.

Analysis of the acceptance of park-and-ride by users: A cumulative logistic regression approach

Park-and-ride (P&R) schemes are an important way of increasing the public transport mode share, which relieves the negative impact caused by excessive automobile usage. Several existing studies have been conducted in the past to explore the factors that can influence the acceptance of P&R by travelers. However, quantitative analyses of the pertinent factors and rates of traveler choice are quite rare. In this paper, the data collected from a survey in Melbourne, Australia, is used to analyze the acceptance of P&R by travelers going to the central business district (CBD). In particular, we explore the influence that specific factors have on the choice of travel by those who are currently using P&R. The results indicate that the parking fee in the CBD area, travel time on public transport, and P&R transfer time affect traveler use of P&R. A quantitative assessment of the impact of these three factors is conducted by using a cumulative logistic regression model. Results reveal that the P&R transfer time has the highest sensitivity while public transport travel time has the least. To maximize the use of P&R facilities and public transport, insights into setting parking fees and designing P&R stations are presented.

Updated Models of Passenger Transport Related Energy Consumption of Urban Areas

Introduction: As the global warming threat has become more concrete in recent years, there is a need to update transport energy consumptions of cities and to understand how they relate to population density and transport infrastructure. Transportation is one of the major sources of global warming and this update is an important warning for urban planners and policy makers to take action in a more consistent way. Analysis: This paper estimates and analyzes the passenger transport energy per person per year with a large and diverse sample set based on comparable, directly observable open-source data of 57 cities, distributed over 33 countries. The freight transport energy consumption, which accounts for a large portion of urban transport energy, is not considered. The main focus of the analysis is to establish a quantitative relation between population density, transport infrastructure and transport energy consumption. Results: In a first step, significant linear relations have been found between road length per inhabitant, the road infrastructure accessibility (RIA) and private car mode share as well as between RIA and public transport mode share. Results show further relation between travel distance, population density and RIA. In a second step, a simplified model has been developed that explains the non-linear relation between the population density and RIA. Finally, based on this relation and the above findings, a hyperbolic function between population density and transport energy has been calibrated, which explains the rapid increase of transport energy consumption of cities with low population density. Conclusions: The result of the this study has clearly identified the high private car mode share as main cause for the high transport energy usage of such cities, while the longer average commute distance in low-population density cities has a more modest influence on their transport energy consumption.

Measuring the Added Effectiveness of Using Detailed Spatial and Temporal Data in Generating Accessibility Measures

It is hypothesized that spatially disaggregated and temporally variable data will lead to more accurate determinations of accessibility. This paper examines whether such measures are more effective in predicting public transport mode share and commute duration in Montreal, Canada through regression models. While results show that the model fit to predict mode share is better when accessibility is generated using detailed spatial and temporal data, the improvement is minimal. In predicting commute duration, no improvements are observed. Furthermore, the change in resulting values of accessibility between measures is observable and varies depending on the configuration and frequency of transport supply.

Measuring the potential emission reductions from a shift towards public transport

The research presented in this paper investigates the behavioural response and subsequent appraisal of a range of policy incentives devised to encourage greater use of sustainable travel options within the Greater Dublin Area (GDA). Interventions were assessed by employing four-stage modelling techniques, as a tool to identify signs of mode shifting behaviour from single occupancy vehicle (SOV) use to public transport modes. Extensive modelling work was conducted in collaboration with the National Transport Authority (NTA) of Ireland utilising the National Regional Modelling System (RMS) to represent the sustainable policy changes. Parameter modifications in the mode and destination choice and trip assignment stages were made to account for improvements made to frequency, time and cost attributes of public transport modes included in the model. Subsequent changes in vehicle kilometres travelled of various modes modelled were then utilised to estimate the potential emissions savings. In addition to this, the potential monetary savings generated from a reduction in emissions were calculated. The key results produced from this study found that an increase in the mode share of public transport of up to 2.87% could be achieved in the GDA. Up to 1.76% of which was estimated to come directly from private car trips, as a result of implementing the policy incentives tested. Furthermore, daily emissions savings of up to 431.58 tonnes of CO2, 0.95 tonnes of NOx, and 0.046 tonnes of PM2.5 were also estimated.

Will Bus Subsidy in Indonesia Sustainable?

The subsidies for public transport entails a controversial discussion on the pros and cons. On one hand mode share of public transport will decrease with increasing income levels towards private motor vehicle use. Intention of this paper is to prove that subsidy plays important role in the public transport operation and business. However such subsidy is not recover he needs to carry out the sustainable urban transport in the future. Government and private partner should create a systematic subsidy targeted for the right modes, that having sustainable achievement. This paper is structured to answer to what extent the effectiveness of government subsidies for the development of public transport services.

A case study of a last-mile solution in a high-density residential neighborhood

Studies on new transportation services such as autonomous taxis and autonomous shuttles are underway in various cities around the world. Most of these studies discuss the effects (e.g., vehicle miles traveled, travel time, delay rate, and so on) of introducing new modes of transportation. This study analyzes the impact of providing autonomous minibus service in a dense residential area. Regular buses usually run along main roads with more than one lane, but minibuses can operate along roads with a single lane. There are many one-way roads around high-density apartments such as in Korean cities, so providing a last-mile solution can have a positive effect and increase the demand for public transportation. In addition, this study compared the level-of- service between different modes of transportation (e.g., car, walking, and minibus), unlike previous studies in which minibus demand was fixed. The results showed that minibuses did not replace the trunk traffic. These results suggested that minibus service should be used as an auxiliary for trunk traffic. According to the scenarios provided by the minibus, it was analyzed that the minibus service increased the public transport mode share by 3-5%.

Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model

To improve the mode share of public transport and reduce the transition to private transport of passengers waiting at bus station, the mechanism of passengers’ decision-making procedure and influence factors of the travel mode choice were analyzed. Some latent variables such as safety, comfort, convenience, flexibility and economy were selected to reflect the satisfaction degree of passengers on the service level of public transport. Taking Jinan City as an example, the questionnaire of passengers’ travel choice behavior at bus station was designed and carried out. Based on the structure equation model (SEM), the relationship between the satisfaction degree and some latent variables such as safety and comfort was discussed. The SEM method analysis shows that, of the influence level of the latent variables to the service level of public transport, flexibility is the most significant variable affecting passenger’s satisfaction degree followed by safety, convenience, comfort and economy. Travel mode choice model of passengers waiting at bus station was established with an integration approach of SEM and nested logit (NL) model. The SEM-NL integration model results reveal that gender, monthly income, purpose of the trip, travel distance, safety and convenience service level have a significant effect on the choice of the upper model (public transport or private transport). Passenger’s age, vehicle ownership and bus ride frequency have great influence on the choice of the lower mode (ORB: original route bus; ARB: alternative route bus; Taxi; and Shared bike). Sensitivity analysis reveals that the transition probabilities from private transport to public transport can reach the highest point (respectively, 69.85%, 68.84% and 35.51%) when safety service reaches level 4, convenience service reaches level 3, or comfort service reaches level 2, indicating that the safety level equal to 4, convenience level equal to 3 and comfort level equal to 2 are the key threshold to increase the public transport mode share. Some proposals such as ensuring good accessibility of public transport, shortening the transfer distance of different routes, creating a comfortable travel environment and integrating bus ticket system have been put forward for the sustainable development of public transport system.

Optimizing location and capacity of rail-based Park-and-Ride sites to increase public transport usage

ABSTRACTThis paper presents a new methodology to identify optimal locations and capacity for rail-based Park-and-Ride (P&R) sites to increase public transport mode share. P&R is usually taken as an important component of policies for the sustainable development of urban transport systems. However, previous studies reveal that arbitrarily determined P&R sites may act to reduce public transport commuting. This paper proposes a methodology for the optimal location and capacity design of P&R sites, with the aim of enhancing public transport usage. A Combined Mode Split and Traffic Assignment (CMSTA) model is proposed for the P&R scheme. Taking the CMSTA model as the lower level, a bi-level mathematical programming model is then built to establish the optimal location and capacity of P&R sites. A heuristic genetic algorithm is adopted to solve this model. Finally, a network example is adopted to test numerically the proposed models and algorithms.

The influence of integrated space–transport development strategies on air pollution in urban areas

The phenomenon of urban sprawl has strong impacts on transport performance and accessibility and causes an increase of air pollution. Effective control of urban sprawl requires an integrated approach comprising urban transport and land-use planning. Current research is insufficient to demonstrate the effects of urban sprawl on travel behavior and air pollution emission. The present paper examines the potential of an integrated approach on space–transport development strategies with the aim of increasing accessibility and reducing air pollution. A combination of space and transport strategies has been simulated for the rapidly expanding city of Surabaya. A comparative analysis of the impact of those cases indicates the promising potential alternatives to minimize the phenomenon. The transport options considered are combinations of Public Transport (PT), comprising Mass Rapid Transit (MRT), Light Rapid Transit (LRT), and Bus Rapid Transit (BRT). The options for urban structure include a compact zone development for the city, as formulated by the city planning agency, and a polycentric city set-up based on a job-housing balance aimed at minimizing the house-job distance. The results indicate that the polycentric city structure has the potential to make public transport work successfully for the city of Surabaya. This city structure creates a trip demand pattern which matches citizens’ PT preferences. Compared to the current situation, the combination of such a city structure with an expansion of PT systems would lead to a considerable improvement of transport performance, i.e. a PT mode share, a mean commute distance, and a significant reduction in emissions.

Exploring the Mode Change Behavior of Park-and-Ride Users

This paper investigates the mode change behavior of park-and-ride (P&R) users, which is of considerable significance to analyze the effectiveness of P&R site on the commuters’ travel mode change as well as the increase of public transport mode share. Data from an intercept interview survey conducted at different P&R facilities in Metropolitan Melbourne is used. A questionnaire containing revealed preference (RP) and stated preference (SP) questions is used to interview the individuals who park at the facility and catch public transport to go to city. This study firstly aims to know the factors affecting current travel behavior using RP data and secondly to investigate the importance of the factors on influencing the commuters’ decision of travel mode choice using the SP data. The empirical models using multinomial logistic regression reveal that travel time taken by transit vehicle and transfer time at P&R stations are the primary factors affecting individuals’ decision on choosing public transport whereas parking fare is the additional factor affecting commuters’ choice of driving. Based on the results of this study, the effectiveness of P&R scheme on commuters’ travel mode change is evaluated which would be helpful to shed lights on the future construction of P&R sites.

Measuring Public Transport Satisfaction from User Surveys

Customer satisfaction has been considered one of the most important factors in any industry or service due to itsdirect relation to customer retention. Recent estimates indicate that the mode share of public transport in Ammanis only 17%; of these users 65% do not own a car, hence they are considered captive riders. This paper focuseson the user satisfaction with the public transportation system in the city. A user survey was developed to explorethe satisfaction of bus users, minibus users and jitney users. Bus users were found to be the most satisfied.However, the overall average of satisfaction reflects that generally all users are not sufficiently satisfied with thetransit system. Transport planners and decision makers could utilize the results and findings of this study, tofocus on the attributes that are important for public transport users. The outcomes also direct the attention oftransit authorities and operators towards the attributes that scored low in satisfaction, consequently requiringimprovement. It is necessary to increase user satisfaction through improving the public transport system inAmman, in order to maintain existing users and attract new passengers. These improvements will make the citymore sustainable and reduce the use of private cars in the future. Future research could replicate the adoptedmethodology with public transport users in similar countries for comparison purposes.