Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey

This study examines transit mode choice preferences of New Jersey commuters traveling to New York City (NYC) with the objective of assisting trans-Hudson ferry service planning on the basis of variables significantly affecting mode choice. A stated preference survey was conducted to collect data from a total of 2134 respondents who commute from northern New Jersey to NYC. A mixed multinomial logit model (MMLM) with random coefficients was used to analyze the data. The study considered the choice between four transit modes—ferry, PATH train, bus, and commuter rail—all of which can be used to cross the Hudson River to travel from New Jersey to NYC. Essential model results are presented for all four modes, but detailed results are discussed for only the ferry, PATH, and bus modes. Model results indicate that commuters' choices are affected not only by travel time and cost for the segment of the journey that crosses the Hudson River, but also reliability and comfort during that segment, number of access modes required by the journey, and travel time and cost of trips from home to stations/terminals before crossing the river. The results also show that commuters' attachment to the modes they currently use serves as a barrier to switching to other modes. The most important takeaway from this research for transit service planning is that there is a need to consider the attributes of both individual trip segments as well as entire journeys between commuters' home and work when exploring changes to transit service characteristics.     

The impact of the London congestion charging scheme on the generalised cost of car commuters to the city of London from a value of travel time savings perspective

This paper shows that the impacts of the London Congestion Charging Scheme should not be analysed from the standard approach to value of travel time savings. This will invariably lead to the mistaken conclusion that drivers who value their travel time savings below the £5 congestion charge will be regarded as losers from the Scheme. The use of a simple expression of generalised costs leads to different conclusions. First, a motorist who continues to drive but values the time savings of the Scheme less than £5 can still gain from the scheme, if the generalised cost post-charging is lower than the generalised cost pre-charging. Second, a motorist who switches to the bus can still gain from the scheme. Since the bus travel time post-charging will typically be lower than the bus travel time pre-charging, it is possible that the generalised cost of a trip by car pre-charging will be higher than the generalised cost of a trip by bus post-charging, even after taking into consideration the inconvenience of switching.     

Optimal distance tolls under congestion pricing and continuously distributed value of time

This paper addresses the optimal distance-based toll design problem for cordon-based congestion pricing schemes. The optimal distance tolls are determined by a positive and non-decreasing toll-charge function with respect to the travel distance. Each feasible toll-charge function is evaluated by a probit-based SUE (Stochastic User Equilibrium) problem with elastic demand, asymmetric link travel time functions, and continuously distributed VOT, solved by a convergent Cost Averaging (CA) method. The toll design problem is formulated as a mixed-integer mathematical programming with equilibrium constraints (MPEC) model, which is solved by a Hybrid GA (Genetic Algorithm)–CA method. Finally, the proposed models and algorithms are assessed by two numerical examples.     

Active commuting in a university setting: Assessing commuting habits and potential for modal change

This paper describes the results of an online survey that examined commuting patterns, potential for change and barriers and motivators affecting transport decisions in a University population (n=1040 students, n=1170 staff). Overall, 21.5% of staff and 46.8% of students at The University of Western Australia regularly used active modes, and potentially an additional 30% of staff and students would switch to active modes. The results suggested that reducing barriers to using active modes, in particular reducing actual and perceived travel time by bus and bicycle would have the greatest impact on commuting patterns. Some policy applications appeared to hold particular promise, including an implementation of a subsidised public transport pass (U-Pass), increased student housing on or near campus, increased cost of parking, and improved bus services and cycle networks.     

Autos,transit and bicycles: Comparing the costs in large Chinese cities

This study compares the full costs of seven passenger modes in the large Chinese cities facing the difficult yet crucial choice among alternative passenger transportation systems. The seven modes are evaluated at varied traffic volumes in hypothetical radial and circumferential commuting corridors. Using detailed estimates of private and social costs, the full cost of each mode is minimized by optimizing infrastructure investment and operation plans. On all corridors and across different scenarios, commuting by one or more forms of bus transit or bicycle costs less than automobile or rail. Nonetheless, in circumferential corridors, rail can be almost as cost-effective as bus under certain conditions, and bicycle can be less cost-effective than bus in some cases. Unlike results from similar studies conducted in the US, automobile commuting does not cost less than bus transportation at low traffic volumes.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

Multi-city exploration of built environment and transit mode use: Comparison of Melbourne,Amsterdam and Boston

The built environment is an important determinant of travel demand and mode choice. Establishing the relationship between the built environment and transit use using direct models can help planners predict the impact of neighborhood-level changes, that are otherwise overlooked. However, limited research has compared the impacts of the built environment for different networks and for individual transit modes.This paper addresses this gap by developing built environment and transit use models for three multimodal networks, Amsterdam, Boston and Melbourne, using a consistent methodology. A sample of train, tram and bus sites with similar station-area built environments are selected and tested to establish if impacts differ by mode. It is the first study that develops neighborhood-level indicators for multiple locations using a consistent approach.This study compares results for ordinary least squares regression and two-stage least squares (2SLS) regression to examine the impact of transit supply endogeneity on results. Instrumented values are derived for bus and tram frequency in Melbourne and bus frequency in Boston. For other mode and city combinations, the 2SLS approach is less effective at removing endogeneity.Results confirm that different associations exist between the built environment and transit modes, after accounting for mode location bias, and that this is true in multiple networks. Local access and pedestrian connectivity are more important for bus use than other modes. Tram is related to commercial density. This finding is consistent for all samples. Land use mix and bicycle connectivity also tend to be associated with higher tram use. Train use is highest where opportunities exist to transfer with bus. Population density is commonly linked to ridership, but its significance varies by mode and network.More research is needed to understand the behavioral factors driving modal differences to help planners target interventions that result in optimal integration of land use with transit modes.     

Effects of parking and cordon charge policies on tourist's modal shift in central business district of Mashhad city,Iran

The second largest holy city of the world, Mashhad, attracts high volumes of tourists and pilgrims every year. Most visitors travel by private car and are a source of considerable funds for the local economy. Among road users, tourists as one of the major traveller categories in Mashhad city behave differently due to the particular trip purpose. The aim of this research is to model tourist's shifting modes of travel behaviour when policy measures, such as the parking and cordon fares, are implemented. The tourists’ preferences were examined using binary logit analysis when different options of travel cost and time scenarios were provided. Results indicate that travel time, parking cost, cordon cost, education level and vehicle price influence tourist's modal choice. In addition, the finding shows that congestion pricing will be more effective than a parking pricing strategy in encouraging switching of modes.     

Restating modal investment priority with an improved model for public transport analysis

We compare analytically and numerically the optimised performance of different urban public transport modes for three objectives: total cost minimisation, profit maximisation, and welfare maximisation. We find that under optimal operation, buses provide lower waiting time and operator costs, therefore the only possible advantage for rail is providing a lower in-vehicle time cost if trains are faster. Using Australian data, we found that bus rapid transit provides a lower total cost, higher profit and welfare, up to their capacity. Introducing passengers dislike of crowding and train-specific attraction elements might make Heavy Rail the most cost effective mode for high levels of demand.     

Analysing the spatial-temporal characteristics of bus travel demand using the heat map

As the basic travel service for urban transit, bus services carry the majority of urban passengers. The characterisation of urban residents' transit trips can provide a first-hand reference for the evaluation, management and planning of public transport. Over the past two decades, data from smart cards have become a new source of travel survey data, providing more comprehensive spatial-temporal information about urban public transport trips. In this paper, a multi-step methodology for mining smart card data is developed to analyse the spatial-temporal characteristics of bus travel demand. Using the bus network in Guangzhou, China, as a case study, a smart card dataset is first processed to quantitatively estimate the travel demand at the bus stop level. The term ‘bus service coverage’ is introduced to map the bus travel demand from bus stops to regions. This dataset is used to create heat maps that visualise the regional distribution of bus travel demand. To identify the distribution patterns of bus travel demand, two-dimensional principal component analysis and principal component analysis are applied to extract the features of the heat maps, and the Gaussian mixture model is used for the feature clustering. The proposed methodology visually reveals the spatial-temporal patterns of bus travel demand and provides a practical set of visual analytics for transit trip characterisation.     

Travel behavior of university students who live on campus: A case study of a rural university in Asia

With their irregular class schedules and considerable freedom in the campus environment, university students are an example of a social group that tends to have complex and unique travel behavior. This study examined travel patterns of 130 students who study and live on campus in a rural university of Thailand. All survey participants completed a travel diary for seven consecutive days in a typical school week. Other than overall travel patterns, such as trip generation, mode split, distance traveled, and travel time, this study also investigated the differences in traffic patterns of four student groups, categorized by their gender and whether they own a private vehicle or not. It was found that students of both genders appeared to have similar travel patterns in all aspects. Whether they own a private vehicle does not appear to impact daily trip generation nor the total distance traveled of the students, but it does have an effect on the travel modes used by students. Those students who own a private vehicle mostly rely on driving the vehicle, while those who do not own a vehicle rely on three modes of travel: primarily being a passenger on or in a friend’s private vehicle, and to a lesser extent, driving a friend’s vehicle, and taking a bus (the only form of public transport on the campus). The results indicate a high social interdependency among university students, which makes the development of a model to simulate travel behavior of university students a complicated task.     

Estimating welfare changes from efficient pricing in public bus transit in India

Three different and feasible pricing strategies for public bus transport in India are developed in a partial equilibrium framework with the objective of improving economic efficiency and ensuring revenue adequacy, namely average cost pricing, marginal cost pricing, and two-part tariffs. These are assessed not only in terms of gains in economic efficiency, but also in changes in travel demand and consumer surplus. The estimated partial equilibrium price is higher in all three pricing regimes when compared to the current price. As a result, consumer surplus falls in all three cases. The price increase is much larger with average cost pricing compared to marginal cost pricing or two-part tariffs, and hence a larger fall in demand and consumer surplus occurs due to average cost pricing. While there is a gain in economic efficiency from marginal cost pricing and two-part tariffs, this improvement comes at the expense of reduced public bus transit demand and consumer surplus, given the price inelastic public bus transit demand estimated for India. Given the mobility needs and the developmental concerns of a growing economy such as India, the challenge for policy makers is to balance the gains in economic efficiency in the public bus transit sector against other social, political, and developmental goals.     

Design of limited-stop bus service with capacity constraint and stochastic travel time

This paper develops a mathematical model for the optimal stopping design of limited-stop bus service, which allows each bus vehicle to skip some stops. To better reflect the reality, this paper considers the vehicle capacity and stochastic travel time. Also, vehicles are all allowed to skip stops whereas any stop is not allowed to be skipped by two consecutive vehicles. A hybrid artificial bee colony (ABC) and Monte Carlo method is developed to solve the optimal stopping strategy. Finally, the model and solution method are validated by a numerical example, and a sensitivity analysis is performed on the passenger demand.     

Travelling ‘green’: is tourists' happiness at stake?

Several western governments have implemented environmental policies which increase the cost of air travel. Such policies aim to reduce the impact of air travel on climate change, but at the same time they restrict tourists in their travels. This study examines the extent to which the average tourist's happiness is affected by ‘involuntary green travel’, defined as reduced CO₂ emission travel imposed by government regulations. This issue was addressed in a study among 588 Dutch citizens who completed a self-report questionnaire containing questions about their happiness. The strongest determinant of tourists' happiness is freedom in choosing a destination. Any policy measure that interferes with tourists' freedom in destination choice will negatively affect tourists' happiness. Six percent of their happiness is at stake and potentially 17% of all holiday trips are affected. The number of tourists involved is possibly much smaller. The best options for governments are to impose taxes on long-haul destinations, which affect only a small share of all tourists, and air routes which can also be travelled by a variety of alternative modes of transport and thus less limiting to destination choice within this market segment.     

Anticipating long-distance travel shifts due to self-driving vehicles

Increasing population and travel demand has prompted new efforts to model travel demand across the United States. One such model is rJourney that estimates travel demand among thousands of regions and models mode and destination choice. rJourney includes records representing 1.17 billion long-distance trips throughout the year 2010. Although inter-regional impacts caused by an increase of automated vehicles (AVs) has been investigated, there is little research on inter-regional travel and how longer distance destination and mode choices will change. Because of conveniences offered by AVs, the value of travel time of drivers is expected to fall, thus reducing the generalized cost of AV travel. To initially analyze the impacts of AVs in the United States, a new AV mode was added to a subset of the rJourney mode and destination choice models. With an initial scenario assuming an operating cost of AVs that is 118% of traditional cars, two outcomes are observed that are solely based on model results. First, the attractiveness of AVs severely digs into the airline travel market, reducing airline revenues to 53%. Second, the introduction of AVs results in a shift of destination choice, increasing travel in further distances for personal vehicles, but favoring closer distances across all modes, for an overall 6.7% decline in US passenger-miles traveled on existing long-distance trips. While this preliminary research has revealed an initial perspective on how an existing model can support AVs, the increasing availability of data as AVs emerge will refine nationwide long-distance modeling.     

The impact of user heterogeneity on road franchising

A model is presented for analyzing Pareto-efficient build-operate-transfer toll road contracts. The formulation simultaneously allows maximizing social welfare and private profit when road users vary in their value-of-time (VOT). The failure rate and mean residual functions of the VOT distribution are used to characterize Pareto-efficient solutions. Service quality, measured in terms of the volume-to-capacity ratio, is shown to be better than, identical to, or lower than the socially optimal level depending on the curvature of the mean residual VOT function. The outcomes of various regulatory regimes are examined as well.     

Use characteristics and mode choice behavior of electric bike users in China

In 2005, 10 million electric bikes were produced in China. Strong domestic sales are projected for coming years, raising concerns about the sustainability and potential regulation of this fairly new mode. Policy makers are wrestling with developing policy on electric bikes with little information about who uses them, why they are used, and what factors influence electric bike travel. This paper probes these questions by surveying electric bike usage in two large Chinese cities, Kunming and Shanghai. Demographic comparisons are made between the different modes and cities as well as differences in travel patterns. Electric bike users are found to travel considerably more than bicycle users. Also, most electric bike users would travel by bus if electric bikes were unavailable. This suggests that electric bikes are less of a transitional mode between human-powered bikes and full-blown automobile ownership, and more an affordable, higher quality mobility option to public transport.     

Home-end and activity-end preferences for access to and egress from train stations in the Copenhagen region

Increasing public transport use with the aim of improving the sustainability of cities should focus not only on enhancing level and quality of the service offered, but also on understanding determinants of the choice of access and egress modes to and from the railway network. This study analyzes the difference in preferences at the home-end and activity-end for travelers who have chosen train as their main travel mode while investigating the effect of policy variables such as car parking availability, bicycle parking availability and type, and bicycle on train possibility. Specifically, this study analyzes the choices between five transport modes (i.e., “walk,” “bicycle,” “car driver,” “car passenger,” “bus”) for 2921 home-end and 3658 activity-end trips. Joint mixed logit models are specified and estimated to account for heteroscedasticity and correlation across alternative modes as well as taste heterogeneity across travelers. Model estimates and pseudo-elasticities uncover the importance of travel time and underline how the improvement of walkability, bikeability, and bus service would contribute significantly to the increase in the probability of choosing sustainable modes to and from train stations. Moreover, model results emphasize the role of bicycle parking in terms of the sheer number of spaces to be increased as well as covered places to be offered at the activity end, de facto giving the possibility to leave a bicycle at that end during the night. Lastly, model results show that it is a matter of not only time and trip characteristics, but also traveler characteristics, occupation, and purpose.     

The factors in residents' mobility in rural towns of China: Car ownership,road infrastructure and public transport services

The improvement of rural people's mobility in developing countries has informed many policies. Still, debates remain on which policies are efficient, for instance, building more roads, providing public transport or promoting car ownership. The empirical evidence for these debates at the national level remains scarce. As a result, this paper aims to provide fresh evidence for discussions by examining residents' mobility in China using nationwide survey data with 12,524 respondents from 119 rural towns. The results of the analysis show car ownership is the most significant factor influencing rural people's mobility than other factors. Higher car ownership relates to a higher travel frequency to counties or cities. Other kinds of transport vehicles (i.e. electric cars, motorcycles and electric bikes) also have positive but relatively weaker impacts on rural mobility. For public transport, it is more accessible to access bus stops, which encourages travel to higher-order centres rather than increasing the frequency of county bus services. The accessibility of high-quality road systems tends to have a negative influence and has combined effects with levels of local services. People from towns with insufficient local services and poor access to highways travel the most frequently to higher-order centres. This study highlights the critical role of road investments and car ownership enhancement policies in improving mobility. Moreover, this study also underscores the supplemental role of public transport services given the current low car ownership rates in rural towns of China and the global consensus on sustainable green transport development. It highlights the importance of engaging eco-friendly and locally adaptive transport alternatives, such as electric cars and electric bikes. It also calls for a rational distribution of bus stops and more flexible, convenient, and physically accessible public transport and carshare modes in rural China.     

Residential self-selection and travel behaviour: What are the effects of attitudes,reasons for location choice and the built environment?

In studies of the effect of built environment on travel behaviour, residential self-selection is an increasingly important issue. Self-selection implies that households locate in places that provide them with conducive conditions for their preferred way of travelling. In these studies, it is assumed that attitudes toward different travel modes are an important factor in location choice, and that households are unconstrained in choosing their preferred residential location. This paper challenges these assumptions, by distinguishing between the more passive travel attitude and travel considerations as a deliberate reason to locate in a certain place. Based on a survey among 355 recently relocated households in Dutch TOD locations, we find that the association between travel attitude and residential environment is weak, and that the association between travel attitude and travel as a factor in location choice is moderate at best. Multivariate models show that both travel attitude and travel being a reason for location choice influence travel mode use, suggesting that travel attitude is insufficient to fully reflect self-selection processes. In comparison to other travel modes, train travel is most influenced by the fact whether residents deliberately chose to live in an environment conducive to using this mode.