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Does mass rapid transit reduce motorcycle travel? Evidence from Taipei, Taiwan
Abstract
Motorcycles bring environmental harm. Many cities with high motorcycle ownership rates have been establishing or expanding mass transit. Whether these investments can lure existing motorcycle users is of policy concern. This research is the first to examine mass rapid transit effects on motorcycle travel, using datasets from the most recent 2000 and 2009 large-scale household travel surveys in Taipei, one of the world’s earliest motorcycle-stressed cities to have adopted a metro system. The difference-in-differences method was employed to examine the treatment effects of metro stations on mode choice in trips and household motorcycle vehicle kilometers traveled within their proximity, controlling for built environment and socioeconomic predictors of motorcycle travel. Findings suggest that both newly introduced metro stations and older pre-existing ones were effective in reducing the motorcycle mode choice probability relative to that of the metro for trips originating nearby as well as household motorcycle vehicle kilometers traveled around them.
This paper investigates the impacts of objective and subjective built environment measures on household car and two-wheeler ownership levels in Hubli and Dharwad cities in India. The empirical analysis bases on primary household vehicle ownership data and secondary land use information. The study accommodates self-selection due to travel attitudes. An important finding of the study is that households’ perceptions about neighborhood attractiveness and cleanliness are significant predictors of car and two-wheeler ownership decisions in both cities. The correlation of this latent variable is strong in Dharwad than in Hubli, probably due to the less urbanized context of Dharwad when compared to Hubli. The land-use diversity indicator improved its statistical significance in motorcycle ownership models after controlling for travel attitudes in Hubli, while in Dharwad, the coefficient's magnitude worsened. In Dharwad, road network density and distance measures revealed ‘causal’ impacts on motorcycle ownership levels, even after controlling for travel attitudes. Distance to hospitals and bus stops are highly important for a Dharwad resident's motorcycle ownership decisions. The models show that self-selection is not at work in car ownership decisions in Hubli, and built environment variables have independent effects. Among the built environment variables, land use diversity and population density can decrease car ownership levels in Hubli city. Besides, with an improvement in the women travel friendliness of neighborhoods in Hubli, households are less likely to increase car ownership levels. In Dharwad, none of the objective built environment attributes remained significant after controlling for travel attitudes, suggesting self-selection effects. The statistical relevance ‘children-friendliness’ factor was unaltered due to the addition of attitudinal variables.
The random utility maximization (RUM) is a widely used principle to study customer behaviors derived from econometric theory. The mode choice problem in transportation planning has been intensively studied to explore the choice behavior of travelers. In the demand analysis, market shares among transport modes are substantially used for public transport planning and operation. Therefore, this study is a preliminary analysis of the modeling complex mode choice behaviors among motorcycle and bus system so-called Trans Koetaradja by considering specific attributes of mode, households, and individual sociodemographic attributes. The developed model of mode choice is used to explore the effect of specific attributes of mode, households, and individual sociodemographic attributes on traveler’s mode choice behaviors and its contributing factors. Using the Revealed Preference (RP) data collected in Banda Aceh, we formulate Binary Logit (BL) to identify and evaluate the effects specific attributes of mode, households, and individual sociodemographic on mode choice. These results confirm that there is a substantial contribution of the specific mode attributes of the individual in determining selected mode choice. The specific attribute of motorcycle mode preference such as travel time (TT) and distance of destination (DD). Findings further confirm that individual sociodemographic variable including dummy young Age (DYA), dummy has elementary education background (DEB), dummy has low-medium income (DIN), dummy owned motorcycle (DOM) and dummy has driver license (DDL) have a statistically significant alert to the selecting mode choice of motorcycle.
Gasoline-powered motorcycles contribute disproportionately to traffic noise and emissions, so motorcycle electrification merits investigation. Recent advances in battery efficiency allow electric motorcycles (EMCs) to join electric cars and bicycles as a viable consumer option. This study quantifies noise and emissions using both simulations and experimental data, examines the factors that make EMCs big offenders and uses popular EMC specifications to estimate the costs and benefits of electrification in the USA. Motorcycles produce more CO, CH4, NOx, HC and particulate matter than passenger vehicles per vehicle-mile travelled. Due to limited regulation of motorcycles and weak enforcement, the perceived noise of motorcycles exceeds that of most other vehicles, being roughly double that of automobiles at speeds of over 30 mph and surpassing even that of medium trucks and buses at speeds of over 50 mph, at which point motorcycles exceed the 80 dBA US standard limit. Electrification can resolve such issues, although range limitations and high prices are presently a barrier to widespread adoption. In order to realize these environmental benefits, it is important that electrification occur with a corresponding shift away from coal as an energy source. Stricter emission regulations and stronger enforcement of existing prohibitions on certain forms of customization could also reduce the outlier status of gasoline-powered motorcycles.
The book is about “reordering priorities” for people and place-oriented city planning in the age of technological transformation and the forth industrial revolution. The authors present examples from around the world and emphasise craft placemaking, urban design, the inclusion
of pedestrian and cyclist and community development by putting transport and mobility in the core. Hence, the aim of this book is to provide a framework for accessible cities through more interaction between people and places which includes rejuvenated former
industrial estates, mixed-use in business parks and walkable neighbourhoods.
Dependency on private vehicles has become a prevalent phenomenon in big cities experiencing urban sprawl. Related to that, there are still many unknown factors affecting the dependence on motorcycles. Various factors are suspected to influence this, ranging from spatial factors to aspatial factors. This research was conducted in Yogyakarta Urbanized Area (YUA) by taking 175 samples. Binomial Logistic Regression is used in order to find the factors that affect motorcycle dependency. The results showed that the index of dependency in YUA can be quite high. Motorcycle usage, bicycle ownership, and perception about the increase of fuel price are the factors that have a significant influence on motorcycle dependence in YUA. Even though the correlation between spatial factors and motorcycle dependency was weak, it cannot be said to have no effect. These factors are most likely to be influential if other indicators are included with more suitable proxies.
The purpose of this paper is to verify the justification provided for a centralized national road policyin Indonesia, namely, that trips on national roads are typically inter-urban, by measuring the spatialdimensions of automobile and motorcycle trips on national roads in Indonesia. The study finds thatmotorcycle trips are characteristically local; by contrast, automobile trips extend beyond city boundaries,although to a limited extent. The results suggest the decentralization of transportation policies for thedevelopment and maintenance of national roads by granting autonomy to local governments when nofiscal externality exists. The results also indicate that road capacity, gasoline prices, income, populationand worker density, city size, and the number of public buses are strong predictors of vehicle kilometerstraveled.
This paper presents the results of household auto/motorcycle ownership and joint mode and destination choice models that were developed based on two large-scale travel surveys conducted eight years apart. It compares the models and discusses implications of the changes that have occurred in the Jakarta Metropolitan Area in the last decade. Given that the context of the society does not change, both models should remain unchanged with fixed parameters over a period of time. However, the models that were estimated based on the surveys conducted in 2002 and 2010 indicated quite different parameters with different degrees of significance. Such implications may also be important and hence worth studying for other urban areas of the developing world, although similarities of the implications may be restricted to regions that have modal and cultural norms in common.
Many developing Asian cities consider a Bus Rapid Transit (BRT) system in their public transport planning because of its advantages, offering lower investment cost and flexible implementation over rail systems. The objective of this research is to assess the potential of BRT for attracting travelers from passenger cars and motorcycles. Three different BRT systems were designed for the main corridor passing through Khon Kaen City in Thailand. The study developed modal split models for predicting the choices of passenger car users and motorcycle users. The models were developed based on a Stated Preference (SP) survey. It was found that BRT could attract significantly private vehicle users to change mode choice. The proportion of motorcycle users shifting is higher than passenger car users. However, the majority of private vehicle users still prefer their own private vehicles. Both travel time and travel cost affects the mode choice, in which travel time has a highly significant effect on passenger car users' choice of BRT, but travel cost has a highly significant effect on motorcyclists' choice. Some socio-economic factors, including gender, age, driving license holding and residence location also influence the choice of BRT.
In an urban setting, investments in bicycle and transit modes are expected to reduce automobile vehicle miles traveled. In reality, these benefits might be lower than expected if users simply shift between nonautomobile modes. This article investigates modal shifts among automobile, bus, and bicycle use in students commuting to the University of Wisconsin-Milwaukee (UWM) in 2008 and 2012, when a few changes were made to the local transportation system. The authors found that a significant decline in automobile mode share was associated with a significant increase in bicycle mode share, suggesting that bicycling replaced certain automobile commuting trips. Analysis by distance revealed nuances in mode substitution. There were significant increases in bicycle commuting for students living between 1.6 and 15.9 km (1.0 and 9.9 miles) from campus. However, the increases in bicycling for students living between 1.6 and 3.1 km (1.0 and 1.9 miles) corresponded with decreases in bus rather than automobile commuting, suggesting bus and bicycle substitution for short commutes. There was a significant shift in long-distance commuting-greater than 16 km (10 miles)-from automobile to bus. The authors also analyzed primary and secondary travel modes and found an increase in the proportion of regular automobile commuters who bicycled as their secondary mode. Moreover, approximately two-thirds of the students whose primary mode was bicycle and nearly half of the students whose primary mode was bus used a different, secondary commute mode. These results suggest the importance of investigating secondary travel modes.
Suburbanization and car-ownership have increased rapidly in developing-world cities over the past half-century. This study examines the relationship between income, car ownership, and suburbanization across geographies and households in metropolitan Mexico City. Neither car-ownership trends by geography nor a mixed logit model of 43,000 households’ joint car-ownership and residential-location decisions suggest that car ownership and suburbanization are moving hand-in-hand. Instead, wealthier households tend to live in central locations and own and drive cars, while poorer households tend to live further from the urban center and rely more heavily on transit. If a random household’s income doubles, that household is around 44% more likely to get an additional car and 29% more likely to live in the urban center. Given the sticky nature of housing supply and the current model of peripheral housing production, aggregate responses to higher income are more difficult to predict, as they will almost certainly be offset by higher prices. Nevertheless, the findings suggest that higher income and car ownership do not tend to encourage a move to larger houses on larger suburban lots in Mexico City.
This article explores differences in the relationship between the built environment and households’ car use in Mexico City in 1994 and 2007. After controlling for income and other household attributes, population and job density, transit and highway proximity, destination diversity, intersection density, and accessibility are statistically correlated with households’ weekday car travel in Mexico City. These correlations are generally stronger than those found in studies from U.S. cities and fairly stable over time. Where correlations have changed, they have strengthened. Findings suggest that land use planning can play a modest and growing role in reducing car travel in Mexico City.
Problem, research strategy, and findings: We assess the direct and indirect effects on car use (as measured by household vehicle miles traveled [VMT]) of the Portland Westside Max light rail transit (LRT) extension. We use longitudinal data to estimate the effects of discrete changes in the built environment by comparing a treated transit corridor with a highway corridor that serves as a control. Before the LRT line, the transit and highway corridors were comparable in almost all respects, including household VMT. After the LRT line was completed, the transit corridor had higher density, generated significantly more household walk and transit trips, and experienced a slower rise in VMT per household. We estimate a transit multiplier of 3.04, meaning that transit reduces VMT by three vehicle miles in total for every vehicle mile reduced due to transit ridership. The direct effect occurs through increases in transit ridership and associated reductions in household VMT. The indirect effect is achieved primarily through increased walking around stations and secondarily through increased densities around stations. Fixed-guideway transit in tandem with comprehensive public policies that promote transit-oriented development (TOD) around transit stations on one hand, and highway corridors on the other, produce different transportation outcomes.
Numerous studies have found that suburban residents drive more and walk less than residents in traditional neighbourhoods. What is less well understood is the extent to which the observed patterns of travel behaviour can be attributed to the residential built environment (BE) itself, as opposed to attitude-induced residential self-selection. To date, most studies addressing this self-selection issue fall into nine methodological categories: direct questioning, statistical control, instrumental variables, sample selection, propensity score, joint discrete choice models, structural equations models, mutually dependent discrete choice models and longitudinal designs. This paper reviews 38 empirical studies using these approaches. Virtually all of the studies reviewed found a statistically significant influence of the BE remaining after self-selection was accounted for. However, the practical importance of that influence was seldom assessed. Although time and resource limitations are recognized, we recommend usage of longitudinal structural equations modelling with control groups, a design which is strong with respect to all causality requisites.
The issue of self-selection's role in shaping travel patterns, by impacting one's home location choice, is a critical question. Developers, planners and policymakers regularly debate to what extent the built environment and land use patterns can alleviate roadway congestion, greenhouse gas emissions and myriad other urban problems. This study illustrates the use of Heckman's (1976, 1979) latent index model to ascertain travel impacts of neighborhood type in Austin, Texas. Under this approach, self-selection is formulated as sample selection bias in receiving a treatment. Here, treatment is defined to be one's residence in a suburban or rural zone, rather than Austin's central business district and nearby urban zones. This treatment/no-treatment approach is a meaningful advance in models of self-selection effects, and requires estimation of three straightforward models. Model results suggest that the great majority (90%) of differences in vehicle-miles-traveled between central/CBD and suburban/rural locations is due to the treatment itself, rather than self-selection of such treatment (by households that wish to meet special travel needs).
The relationship between travel behavior and the local built environment remains far from entirely resolved, despite several research efforts in the area. The significance and explanatory power of a variety of urban form measures on nonwork activity travel mode choice have been investigated. The travel data used for analysis are from the 1995 Portland Metropolitan Activity Survey conducted by Portland Metro. The database on the local built environment was developed by Song in 2002 and includes a more extensive set of variables than previous studies that have examined the relationship between travel behavior and the local built environment by using the Portland data. The results of the multinomial logit mode choice model indicate that mixed uses promote walking behavior for nonwork activities.
This paper examines the relationships between the built environment---both 'neighborhood' design characteristics and relative location-and motor vehicle ownership and use in a rapidly motorising, developing city context, that of Santiago de Chile. A vehicle choice model suggests that income dominates the household vehicle ownership decision, but also detects a relationship between several built environment characteristics and a household's likelihood of car ownership. A second model, directly linked to the ownership model to correct for selection bias and endogeneity, suggests a strong relationship with locational characteristics like distance to the central business district and Metro stations. Elasticities of vehicle kilometres travelled (VKT), calculated via the combined models, suggest that income plays the overall largest single role in determining VKT. In combination, however, a range of different design and relative location characteristics also display a relatively strong association with VKT.
Objective:
To discuss and develop difference-in-difference estimators for categorical outcomes and apply them to estimate the effect of the Affordable Care Act's Medicaid expansion on insurance coverage.
Data sources:
Secondary analysis of Survey on Income and Program Participation (SIPP) data on health insurance coverage types before (Jan 2013) and after (Dec 2015) Medicaid expansion in 39 US states (19 expansion and 20 non-expansion).
Study design:
We develop difference-in-difference methods for repeated measures (panel data) of categorical outcomes. We discuss scale dependence of DID assumptions for marginal and transition effect estimates, and specify a new target estimand: the difference between outcome category transitions under treatment versus no treatment. We establish causal assumptions about transitions that are sufficient to identify this and a marginal target estimand. We contrast the marginal estimands identified by the transition approach versus an additive assumption only about marginal evolution. We apply both the marginal and transition approaches to estimate the effects of Medicaid expansion on health insurance coverage types (employer-sponsored; other private, non-group; public; and uninsured).
Data extraction:
We analyze 16,027 individual survey responses from people aged 18 to 62 years in the 2014 SIPP panel.
Principal findings:
We show that the two identifying assumptions are equivalent (on the scale of the marginals) if either the baseline marginal distributions are identical or the marginals are constant in both grousp. Applying our transitions approach to the SIPP data, we estimate a differencial increase in transitions from uninsured to public coverage and differential decreases in transitions from uninsured to private, non-group coverage and in remaining uninsured.
Conclusions:
By comparing the assumption that marginals are evolving in parallel to an assumption about transitions across outcome values, we illustrate the scale-dependence of difference-in-differences. Our application shows that studying transitions can illuminate nuances obscured by changes in the marginals.
Bangkok has a well-developed urban rail transit system that attracts high-density residential and commercial developments around its stations. This study examines whether gentrification occurs in transit-oriented development (TOD) areas and how travel behavior to work differs between new residents and original residents. From the analysis of a questionnaire survey of new condominium residents and old shophouse residents in 12 station areas along two lines of the Bangkok Transit System (BTS), we find that the areas are gentrified by the development of condominiums. Condominium residents' incomes and level of education are higher than shophouse residents. The shophouse residents have a bigger family size and have a higher proportion of business ownership than condominium residents. Although new residents use the BTS more frequently than original residents, they also prefer to drive cars more than original residents. Shophouse residents are more likely to use motorbikes and walk to work. This is expected because a higher ratio of original residents own a business and their workplace is near their residence. The distance between a station and the workplace affects the preferred mode of travel if the choice is between the BTS and cars but not if the choice is between the BTS and motorbikes. To promote the use of the BTS among car owners, setting up workplaces that employ university graduates near BTS stations would be effective. Condominium developments in station areas will increase car usage around the station area and stations are often along main roads. Preventing excessive gentrification is necessary not only from viewpoint of equity but also for preventing traffic jams in main roads.
There is a distinguishing characteristic between traffic flow in Vietnam (and in many other Asian countries) and those in developed countries: two-wheeled vehicles (so-called motorcycles) consist a high percentage in the road traffic system. Motorcycles, for their special advantages, play a dominant role in the traffic flow in Vietnam cities, leading to the context of traffic depending on motorcycle (so-called motorcycle dependent cities- MDCs). The transportation system in MDCs is facing with a lot of chaotics and problems, such as congestion, pollution and traffic accidents. Recently, there have been a lot of traffic control measurements conducted in the effort of solving the problems. Unfortunately, there is still very little that cities know about managing this mode. This article describes work undertaken to provide a better understanding of motos and what might be done to better position their role in providing urban mobility. Lessons learned and potential solutions for Vietnam could be widely informative across East Asia and other regions where developing cities are facing similar challenges.
This paper presents the results of a choice experiment to evaluate the extent to which electric motorcycles are a potential replacement for gasoline-powered motorcycles in Solo, Indonesia. Survey respondents faced five choice scenarios where they selected between a conventional motorcycle, an electric motorcycle, and no motorcycle based on price, speed, range, and charge time. Approximately 1200 individuals completed all five choice scenarios and fully responded to socioeconomic and preference questions. As in much of Southeast Asia, motorcycles dominate the transportation system and provide inexpensive, relatively safe, and convenient point-to-point travel. However, motorcycles also produce substantial, harmful local emissions. To estimate the probability of selecting different motorcycle types, the survey data are fit with a mixed logit model with random coefficients. This specification allows correlation across choices over time, flexible substitution across the choice alternatives, and variation in consumer preferences. The results of the survey and analysis indicate that there is almost certainly a market for electric motorcycles but their price and performance will have to be competitive with low-cost, gas-powered ones. Speed, range, charge time, and price all mattered substantially with respondents willing to pay a 7-13% premium for motorcycles with 10. km longer range, 10. km/h faster speed, or an hour shorter charge time. Charge time was particularly important, suggesting that improvements in battery charging technology and charging infrastructure could substantially impact consumers' willingness to adopt electric motorcycles. Younger non-smoking respondents with concerns about the environment and favorable views of e-bikes were most likely to choose electric motorcycles.
The present study explores the relationship between metro systems and gentrification. Three hypotheses are proposed as follows: access to metro stations induces gentrification, metro-induced gentrification occurs in both inner and outer city areas, and metro-induced gentrification differs between the inner and outer city areas. The present study tested these hypotheses by using population migration, college graduates, increased floor area, and house price as gentrification outcomes. Panel data and traditional linear regression analyses were conducted between 1996 and 2013 in Taipei City, Taiwan. Empirical evidence generally supports the hypotheses. Particularly, metro-induced gentrification revealed by highly educated residents and real-estate development was significantly stronger in the outer city areas, whereas metro-induced gentrification revealed by house prices was significantly stronger in the inner city areas. The current results broaden the understanding on the manner in which infrastructure investments were related to gentrification in an emerging city and imply that the local government should adopt sufficient means to deal with metro-induced gentrification when upgrading public transport systems.
There is a pressing need to estimate the magnitude and dynamics of the behavioural effects of transportation investments and policy. This article innovates by applying an experimental-control group research design to the case of new light rail transit service in Los Angeles, California. Only a handful of previous studies use an experimental design to assess impacts of light rail transit, and this is the first to use an experimental design to measure impacts on vehicle miles travelled, a key determinant of greenhouse gas emissions from the transport sector. We administered an annual seven-day travel study to a panel of households in the vicinity of Los Angeles’ Expo light rail line before the 2012 start of rail service and twice after the line opened. We find that households living within walking distance (1 km) of the new light rail drove approximately 10 fewer miles per day relative to control households farther away. Rail transit trips among near-station households approximately tripled relative to households beyond walking distance. Such driving reductions among households within walking distance of new rail transit stations suggest that Los Angeles’ large rail transit investment, coupled with land use policy, has the potential to help achieve climate change policy goals. More broadly, experimental evaluation can provide insights into causality and patterns of travel behaviour change associated with planning policies.
Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu-themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. Shows why econometrics is important; Explains econometric research through humorous and accessible discussion; Outlines empirical methods central to modern econometric practice; Works through interesting and relevant real-world examples.
In Asia, many developing countries are facing the issue whether to develop the motorcycle market as a transitional phase or to jump to the automobile market directly. In order to examine the issue, this study attempts to develop a mixed discrete/continuous demand model to analyze the characteristics of household’s decision behavior associated with the mode to work, ownership and usage of cars, and ownership and usage of motorcycles. Empirical analyses indicate that it is not easy to suppress the ownership levels of motorized vehicles by adopting price mechanism or by improving the quality of public transportation. Thus, in order to prevent a great deal of problems resulting from mixing car and motorcycle flows, we suggest that it is better for developing countries not to approve the development of motorcycles as a transitional phase.
Expanding urban populations are inducing development at the edges of Indian cities, given the constraints on land use intensification within municipal boundaries. Existing peripheral towns are becoming anchors for this new growth, creating urban agglomerations. Such areas have become preferred home locations for the working poor and emergent middle class, groups that are often priced out of the urban housing market. However, many such exurban locations lack infrastructure such as durable paved roads and transit, because investments are largely clustered within municipal boundaries. This paper focuses on the Greater Mumbai Region and relies on a cross-sectional household travel survey data set. The objective is to understand how vehicle use is linked to the built environment and socio-economics. Spatial analysis shows that cars are used in urban centres while scooters and motorcycles are used in the exurbs. Estimated censored regression models show that greater household distance from the main employment centre Nariman Point, better job accessibility and improved socio-economic factors increase vehicle use, while land use diversity and density bring down vehicle use. A key econometric result is that after controlling for location, land use, infrastructure supply and socio-economics, the expectation of a motorised two-wheeler or car in a household does not translate to its use. Overall, the findings suggest that policies encouraging higher land use diversity, density and transit supply have the potential to marginally decrease vehicle use in the Indian metropolis. However, future research needs to focus on residential location to better understand how the choices of where to live and how to travel are interconnected.
Problem: Localities and states are turning to land planning and urban design for help in reducing automobile use and related social and environmental costs. The effects of such strategies on travel demand have not been generalized in recent years from the multitude of available studies.Purpose: We conducted a meta-analysis of the built environment-travel literature existing at the end of 2009 in order to draw generalizable conclusions for practice. We aimed to quantify effect sizes, update earlier work, include additional outcome measures, and address the methodological issue of self-selection.Methods: We computed elasticities for individual studies and pooled them to produce weighted averages.Results and conclusions: Travel variables are generally inelastic with respect to change in measures of the built environment. Of the environmental variables considered here, none has a weighted average travel elasticity of absolute magnitude greater than 0.39, and most are much less. Still, the combined effect of several such variables on travel could be quite large. Consistent with prior work, we find that vehicle miles traveled (VMT) is most strongly related to measures of accessibility to destinations and secondarily to street network design variables. Walking is most strongly related to measures of land use diversity, intersection density, and the number of destinations within walking distance. Bus and train use are equally related to proximity to transit and street network design variables, with land use diversity a secondary factor. Surprisingly, we find population and job densities to be only weakly associated with travel behavior once these other variables are controlled.Takeaway for practice: The elasticities we derived in this meta-analysis may be used to adjust outputs of travel or activity models that are otherwise insensitive to variation in the built environment, or be used in sketch planning applications ranging from climate action plans to health impact assessments. However, because sample sizes are small, and very few studies control for residential preferences and attitudes, we cannot say that planners should generalize broadly from our results. While these elasticities are as accurate as currently possible, they should be understood to contain unknown error and have unknown confidence intervals. They provide a base, and as more built-environment/travel studies appear in the planning literature, these elasticities should be updated and refined.Research support: U.S. Environmental Protection Agency.
Directing growth towards compact rail corridors has become a key strategy for redirecting auto-oriented regions towards denser, mixed-use communities that support sustainable travel. Few have examined how travel of near-rail residents varies within corridors or whether corridor land use-travel interactions diverge from regional averages. The Los Angeles region has made substantial investments in transit-oriented development, and our survey analysis indicates that although rail corridor residents drove less and rode public transit more than the county average, households in an older subway corridor with more near-transit development had about 11 fewer daily miles driven and higher transit ridership than households along a newer light rail line, a difference likely associated with development patterns and the composition and preferences of residents. Rail transit corridors are not created equally, and transit providers and community planners should consider the social and development context of corridors in efforts to improve transit access and maximise development.
The evolution of motorcycle ownership is a crucial issue for road safety, as motorcyclists are highly vulnerable road users. Analyzing a panel of 153 countries for the period 1963–2010, we document a motorcycle Kuznets curve which sees motorcycle dependence increase and then decrease as economies develop. Upswings in motorcycle ownership are particularly pronounced in densely populated countries. We also present macro-level evidence on the additional road fatalities associated with motorcycles. Our results indicate that many low-income countries face the prospect of an increasing number of motorcycle-related deaths over coming years unless adequate safety initiatives are implemented.
This study established a hypothesis model based on the seemingly unrelated regression equations (SURE) model to investigate the relationship between public transportation, car, and motorcycle use in various townships in Taiwan and to analyse important factors that affect the usage of these modes. The SURE model was adopted because of the lack of a significant correlation between the dependent variables. The pairwise covariance analysis for any two of the three transportation modes revealed that the transportation modes could substitute for one another. Factors related to modal and demographic characteristics had different impacts on the usage of the three modes. The calculation of elasticity using different population densities and public transportation usage showed that when the ‘number of city bus routes’ was increased by 50% in areas with high population density and high public transportation usage, car usage decreased by 1.4%, which corresponds to 300,000 vehicles, and total CO2 emissions reduced by 0.0204%. When the ‘total length of city bus routes’ was increased by 50%, the number of motorcycles used decreased by 83 million, and total CO2 emissions reduced by 1.119%, which corresponds to 1.4 million tonnes of CO2 emission. These findings suggest that these different factors had varying impacts on car and motorcycle usage in different areas. We therefore recommended that future transportation policies consider the varying transportation usage trends in different areas.
Over the past half century, government agencies in Mexico City have invested heavily in high-capacity public transit, particularly the 225-km Metro system. Nearly all of this investment has been in central locations of the metropolis. Only recently has service coverage been extended into the periphery, which has accounted for the majority of postwar metropolitan population growth. The Metro's Line B, which opened in phases in 1999 and 2000, significantly expanded Metro coverage into the densely populated and fast-growing suburban municipality of Ecatepec. Comparing travel behavior and land use measures at six geographic scales, including the investment's immediate catchment area, across two time periods—six years before and seven years after the investment opened—this paper investigates the effects of one of the first and only suburban high-capacity transit investments in Mexico City. While the investment sparked a significant increase in local Metro use, most of this increase came from people relying on informal transit, rather than cars. This shift reduced average transit expenditures and travel times for local residents. However, it also increased government subsidies for the Metro and had no apparent effect on road speeds. In terms of land use, the investment increased density around the stations but appears to have had little to no effect on downtown commercial development, where it might have been expected to have a significant influence. In short, the effects of Line B demonstrate much of the promise and problem with expanding high capacity transit service into the suburbs. Ridership is likely to be high, but so too will be the costs and subsidies, while the effects on car ownership and urban form are likely to be modest.
Although researchers have long argued in favor of off-peak transit service, studies that have empirically estimated its benefits regarding revenue generation, trip diversions, and greenhouse gas (GHG) emission are rare. This study provides important evidence about the benefits of off-peak commuter rail service by focusing on the Pascack Valley line in New Jersey, where off-peak service was introduced in October 2007. The research involved two focus groups and an onboard survey of passengers. Benefits were estimated regarding additional revenue generation and reduction in vehicle miles traveled (VMT) and GHG emission. The research shows that the new off-peak service potentially reduced VMT by more than 12 million annually due to diversions from other modes. Although diversions from other modes resulted in a substantial reduction in GHG emissions, due to the additional diesel fuel used by the new trains, the net GHG savings were in the range of 28–49 %. The research further shows that both peak period and off-peak riders benefited from the new off-peak service. Evidence is found about an increase in new transit riders and a modest increase peak period usage because of the off-peak service.
One-half mile has become the accepted distance for gauging a transit station’s catchment area in the U.S. It is the de facto standard for planning TODs (transit oriented developments) in America. Planners and researchers use transit catchment areas not only to make predictions about transit ridership and the land use and socioeconomic impacts of transit, but also to prescribe regulations, such as the relaxation of restrictive zoning, or carve out TOD financial plans. This radius is loosely based on the distance that people are willing to walk to transit, but this same reasoning has been used to justify other transit catchment areas. Using station-level variables from 1,449 high-capacity American transit stations in 21 cities, we aim to identify whether there is clear benchmark between distance and ridership that provides a norm for station-area planning and prediction. For the purposes of predicting station-level transit ridership, we find that different catchment areas have little influence on a model’s predictive power. This suggests that transit agencies should use the easiest and most readily available data when estimating direct demand models. For prescribing land-use policy, by contrast, the evidence is less clear. Nevertheless, we find some support for using a quarter-mile catchment area for jobs around transit and a half-mile catchment for population. While these distances will likely vary from place to place and depending on the study purpose, they are a good starting point for considering transit-oriented policy or collecting labor-intensive data, such as surveys, about transit-adjacent firms or households.
Motorcycles are a widespread mode of travel in several parts of the world as, for example, in Southern Europe and Asia. However, motorcycle ownership and usage have been scarcely examined, despite being critical for developing transportation and traffic safety plans and policies in urban areas with high motorcycle presence. This pap dels are developed for this purpose based on questionnaires collected in Athens, Greece. A binary Probit model is used for analyzing motorcycle ownership and a hazard-based duration model for explaining factors affecting motorcycle usage. Results indicated that income, gender, age and er investigates factors affecting motorcycle ownership and use; appropriate mo spatial trip characteristic do have an effect on motorcycle ownership and usage.
A bus rapid transit (BRT) system began operation in Jakarta City, Indonesia, in January 2004 and led to a modal shift from
private to public modes of transport. This modal shift from car and motorcycle to BRT reduced the emission intensity of primary
pollutants, such as NOx and CO. We applied a combined structural equation model and an artificial neural network to evaluate the impact of the BRT
system on the concentration of secondary pollutants in the roadside areas in the BRT corridors. An empirical analysis was
carried out using data collected at five continuous ambient air quality monitoring stations located near to the BRT TransJakarta
corridors in 2005. The establishment of our structural equation model gives a better understanding of the cause–effect relationship
among the factors influencing roadside ambient air pollution, and was useful in simplifying the complexity of our artificial
neural network model for predicting the modal shift’s impact on the PM10 values and concentration of O3. The introduction of the BRT system, and the modal shift it produced, had a greater influence on rapidly decaying pollutants,
such as PM10, than on O3 because of the exposure to near-source microenvironments, such as the roadside of the TransJakarta corridors.
KeywordsTransJakarta bus rapid transit system–Structural equation model–Artificial neural network
This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models - ordinary, fixed, and random effects - are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled.
As environmental concerns mount alongside increasing auto dependence, research has been devoted to understanding the number of automobiles households own. The 2000 US census public use micro sample is used to demonstrate the importance of preference formation in auto ownership by studying auto ownership among recent movers. Using a multinomial probit model, the paper demonstrates that residents in the US transit cities who moved from major metropolitan areas are more likely to own fewer vehicles than counterparts who moved from smaller metropolitan areas and non-metropolitan areas. It is concluded that these results are due to learned preferences for levels of car ownership. Once the self-reinforcing 'cultural knowledge' of living without cars is lost, it could be difficult to regain. A focus on children and young adults, familiarising them with alternatives to the car may be an important approach to developing collective preferences for fewer cars.
This paper aims to explore the effects of rational and habitual factors on mode choice behaviors in a motorcycle-dependent region. Both a discrete choice model and theory of planned behavior (TPB) are employed to examine mode choice behaviors. A sample was obtained from two major cities in Taiwan to examine the contextual effect of public transport development. The empirical results reveal that psychological (rational and habitual) factors have stronger influences on mode choice behaviors than socio-economic factors, and furthermore that habitual factors explain traveler mode choice behaviors better than rational ones. The contextual effect with regard to public transport development is found to be significant for motorcyclists' mode choice behaviors. The practical implications of the results of this study are discussed.
The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing
simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan
and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area
significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan
area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while
higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between
the two areas.
This study investigated the influence of benzene concentration from motorcycle exhaust emissions on ambient air quality in Bangkok Metropolitan Region (BMR). Measurement of benzene concentration in exhaust emissions is performed on a standard test driving cycle through which each motorcycle to be tested is driven. The test result revealed that average benzene concentrations in exhaust emission for the test motorcycles ranged from 3.02 to 109.68 mg/m3. The finding also indicated that two-stroke motorcycles emitted five times more benzene than that of four-stroke motorcycles. Four air monitoring sites were strategically established to determine the relationship between average benzene concentrations with different traffic configurations in each traffic zone of BMR during peak/non-peak hours, day/night times and weekday/weekend. The shape of the curve for benzene level usually shows two peaks corresponding to the morning and evening traffic rush or commuter rush hours. The finding shows that the mean concentrations for benzene in all monitoring stations in the ambient air for peak hours (07:00–09:00 and 16:00–18:00 h) ranged from 15.1 to 42.4 μg/m3. For non-peak hour (11:30–15:00 h), benzene levels were found in the range 16.3–30.9 μg/m3. It is observed that higher levels of benzene are found among roadside stations with slow moving traffic while lower levels are found among roadside stations with fast traffic movement. Additional factors such as temperature, wind speed, rainfall, etc. are also considered in this study to determine the relationship between traffic conditions and ambient benzene levels.
We have explored vehicle dependence, taking account of subjective considerations of individual travelers. Vehicle dependence, arising from economic considerations, psychological preference, and habitual behavior, is formulated here as a subjective latent construct that acts in a person’s mode choice. The Rasch model is reviewed, and suggested as an instrument to measure such a latent construct. An empirical analysis of motorcycle dependence was performed using self-rated information about eight items from 321 motorcyclists in Taipei. The empirical results showed that motorcyclists in Taipei depend on their motorcycles to achieve unaccompanied, short-distance, multistop trips; motorcyclists under the age of 25 who were inferior in economic terms and did not use an automobile showed relatively higher measures of motorcycle dependence. This paper conceptualizes vehicle dependence in terms of both its socioeconomic and its psychological nature. The results of exploring vehicle dependence should benefit researchers in modifying their formulations of mode choice, and policy makers in enacting more effective policies.
Numerous studies have found that suburban residents drive more and walk less than residents in traditional neighborhoods. What is less well understood is the extent to which the observed patterns of travel behavior can be attributed to the residential built environment itself, as opposed to the prior self-selection of residents into a built environment that is consistent with their predispositions toward certain travel modes and land use configurations. To date, most studies addressing this attitudinal self-selection issue fall into seven categories: direct questioning, statistical control, instrumental variables models, sample selection models, joint discrete choice models, structural equations models, and longitudinal designs. This paper reviews and evaluates these alternative approaches with respect to this particular application (a companion paper focuses on the empirical findings of 28 studies using these approaches). We identify some advantages and disadvantages of each approach, and note the difficulties in actually quantifying the absolute and/or relative extent of the true influence of the built environment on travel behavior. Although time and resource limitations are recognized, we recommend usage of longitudinal structural equations modeling with control groups, a design which is strong with respect to all causality requisites.
There has been an increasing interest in the land use-transportation connection in the past decade, motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual traveler behavior and aggregate travel demand. In this line of research and application pursuit, it is critical to understand whether the empirically observed association between the built environment and travel behavior-related variables is a true reflection of underlying causality or simply a spurious correlation attributable to the intervening relationship between the built environment and the characteristics of people who choose to live in particular built environments.
The environmental and energy concerns of using motorcycles in urban areas have fostered the rapid development development of electric motorcycles (EMs) in Taiwan in recent years. EMs' zero-emission, low noise level and high energy efficiency features provide the promising potential to alleviate the severe environmental pollution problem caused by the existing gasoline motorcycles. This study summarizes the recent development of the EM. More specifically, this study aims to analyze the potential demand for EMs based on an interview survey using stated preference modeling approaches. Study results show that female motorists are the potential target market for EMs. Developmental and energy-use issues of EMs are also discussed in this study.
We specify and estimate a joint model of residential density, vehicle use, and fuel consumption that accounts for both self selection effects and missing data that are related to the endogenous variables. Our model is estimated on the California subsample of the 2001 U.S. National Household Travel Survey (NHTS). Comparing two California households that are similar in all respects except residential density, a lower density of 1000 housing units per square mile (roughly 40% of the weighted sample average) implies an increase of 1200 miles driven per year (4.8%) and 65 more gallons of fuel used per household (5.5%). This total effect of residential density on fuel usage is decomposed into two paths of influence. Increased mileage leads to a difference of 45 gallons, but there is an additional direct effect of density through lower fleet fuel economy of 20 gallons per year, a result of vehicle type choice.
Many US cities invest in large public transit projects in order to reduce private vehicle dependence and to reverse the downward trend in public transit use. Using a unique panel data set for five major cities that upgraded their rail transit systems in the 1980s, we estimate new rail transit’s impact on usage and housing values, using distance as a proxy for transit access. New rail transit has a small impact on usage and housing values. This impact is enough to represent tangible benefits of new transit to nearby residents. New transit’s benefits are not uniformly distributed. We document which demographic groups are over represented in transit growth areas and the changes in transit usage by different demographic groups.