Making do: The effects of a mass transit strike on travel behavior

A brief transit strike in early December 1976 disrupted bus services to the city of Pittsburgh and surrounding Allegheny County. That strike provided an opportunity for testing a variety of approaches to increase ride-sharing and to reduce traffic congestion, and for examining the effect of the strike on traffic congestion and on individual travel behavior. Even though over 60% of the commuters to the CBD use transit, the effects of the strike were relatively mild. There was some increase in traffic flow into the CBD and some spreading of the peak period. The largest proportion of the transit commuters who made trips to the CBD during the strike were dropped off by a non-commuter, increasing highway traffic. The most severe impact was felt by those transit commuters who had no cars in the household; 25% of these commuters (only 3% of the total CBD commuters) stayed home from work on the first day of the strike. Most attempts to mitigate the impact of the strike had little effect, largely because most commuters were able to manage adequately during the short strike. The anticipated parking problem, on which much of the contingency planning was focused, did not emerge, largely because of the use of carpooling and drop-off mode by many of the transit users.     

Attitudes,mode switching behavior,and the built environment: A longitudinal study in the Puget Sound Region

Carpooling in the US has a storied history. After experiencing a peak 20% mode share in 1980, the current share of carpooling for work trips is about 10% and the majority of these carpooling trips are made by intra-household members. Casting the choice between SOV and carpool as a social dilemma in which SOV is a noncooperative choice and carpool is a cooperative one, we propose to test two hypotheses. First, the switch from SOV to carpool and the reverse choice are attributed to different factors—structural factors, or those factors altering the objective features of a decision scenario such as travel time and travel cost, play a dominant role in the switch from carpool to SOV while psychosocial factors (attitudes and beliefs) play a critical role in the switch from SOV to carpool. Second, the two choices are underlay by different behavioral mechanisms. In particular, we expect self-justification by carpool-to-SOV switchers—after they switch from carpool to SOV, they adjusted their attitudes toward carpool accordingly to match their behavior. The analysis of the first three waves of the Puget Sound Transportation Panel supports these two hypotheses. Our study results recommend developing programs and policies that aim at influencing people’s subjective assessments of carpooling, in addition to the existing ones that mostly focus on incentivizing carpooling, and differentiating between programs seeking to encourage SOV users to switch to carpool and those aiming to maintain existing carpoolers.     

Modelling commuting mode choice with explicit consideration of carpool in the choice set formation

This article investigates the carpool mode choice option in the context of overall commuting mode choice preferences. The article uses a hybrid discrete choice modelling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting mode choice together with the response bias corrections through the accommodation of measurement equations. A cross-nested error structure for the econometric formulation is used to capture correlations among various commuting modes and carpool consideration in the choice set. Empirical models are estimated using a data set collected through a week-long commuter survey in Edmonton, Alberta. The empirical model reveals many behavioural details of commuting mode choice and carpooling. Interestingly, it reveals that interactions between various Travel Demand Management (TDM) tools with the carpooling option can be different at different level of decision making (choice set formation level and final choice making level).     

Multi-agent simulation of individual mobility behavior in carpooling

Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We developed a prototype of our agent-based carpooling application based on the work presented in this paper and carried out a validation study of our results with real data collected in Flanders, Belgium.     

Stable ride-sharing matching for the commuters with payment design

Ride-sharing enables reduction of private car usage for commuting. This paper proposes a stable matching model for the ride-sharing which aims to minimize the travel cost of all commuters. A payment for the ride-sharing is designed considering the equity and incentive. An algorithm based on the deferred acceptance algorithm is proposed for the model. To verify the model and algorithm, cases with different scales are presented based on Dalian. The results illustrate that the compensation, time window and driver-to-rider ratios can affect the successful matching rate.

     

Getting by with a little help from my friends…and family: immigrants and carpooling

While much of the scholarly literature on immigrants’ travel focuses on transit use, the newest arrivals to the United States make over twelve times as many trips by carpool as by transit. Using the 2001 National Household Travel Survey and multinomial logit mode choice models, we examine the determinants of carpooling. In particular, we focus on the likelihood of carpooling among immigrants—carpooling both within and across households. After controlling for relevant determinants of carpooling, we find that immigrants are far more likely to form household carpools than native-born adults and also are more likely than the native-born to form external carpools (outside the household). Moreover, when faced with the options of carpooling and public transit, immigrants—even recent arrivals—appear to prefer carpools over transit more strongly than the native born.     

Studying the benefits of carpooling in an urban area using automatic vehicle identification data

Carpooling has been considered a solution for alleviating traffic congestion and reducing air pollution in cities. However, the quantification of the benefits of large-scale carpooling in urban areas remains a challenge due to insufficient travel trajectory data. In this study, a trajectory reconstruction method is proposed to capture vehicle trajectories based on citywide license plate recognition (LPR) data. Then, the prospects of large-scale carpooling in an urban area under two scenarios, namely, all vehicle travel demands under real-time carpooling condition and commuter vehicle travel demands under long-term carpooling condition, are evaluated by solving an integer programming model based on an updated longest common subsequence (LCS) algorithm. A maximum weight non-bipartite matching algorithm is introduced to find the optimal solution for the proposed model. Finally, road network trip volume reduction and travel speed improvement are estimated to measure the traffic benefits attributed to carpooling. This study is applied to a dataset that contains millions of LPR data recorded in Langfang, China for 1 week. Results demonstrate that under the real-time carpooling condition, the total trip volumes for different carpooling comfort levels decrease by 32–49%, and the peak-hour travel speeds on most road segments increase by 5–40%. The long-term carpooling relationship among commuter vehicles can reduce commuter trips by an average of 30% and 24% in the morning and evening peak hours, respectively, during workdays. This study shows the application potential and promotes the development of this vehicle travel mode.     

On the morning commute problem with carpooling behavior under parking space constraint

Morning commuters choose their departure times and travel modes based on a combinational evaluation of factors associated with the chances of running into bottleneck congestion, likely schedule delays, parking space availability as well as monetary costs of traveling and parking. This study investigates a morning commute problem with carpooling behavior under parking space constraint at destination. We consider such a scenario that as a competing mode of the transit line, the highway contains a carpool lane only used by carpoolers while all solo drivers are forced to use a general purpose (GP) lane. Unlike the standard bottleneck model, the rush-hour dynamic departure patterns with a binding parking supply vary with the relative proportion of the two lanes’ capacities. The possible departure pattern domain with different parking supply and lane capacity allocation is explored in terms of the relative extra carpool cost and distinguished between the bi-mode and multi-mode equilibria. It is found that compared with solo drivers, carpoolers have shorter rush hour in order to smooth the extra carpool cost. With the decrease of parking spots, the number of solo drivers cuts down gradually, whilst the number of carpoolers climbs up firstly and then declines in the multi-mode system. Under mild assumptions, the best system performance can be realized with the joint consideration of total travel cost and vehicle emission cost through optimizing the lane capacity allocation and the parking supply.     

Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use

Fluctuating fuel prices, rising congestion, longer commutes, and related environmental and human health effects have combined to once more draw the interest of governments, commuters, and firms toward the concept of travel demand management (TDM). While TDM is not new, the proliferation of mobile telephony, fixed Internet, and associated applications has created fresh prospects for the implementation of commuter focused TDM strategies. One recent example is Carpool Zone, an on-line carpool-matching tool deployed and managed by the TDM group at Metrolinx, the regional transportation planning agency within Canada’s largest metropolitan region, the Greater Toronto and Hamilton Area. Using data provided by Metrolinx, this paper broadens current thinking on carpool formation and use. The main hypothesis guiding this work is that the carpool formation and use process is sensitive to personal and household characteristics, space, time, travel cost, and workplace TDM policies. Results from a logistic regression analysis suggest that geographical proximity to other users; workplace TDM policies; the scheduling of work; and commuter role preference increase the odds of successfully carpooling. Importantly, findings regarding the positive influence of workplace TDM policies suggest that Internet based TDM tools will likely require critically important investment in human capital at the back-end to ensure program participation.     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

Measuring the impact of efficient household travel decisions on potential travel time savings and accessibility gains

Using the conceptual framework of time–space geography, this paper incorporates both spatio-temporal constraints and household interaction effects into a meaningful measure of the potential of a household to interact with the built environment. Within this context, personal accessibility is described as a measure of the potential ability of individuals within a household not only to reach activity opportunities, but to do so with sufficient time available for participation in those activities, subject to the spatio-temporal constraints imposed by their daily obligations and transportation supply environment. The incorporation of activity-based concepts in the measurement of accessibility as a product of travel time savings not only explicitly acknowledges a temporal dimension in assessing the potential for spatial interaction but also expands the applicability of accessibility consideration to such real-world policy options as the promotion of ride-sharing and trip chaining behaviors. An empirical application of the model system provides an indication of the potential of activity-based modeling approaches to assess the bounds on achievable improvements in accessibility and travel time based on daily household activity patterns. It also provides an assessment of roles for trip chaining and ride-sharing as potentially effective methods to facilitate transportation policy objectives.     

Commuting trip satisfaction in Beijing: Exploring the influence of multimodal behavior and modal flexibility

In the past decade, many studies have explored the relationship between travelers’ travel mode and their trip satisfaction. Various characteristics of the chosen travel modes have been found to influence trip experiences; however, apart from the chosen modes, travelers’ variability in mode use and their ability to vary have not been investigated in the trip satisfaction literature. This current paper presents an analysis of commuting trip satisfaction in Beijing with a particular focus on the influence of commuters’ multimodal behavior on multiple workdays and their modal flexibility for each commuting trip. Consistent with previous studies, we find that commuting trips by active modes are the most satisfying, followed by trips by car and public transport. In Beijing, public transport dominates. Urban residents increasingly acquire automobiles, but a strict vehicle policy has been implemented to restrict the use of private cars on workdays. In this comparatively constrained context for transport mode choice, we find a significant portion of commuters showing multimodal behavior. We also find that multimodal commuters tend to feel less satisfied with trips by alternative modes compared with monomodal commuters, which is probably related to their undesirable deviation from habitual transport modes. Furthermore, the relationship between modal flexibility and trip satisfaction is not linear, but U-shaped. Commuters with high flexibility are generally most satisfied because there is a higher possibility for them to choose their mode of transport out of preference. Very inflexible commuters can also reach a relatively high satisfaction level, however, which is probably caused by their lower expectations beforehand and the fact that they did not have an alternative to regret in trip satisfaction assessments.     

A study of carpooling behaviour using a stated preference web survey in selected cities of India

This paper analyses how people perceive the idea of carpooling and evaluate preferences while making a decision to join a carpool. Analysing data from a web-based stated preference survey in India reveals that cognitive attitudes play a significant role in evaluating the perceived advantages and disadvantages of carpooling whereas intentions to carpool are associated with perceived negative evaluations. A factor analysis identifies two latent attitudinal factors: a ‘time–convenience’ factor that discourages carpooling and a ‘private–public cost’ factor that encourages carpooling. The study analyses the influential attributes – extra travel time, walking time to reach meeting point, waiting time at pickup point and cost savings – as explanatory variables for the utility of carpooling. Cost savings prove to be the most significant attribute when combined with other attributes, followed by extra travel time. The study provides the implications to policy-makers of designing promotional tools to improve the propensity of carpooling among single occupant vehicle drivers.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Using a stages of change approach to explore opportunities for increasing bicycle commuting

Given the potential benefits of bicycling to the environment, the economy, and public health, many U.S. cities have set ambitious goals for increasing the bicycle share of commute trips. The Transtheoretical Model of Behavior Change, which seeks to describe how positive and permanent change can be fostered in individuals, may shed light on how cities can most effectively increase bicycle commuting. We use the model’s “stages of change” framework to explore the potential for increased bicycle commuting to the UC Davis campus in Davis, California. Our analysis uses data from the 2012 to 2013 UC Davis Campus Travel Survey, an annual online survey that is randomly administered to students and employees at UC Davis. Based on their responses to questions about current commute mode and contemplation of bicycle commuting, respondents are divided into five stages of change: Pre-contemplation, Contemplation, Preparation, Action, and Maintenance. We construct a Bayesian multilevel ordinal logistic regression model to understand how differences in socio-demographic characteristics, travel attributes, and travel attitudes between individuals explain their membership in different stages of change. In addition, we use this model to explore the potential of various intervention strategies to move individuals through the stages of change toward becoming regular bicycle commuters. Our results indicate that travel attitudes matter more to progression toward regular commute bicycling than travel attributes, tentatively supporting the efficacy of “soft” policies focused on changing travel attitudes.     

An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model

The trip timing and mode choice are two critical decisions of individual commuters mostly define peak period traffic congestion in urban areas. Due to the increasing evidence in many North American cities that the duration of the congested peak travelling periods is expanding (peak spreading), it becomes necessary and natural to investigate these two commuting decisions jointly. In addition to being considered jointly with mode choice decisions, trip timing must also be modelled as a continuous variable in order to precisely capture peak spreading trends in a policy sensitive transportation demand model. However, in the literature to date, these two fundamental decisions have largely been treated separately or in some cases as integrated discrete decisions for joint investigation. In this paper, a discrete-continuous econometric model is used to investigate the joint decisions of trip timing and mode choice for commuting trips in the Greater Toronto Area (GTA). The joint model, with a multinomial logit model for mode choice and a continuous time hazard model for trip timing, allows for unrestricted correlation between the unobserved factors influencing these two decisions. Models are estimated by occupation groups using 2001 travel survey data for the GTA. Across all occupation groups, strong correlations between unobserved factors influencing mode choice and trip timing are found. Furthermore, the estimated model proves that it sufficiently captures the peak spreading phenomenon and is capable of being applied within the activity-based travel demand model framework.     

Transportation serviceability analysis for metropolitan commuting corridors based on modal choice modeling

Major commuting corridors in metropolitan areas generally comprise multiple transportation modes for commuters, such as transit (subways or buses), private vehicles, or park-and-ride combinations. During the morning peak hour, the commuters would choose one of the available transportation modes to travel through the corridors from rural/suburban living areas to urban working areas. This paper introduces a concept of transportation serviceability to evaluate a transportation mode’s service status in a specific link, route, road, or network during a certain period. The serviceability can be measured by the possibility that travelers choose a specific type of transportation service at a certain travel cost. The commuters’ modal-choice possibilities are calculated using a stochastic equilibrium model based on general travel cost. The modeling results illustrate how transportation serviceability is influenced by background traffic flow in a corridor, value of comfort for railway mode, and parking fee distribution.     

Measuring tradeoffs in carpool driving arrangement preferences

In each of two experiments evaluations were obtained of alternative carpooling situations varying in driving arrangement, size of carpool, distance traveled, and amount of time to pick up and deliver passengers. College students in Experiment I rated each situation in terms of comfort, economy, convenience and overall desirability. Shared driving emerged as the most desirable driving arrangement, and results suggested that this was due to a tradeoff of the perceived economic advantages of being the driver and the perceived greater comfort and convenience of being a rider. Driving all the time was the least preferred arrangement for females, and riding all the time was the least preferred arrangement for males. Desirability ratings decreased as carpool size increased, and this was interpreted to indicate that perceived economic advantages of large pools were outweighed by large perceived decreases in comfort and convenience. The major results of Experiment I were replicated in Experiment II, using university employees who were either currently in carpools or seeking to find carpools. Results are discussed in terms of the practical implications of the findings concerning driving arrangement and carpool size preferences, and in terms of the usefulness of controlled experimental designs for understanding the processes-underlying ride-sharing attitudes and behavior.     

All minutes are not equal: travel time and the effects of congestion on commute satisfaction in Canadian cities

Despite decades of research, it is unclear under which circumstances travel is most onerous. While studies have found that some individuals derive positive utility from aspects of commuting, others have shown that traffic congestion can entail important time, monetary, and mental stress costs. Moreover, responses to traffic congestion-related stressors differs by individual characteristics. In response, this research captures how exposure to traffic congestion events, the duration of this exposure, and individual trait susceptibility to congestion affect the utility of commuting. Working through the lens of individual satisfaction with the duration of their commute, we show that not every minute of travel is valued the same by car commuters in Canadian cities. Results suggest a complex relationship between travel time, congestion, and individual predisposition to congestion-related stress. While improvements in travel time matter for increasing commute satisfaction, it is reductions in travel in congested conditions that matter most, particularly among those susceptible to congestion-related stressors.     

Bottleneck model revisited: An activity-based perspective

The timing of commuting trips made during morning and evening peaks has typically been investigated using Vickrey’s bottleneck model. However, in the conventional trip-based approach, the decisions that commuters make during the day about their activity schedules and time use are not explicitly considered. This study extends the bottleneck model to address the scheduling problem of commuters’ morning home-to-work and evening work-to-home journeys by using an activity-based approach. A day-long activity-travel scheduling model is proposed for the simultaneous determination of departure times for morning and evening commutes, together with allocations of time during the day among travel and activities undertaken at home or at the workplace. The proposed model maximizes the total net utility of the home-based tour, which is the difference between the benefits derived from participating in activities and the disutility incurred by travel between activity locations. The properties of the model solution are analytically explored and compared with the conventional bottleneck model for a special case with constant marginal-activity utility. For the case with linear marginal-activity utility, we develop a heuristic procedure to seek the equilibrium scheduling solution. We also explore the effects of marginal-work utility (or the employees’ average wage level) and of flexible work-hour schemes on the scheduling problem in relation to the morning and evening commuting tours.