Evaluating bus transit performance of Chinese cities: Developing an overall bus comfort model

In order to improve the level of bus service, a field study was undertaken to develop a combined bus comfort model. This paper provides a comprehensive review of the different ways to predict the bus comfort, in addition to the variable experimental techniques used. It was found some environment parameters like noise, vibration, thermal comfort and the acceleration would affect the passengers’ experience. In this model, both the measurement of objective physical parameters and subjective questionnaire survey were conducted to gather the practical environment date, as well as to distribute questionnaires on board city buses during the same trips. By comparing the subjective views of bus passengers to objective physical parameters, a combined bus comfort model was established. This model helps to calculate the concrete value of passengers’ perceived bus comfort. An effective approach integrated the comfort model, measuring instrument and the driver monitor could greatly improve the bus service quality.     

Merging ICT and informal transport in Jakarta's ojek system

This paper discusses how information and communication technologies (ICT) may influence travel behavior of an informal transport system, and whether and in which ways merging digital technologies represents disruption for a specific sociotechnical ensemble. For decades, ojek has been a form of informal passenger transport, based on motorcycles in Jakarta, and recently smartphone apps have become available in that sociotechnical arrangement. We randomly surveyed passengers and drivers in the central district, for both those who do and do not use these apps. Despite many similarities between both groups, the drivers who use smartphones for their trips reported higher daily incomes, longer average trip distances and a larger coverage area. Passengers using conventional ojek transport reported lower levels of both safety perception and satisfaction when compared to app-based ojek users. For both categories of user, ojek seems to compete with, complement, and be an alternative to bus rapid transit and the suburban rail system (KRL) in the area covered by our sample. The areas covered by regular buses and vans roughly match the origins and destinations of ojek trips.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Passenger waiting time and information acquisition using automatic vehicle location for verification

Bus riders utilize a variety of information media to learn how to travel to their destinations and to learn when they should arrive at bus stops. As part of the OCTA (Orange County Transit Authority) Transit Probe evaluation, 1199 passengers were surveyed to measure relationships between information acquisition and waiting time. A unique aspect of the survey was that some of the data could be correlated with automatic‐vehicle‐location (AVL) measurements of bus lateness at stops. Insights are provided as to the types of information riders acquire based on the nature of the trip and demographic characteristics. Insights are also provided as to factors affecting perceived waiting time. We found age group, whether a person needs to arrive at a destination by a specific time, primary language, and whether the person is a first‐time user of the bus line to be significant causal factors.     

Changes in perceived travel cost and time for the work trip during a period of increasing gasoline costs

This study was designed to examine the relationship between actual and perceived values of cost and time for the work trip and to examine how perceptions have changed over a period of dramatically increased travel costs. Variations in the relationship between perceived and actual values were examined as a function of situational and attitudinal variables. Two telephone surveys were conducted one year apart (Fall 1978 and Fall 1979). On the next working day following a survey, a research assistant recreated the respondent's work trip, recorded time values and used distance measures, car type information and parking costs to compute travel cost. The first survey revealed that most auto users were unable to articulate dollars-and-cents driving costs for the work trip, but auto users in the second survey were able to provide fairly accurate cost estimates. Dramatic changes in fuel prices between surveys is probably the main reason for the change in driving cost awareness. Auto users were also asked to rate relative costs of driving a car compared to using the bus for the work trip. These ratings showed that auto users tended to underestimate driving costs relative to bus costs, but this tendency decreased from the first to the second time period. Commuters in all modal groups at both time periods tended to overestimate travel times. Perception of travel time varied as a function of mode, perceived comfort (for car users), and perceived convenience and number of transfers (for bus users).To whom correspondence should be addressed.     

Promoting bike-and-ride: The Dutch experience

The number of policy initiatives to promote the use of bike-and-ride, or the combined use of bicycle and public transport for one trip, has grown considerably over the past decade as part of the search for more sustainable transport solutions. This paper discusses the experiences with, and impacts of, such initiatives in the Netherlands. The Dutch measures to promote bicycle use in access trips have been generally successful. A country-wide program to upgrade regular and secure bicycle parking at train stations has led to an increase in user satisfaction and a growth in bicycles parked at stations. Smaller programs to stimulate the combined use of bike-and-bus have resulted in an increase in bicycle use, bus use, and share of infrequent bus passengers. Bicycle lockers at bus stops are hardly used by bus passengers, due in part to the dominance of students among bus users as well as the relatively high price of lockers in comparison to the value of bicycles used for access trips. Measures to promote the use of the bicycle in egress trips have met with more varying results. Projects to introduce leasing bicycles for egress trips have failed to attract passengers, for both train and bus services. In contrast, the introduction of flexible rental bicycles at train stations has resulted in a small reduction in car use, growth in train trips, and growth in bicycle use for non-recurrent trips. The Dutch experiences suggest some lessons for promoting bike-and-ride in countries and cities with a less well-developed bicycle infrastructure.     

The ambivalence of ridesharing

Ridesharing is quite a popular topic of discussion among transport authority personnel. It is perceived to be a viable alternative to classical modes of transportation, and receives a great deal of political support from transport planners. However, not much objective information is available on ridesharing behaviors. We use travel survey data to study the evolution of the ridesharing market in an urban area. Our study is based on data from four large-scale OD surveys conducted in the Greater Montreal Area (1987, 1993, 1998 and 2003). In the latest survey conducted in Montreal, car passengers were asked to identify the driver who gave them the opportunity to travel in this way. Their answers were classified according to the type of driver; for instance, a member of their household, a neighbor or a co-worker. We use this information to calibrate a model matching car passengers and car drivers belonging to the same household. This will be referred to as IHHR (intra-household ridesharing). Preliminary results reveal that approximately 70% of all trips made by car passengers are the result of IHHR. Furthermore, around 15% of those trips are questionable, in that they were exclusively generated for another individual’s purposes, consequently generating an additional trip for the journey back home. Moreover, this percentage increased over time. Objective data regarding ridesharing and its evolution in an urban area will undoubtedly help decision makers gain a clearer profile of this means of travel and help to realign attitudes on the issue.

An improved headway-based holding strategy for bus transit

Abstract

This paper presents an improved headway-based holding strategy integrating bus transit travel and dwelling time prediction. A support vector machine-based (SVM) model is developed to predict the baseline travel and dwell times of buses based on recent data. In order to reduce prediction errors, an adaptive algorithm is used together with real-time bus operational information and estimated baseline times from SVM models. The objective of the improved holding strategy is to minimize the total waiting times of passengers at the current stop and at successive stops. Considering the time-varying features of bus running, a ‘forgetting factor’ is introduced to weight the most recent data and reduce the disturbance from unexpected incidents. Finally, the improved holding strategy proposed in this study is illustrated using the microscopic simulation model Paramics and some conclusions are drawn.     

Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data

This paper explores how we can use smart card data for bus passengers to reveal individual and aggregate travel behaviour. More specifically, we measure the extent to which both individual and bus routes exhibit habitual behaviour. To achieve this, we introduce a metric called Stickiness Index to quantify the range of preferences of users that always select to travel on the same route (high stickiness) to those with a more varied patterns of route selection (low stickiness). Adopting a visual analytic and modelling approach using a suite of regression models we find evidence to suggest that stickiness varies across the metropolitan area and over a 24-h period wherein higher stickiness is associated with high frequency users where there is substantial variability of route travel times across all alternatives. We argue that our findings are important in their capacity to contribute to a new evidence base with the potential to inform the (re)-design and scheduling of a public transit systems through unveiling the complexities of transit behaviour.     

Bus crime in Los Angeles: II—Victims and public impact

This paper documents victims of bus crime and examines the extent to which fear of personal security affects bus ridership. Using data from a victimization survey of 1088 households in west central Los Angeles, it was found that frequency of bus use was the most important correlate of being victimized. Examining moderate and heavy bus users only, it was found that the elderly, women, Hispanics and low-income persons were more likely to be victimized than other subpopulations. There was a general perception that bus travel to downtown Los Angeles was more dangerous than travel within residential neighborhoods, and that night travel was much more dangerous than day travel. Women, Hispanics and persons of low education level were more likely to perceive bus use as dangerous, indicating a subpopulation correspondence between the likelihood of victimization and perceptions of safety from bus crime. In addition, persons who had been victimized by a bus crime or who knew persons who had been victimized were more likely to perceive bus use as less safe. Lastly, it appears that victims of bus crimes, persons who had witnessed bus crimes and persons who perceived bus travel as less safe may be less likely to use buses, especially on certain routes and during certain times, but these variables are secondary in importance to automobile access, the convenience of bus travel and age.     

Bus running time prediction using a statistical pattern recognition technique

Abstract

Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.     

Policy Simulation for New BRT and Area Pricing Alternatives Using an Opinion Survey in Jakarta

Abstract

An area pricing scheme for Jakarta, Indonesia, is currently under review as a transportation control measure along with the operation of new bus rapid transit (BRT) system. While this scheme may be effective for congestion reduction in the central business district (CBD), provision of alternative means of transportation for auto users that are ‘pushed-out’ is of great importance to obtain public acceptance. Hence, it is necessary to simulate simultaneously the area pricing scheme and the BRT development which may serve as an alternative for assumed ‘pushed-out’ auto users. Utilizing data from an opinion survey, this paper studies how BRT and auto ridership are likely to vary as a function of traveler and system attributes. Additionally, the study attempts to evaluate the way this new travel mode is distinguished from other existing conventional transportation alternatives in Jakarta. The survey data contains socioeconomic information of over 1000 respondents as well as details of to-work/school trips to the CBD including mode, travel cost, time, etc. Respondents were asked about their willingness to shift from their current mode to BRT to make the same travel for different BRT fare levels. Modeling efforts suggest that a mixed logit model performs better in explaining choice behavior. Therefore, this model was used for policy simulation. The simulation results brought about many implications as to the tested policies. While the developed models may be applied only to future BRT corridors in which the survey was conducted, they capture the key variables that are significant in explaining mode choice behavior and present great potential for practical use in policy simulation and analysis in a large metropolitan area of the developing world.     

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.     

Economic and service comparison of conventional bus and automated transit—a case study

Three origin‐destination matrices of inter‐zonal person trips for a section of the Los Angeles metropolitan region are analyzed using principal component analysis. The matrices represent total person trips, journey‐to‐work trips, and shopping trips. This allows for the identification of a number of sub‐regional travel fields or functional regions within the area. The composition of and interrelationships between these fields and the spatial coincidence of fields defined for different travel purposes are compared with existing and proposed public transit facilities.     

Livelihoods,daily mobility and poverty in sub-saharan Africa

Based on research funded by the UK Department for International Development, this paper investigates the utility of a livelihoods approach in identifying the mobility and accessibility needs of the poor. Mobility patterns and livelihoods of stratified samples of households in urban-to-rural corridors originating in the national capital cities of Zimbabwe and Uganda are compared, with emphasis on the poor's position relative to higher income groups. It is found that livelihood work was the most frequent purpose of short-distance travel for all income groups and localities, amounting to 38% of trip purposes in Uganda and 46% in Zimbabwe. On average, Zimbabweans were more mobile making more daily trips over longer distances reflective of greater reliance on motorized transport in the country. Nonetheless, walking dominates modal journeys in both countries. Ugandans display heavier dependence on bicycle and motorcycle transport primarily through taxi hire compared with Zimbabweans' private care and public kombi bus transport. Survey evidence suggests that Uganda's poor and middle-incomed urban and rural residents benefit from more widely available multimodal public transport.     

Characteristics analysis for travel behavior of transportation hub passengers using mobile phone data

The travel behavior of passengers from the transportation hub within the city area is critical for travel demand analysis, security monitoring, and supporting traffic facilities designing. However, the traditional methods used to study the travel behavior of the passengers inside the city are time and labor consuming. The records of the cellular communication provide a potential huge data source for this study to follow the movement of passengers. This study focuses on the passengers’ travel behavior of the Hongqiao transportation hub in Shanghai, China, utilizing the mobile phone data. First, a systematic and novel method is presented to extract the trip information from the mobile phone data. Several key travel characteristics of passengers, including passengers traveling inside the city and between cities, are analyzed and compared. The results show that the proposed method is effective to obtain the travel trajectories of mobile phone users. Besides, the travel behavior of incity passengers and external passengers are quite different. Then, the correlation analysis of the passengers’ travel trajectories is provided to research the availability of the comprehensive area. Moreover, the results of the correlation analysis further indicate that the comprehensive area of the Hongqiao hub plays a relatively important role in passengers’ daily travel.

     

A bi-level programming for bus lane network design

This paper proposes a bi-level programming model to solve the design problem for bus lane distribution in multi-modal transport networks. The upper level model aims at minimizing the average travel time of travelers, as well as minimizing the difference of passengers’ comfort among all the bus lines by optimizing bus frequencies. The lower level model is a multi-modal transport network equilibrium model for the joint modal split/traffic assignment problem. The column generation algorithm, the branch-and-bound algorithm and the method of successive averages are comprehensively applied in this paper for the solution of the bi-level model. A simple numerical test and an empirical test based on Dalian economic zone are employed to validate the proposed model. The results show that the bi-level model performs well with regard to the objective of reducing travel time costs for all travelers and balancing transit service level among all bus lines.     

A stochastic optimization model for transit network timetable design to mitigate the randomness of traveling time by adding slack time

Transit network timetabling aims at determining the departure time of each trip of all lines in order to facilitate passengers transferring either to or from a bus. In this paper, we consider a bus timetabling problem with stochastic travel times (BTP-STT). Slack time is added into timetable to mitigate the randomness in bus travel times. We then develop a stochastic integer programming model for the BTP-STT to minimize the total waiting time cost for three types of passengers (i.e., transferring passengers, boarding passengers and through passengers). The mathematical properties of the model are characterized. Due to its computational complexity, a genetic algorithm with local search (GALS) is designed to solve our proposed model (OPM). The numerical results based on a small bus network show that the timetable obtained from OPM reduces the total waiting time cost by an average of 9.5%, when it is tested in different scenarios. OPM is relatively effective if the ratio of the number of through passengers to the number of transferring passengers is not larger than a threshold (e.g., 10 in our case). In addition, we test different scale instances randomly generated in a practical setting to further verify the effectiveness of OPM and GALS. We also find that adding slack time into timetable greatly benefits transferring passengers by reducing the rate of transferring failure.