Modeling bus bunching using massive location and fare collection data

Bus bunching is a well-known phenomenon for operators, users and regulators of high-frequency bus services. Bus operations are usually affected by increasing differences in the time intervals (headways) between consecutive buses. The effect of this variability is that buses tend to group into bunches of two or more, which severely affects the quality of service and the operational efficiency. The aim of this paper is to analyze which factors are associated to the phenomenon, using massive data from high-frequency services available in Santiago (Chile) and common-route services in Gatineau (Canada). The data is obtained from the bus GPS and AFC systems and are processed to obtain headways between buses. Using data from one week, we develop models to explain the variation of the continuous and discrete indicators of bus bunching as a function of variables related to the operation, variables related to the demand structure, and variables related to the infrastructure. Some of the factors that contribute to increase bus bunching are: stops located toward the end of the route, high scheduled frequency, irregular bus dispatch headways, non-homogeneous fleet, high demand, and high variability of demand. The results are useful for the design of quality indexes to measure bunching in bus operations, and for the design and operation of bus routes, taking into consideration the potential bus bunching problems.     

Modeling isoexposure to transit users for market potential analysis

Transit operators face a difficult fiscal environment and an imperative to contribute to urban sustainability. Under these circumstances, operators must find innovative ways to make public transportation attractive to broader segments of the public, while simultaneously trying to raise revenue to reduce reliance on public subsidies. Development of commercial partnerships is seen as a promising way to achieve these goals. Previous research has examined the potential of using geodemographics to assist transit agencies in the task of identifying potential partners for developing mutually beneficial commercial agreements. In this paper we describe an approach to model isoexposure to transit users as a tool to assess market potential. The approach is based on the analysis of walking behavior of transit users, and specifically distance walked at the end of their transit trip. Spatial modeling is used to geographically project estimates of walking distance for a desired demographic profile at a specific transit facility. After expanding the estimates using sample weights, overlays of these estimates can be used to generate variations in exposure to transit travelers at different locations in space. The approach is demonstrated using the case of Metro users in Montreal, Canada. The case study demonstrates the use of isoexposure profiles as a novel approach to generate marketing intelligence. This should be of interest to transit agencies and businesses interested in developing partnerships.     

The impact of compliance measures on the operation of a bus system: The case of Transantiago

In a regulated bus system operated by private companies, pecuniary incentives can be of primary importance to ensure the quality of the operation and the level of service, especially when there are only a few companies and basically no competition among them. The case of Transantiago, in the capital city of Chile, provides a good example of this. The very ambitious Transantiago project, implemented in 2007 in Santiago, integrated the bus and the subway systems, changing the route structure of the bus services, introducing a common and integrated fare system and electronic payment device, and tendering the operation of approximately 4,600 buses (which by the launch of the system in February 2007 had increased to 5600) to 10 private companies replacing some 4000 small operators which owned 8000 buses. In the beginning, the system faced huge difficulties. Operators' revenue formula basically consisted of a fixed payment, which changed slightly with the actual patronage. This quickly turned out to be a problem, and as technological support became available (several months after the launch), compliance measures were implemented, directly affecting the operators' revenue. The first measure considered the seat/standing places per hour of the buses in operation, for each company, and compared it to the theoretical figure. As a result, buses operating during peak hours increased from 4600 to 5600 in just two months. Subsequent indexes included service frequency and regularity, as well as effective bus-km, aggregated by company first and later by service. This paper shows how the successive implementation of these performance indexes had an impact on the operation of Transantiago in the first years, discusses the difficulties faced to implement them and highlights the importance of technological support to make possible the application of adequate compliance measures.     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

Cruise Traffic Seasonality Patterns in the Western Mediterranean and the Adriatic Sea: A Challenge to Port Operators

The positive trend in the cruise industry since the beginning of the twenty-first century brings with it a series of challenges, mainly for cruise lines and ports. Among them is the seasonality of cruise traffic. This study examines the seasonality of the cruise traffic in the Western Mediterranean and the Adriatic Sea. A sample of 26 ports in 7 countries forms the basis of the empirical analysis, which uses the monthly total cruise passenger movements of each port during the period from 2005 to 2015 as a variable. Methodologically, a “dynamic” classification of ports structured in three sizes is proposed, the seasonality pattern of each port is determined, a cluster analysis is applied to group the ports in clusters with homogeneous patterns, and the changes in seasonal concentration during the analysis period are determined using a Gini coefficient. The main findings suggest the heterogeneity of the ports in the analyzed area and the existence of two clusters with different seasonality patterns. Furthermore, a list of strategies is provided to address the negative effects of cruise traffic seasonality in the management of cruise terminals, taking into account that each cluster obtained requires different strategies.     

Characteristics and consequences of the cruise traffic seasonality on ports: the Spanish Mediterranean case

Cruise traffic is a maritime business and tourist typology that has expanded significantly in the past two decades. The seasonality of the industry affects maritime traffic, generating negative effects for the primary stakeholders involved in the configuration of a cruise itinerary. This article focuses on cruise traffic seasonality from the perspective of cruise ports by analysing a sample of 13 ports on the Spanish Mediterranean coast. The variable used was cruise passenger movements during the period 2000–2015. The main objective of this article is to analyse cruise traffic seasonality in order to identify a pattern, classify through a cluster analysis, and identify the changes in seasonality during the period. Specifically, a threefold analysis has been performed, with the additional goal of providing a series of counter-seasonal suggestions and strategies to apply in the management of cruise ports. First, the seasonality pattern of each port was determined. Second, a cluster analysis was conducted to classify ports into clusters with homogeneous seasonality patterns. Third, an analysis was conducted to identify the changes in seasonality during the period of analysis using the coefficient of variation and the Gini coefficient. This article concludes the existence of two port clusters with different seasonal patterns.     

Estimating traffic volumes on intercity road locations using roadway attributes,socioeconomic features and other work-related activity characteristics

Traffic volume data are key inputs to many applications in highway design and planning. But these data are collected in only a limited number of road locations due to the cost involved. This paper presents an approach for estimating daily and hourly traffic volumes on intercity road locations combining clustering and regression modelling techniques. With the aim of applying the procedure to any road location, it proposes the use of roadway attributes and socioeconomic characteristics of nearby cities as explanatory variables, together with a set of previously discovered patterns with the hourly traffic percent distribution. Test results show that the proposed approach significantly produces accurate estimates of daily volumes for most locations. The accuracy at hourly level is a bit more reduced but, for periods when traffic is significant, more than half of the estimates are within 20% of absolute percentage error. Moreover, the main peak period is approximately identified for most cases. These findings together with its great applicability make this approach attractive for planners when no traffic data are available and an estimate is helpful.     

Global versus localised attitudinal responses in discrete choice

Despite the increasing popularity of including attitudinal and perceptual indicators within discrete choice models, debate endures as to whether there exists a causative relationship between attitudes and behaviour, resulting in what has been termed the attitude behaviour gap. In attempt to understand its origins, attitudes have been categorised as global or localised according to whether or not they are related to a specific time, context and action. Under this framework, global attitudes (GA) typically result in poor predictions of specific overt behaviours, whilst attitudes toward behaviour, or localised attitudes (LA), tend to be better predictors of actual outcomes. Also, attitude strength, measured as the accessibility in memory, plays a determinant role in reducing the gap between attitudes and behaviour, with “memory-based” attitudes having a better prediction of overt behaviours than short-term attitudes constructed “on the spot”. The specific focus of the current paper is to examine the temporal stability and the nature of attitudes, being it critical to transportation planning and research considering the controversial link between attitudes and behaviour. An in depth analysis of the different types of attitudes towards satisfaction for train trips reveals that GAs and LAs provide moderately different outcomes. Also, a memory effect has been found, suggesting the connection between attitudes created on the spot and those stored in memory. Further, both GAs and LAs impact significantly on individual preferences. Finally, the omission of LAs, which are rarely employed within transport literature, may potentially lead to inconsistent estimates, as their contribution in explaining the choice will be absorbed by the error term.

     

Managing a smart bicycle system when demand outstrips supply: the case of the university community in Seville

Of the many public initiatives used to promote the use of bicycles in the urban environment, the one that has achieved the most spectacular results in a short period of time is the public bicycle hire system. The experience of Seville is one of the most successful internationally, where 6.6 % of mechanised trips were being made by bicycle within 30 months. This paper analyses this experience in the university community, which represents one-third of system users. We conclude that the people who are most satisfied with the system are those who use it for leisure and recreation activities, non-residents of the city, more environmentally aware people and those who have no alternative mode of transportation. Their satisfaction is also closely linked to their appreciation of the bicycles’ level of comfort, the ease with which users can hire bicycles and return them and the small amount of paperwork involved required to sign up for the system. However, user appreciation has fallen over time because the system’s rapid success has caused it to become overloaded. This experience therefore provides one main lesson: the system’s success can result in eventual difficulties.     

Enjoyment of commute: A comparison of different transportation modes

This study investigates how socio-demographic and attitudinal variables of university students affect their desire to increase or decrease their daily commute. The case study is McMaster University in Hamilton, Canada, and data was obtained by means of a web-based survey that included questions regarding travel behavior, socio-demographic information, and attitudes toward travel, land use, and the environment. The objective variable is defined as the ratio of ideal to actual commute time, and regression analysis is implemented to test the relationship between this variable and socio-demographic variables and attitudinal scores. The impact of different attitudes on the gap between ideal and actual commute time is expanded to include three different modes, active travel (walk/cycle), transit, and personal automobile. Interestingly, the results indicate that active travelers tend to be less dissatisfied with their commute, followed by those who travel in a personal vehicle and transit users. A number of attitudinal responses are shown to impact the desire to travel more or less, including variables that relate to the social environment, availability of local activities, quality of facilities, productive use of the commute, and the intrinsic value found in the commute travel. The picture emerges of a traveler who would like to spend more time commuting, as someone who is an active traveler, thinks that getting there is half the fun, dislikes traveling alone, but rather likes to live in an active neighborhood where there is a sense of community. The results suggests that enjoyment of commuting, while a challenge from the perspective of motorized mobility, may provide valuable policy opportunities from the perspective of active transportation.