Effects of new bus and rail rapid transit systems – an international review

Cities worldwide are implementing modern transit systems to improve mobility in the increasingly congested metropolitan areas. Despite much research on the effects of such systems, a comparison of effects across transit modes and countries has not been studied comprehensively. This paper fills this gap in the literature by reviewing and comparing the effects obtained by 86 transit systems around the world, including Bus Rapid Transit (BRT), Light Rail Transit (LRT), metro and heavy rail transit systems. The analysis is twofold by analysing (i) the direct operational effects related to travel time, ridership and modal shifts, and (ii) the indirect strategic effects in terms of effects on property values and urban development. The review confirms the existing literature suggesting that BRT can attract many passengers if travel time reductions are significantly high. This leads to attractive areas surrounding the transit line with increasing property values. Such effects are traditionally associated with attractive rail-based public transport systems. However, a statistical comparison of 41 systems did not show significant deviations between effects on property values resulting from BRT, LRT and metro systems, respectively. Hence, this paper indicates that large strategic effects can be obtained by implementing BRT systems at a much lower cost.     

A new schedule-based transit assignment model with travel strategies and supply uncertainties

This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space–time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers.     

Waiting time perceptions at transit stops and stations: Effects of basic amenities,gender, and security

Waiting time in transit travel is often perceived negatively and high-amenity stops and stations are becoming increasingly popular as strategies for mitigating transit riders’ aversion to waiting. However, beyond recent evidence that realtime transit arrival information reduces perceived waiting time, there is limited empirical evidence as to which other specific station and stop amenities can effectively influence user perceptions of waiting time. To address this knowledge gap, the authors conducted a passenger survey and video-recorded waiting passengers at different types of transit stops and stations to investigate differences between survey-reported waiting time and video-recorded actual waiting time. Results from the survey and video observations show that the reported wait time on average is about 1.21 times longer than the observed wait time. Regression analysis was employed to explain the variation in riders’ reported waiting time as a function of their objectively observed waiting time, as well as station and stop amenities, weather, time of the day, personal demographics, and trip characteristics. Based on the regression results, most waits at stops with no amenities are perceived at least 1.3 times as long as they actually are. Basic amenities including benches and shelters significantly reduce perceived waiting times. Women waiting for more than 10 min in perceived insecure surroundings report waits as dramatically longer than they really are, and longer than do men in the same situation. The authors recommend a focus on providing basic amenities at stations and stops as broadly as possible in transit systems, and a particular focus on stops on low-frequency routes and in less safe areas for security measures.     

Policy analysis of third party electronic coupons for public transit fares

Mobile technologies are generating new business models for urban transport systems, as is evident from recent startups cropping up from the private sector. Public transport systems can make more use of mobile technologies than just for measuring system performance, improving boarding times, or for analyzing travel patterns. A new transaction model is proposed for public transport systems where travelers are allowed to pre-book their fares and trade that demand information to private firms. In this public-private partnership model, fare revenue management is outsourced to third party private firms such as big box retail or large planned events (such as sports stadiums and theme parks), who can issue electronic coupons to travelers to subsidize their fares. This e-coupon pricing model is analyzed using marginal cost theory for the transit service and shown to be quite effective for monopolistic coupon rights, particularly for demand responsive transit systems that feature high cost fares, non-commute travel purposes, and a closed access system with existing pre-booking requirements. However, oligopolistic scenarios analyzed using game theory and network economics suggest that public transport agencies need to take extreme care in planning and implementing such a policy. Otherwise, they risk pushing an equivalent tax on private firms or disrupting the urban economy and real estate values while increasing ridership.     

Large-scale transit market segmentation with spatial-behavioural features

Transit market segmentation enables transit providers to comprehend the commonalities and heterogeneities among different groups of passengers, so that they can cater for individual transit riders’ mobility needs. The problem has recently been attracting a great interest with the proliferation of automated data collection systems such as Smart Card Automated Fare Collection (AFC), which allow researchers to observe individual travel behaviours over a long time period. However, there is a need for an integrated market segmentation method that incorporating both spatial and behavioural features of individual transit passengers. This algorithm also needs to be efficient for large-scale implementation. This paper proposes a new algorithm named Spatial Affinity Propagation (SAP) based on the classical Affinity Propagation algorithm (AP) to enable large-scale spatial transit market segmentation with spatial-behavioural features. SAP segments transit passengers using spatial geodetic coordinates, where passengers from the same segment are located within immediate walking distance; and using behavioural features mined from AFC data. The comparison with AP and popular algorithms in literature shows that SAP provides nearly as good clustering performance as AP while being 52% more efficient in computation time. This efficient framework would enable transit operators to leverage the availability of AFC data to understand the commonalities and heterogeneities among different groups of passengers.     

A utility-based travel impedance measure for public transit network accessibility

A utility-based travel impedance measure is developed for public transit modes that is capable of capturing the passengers’ behaviour and their subjective perceptions of impedance when travelling in the transit networks. The proposed measure is time-dependent and it estimates the realisation of the travel impedance by the community of passengers for travelling between an origin–destination (OD) pair.The main advantage of the developed measure, as compared to the existing transit impedance measures, relates to its capability in capturing the diversity benefit that the transit systems may offer the society of travellers with different traveling preferences. To clarify the necessity of such capability, we demonstrate the randomness (subjectivity) of travel impedance perceived by transit passengers, through evidence from the observed path choices made in the transit network of the greater Brisbane metropolitan region in Australia.The proposed impedance measure is basically a nested logit “logsum” composition over a generated set of reasonable path options whose systematic utilities are evaluated based on a discrete choice model previously developed and calibrated for the greater Brisbane transit passengers. As a case study, the proposed impedance measure is calculated for all the origin blocks in the Brisbane area, during the morning commutes to the Central Business District (CBD). The results are presented and discussed, and intuitive and important advantages are demonstrated for the proposed measure.     

Calibrating a transit assignment model using smart card data in a large-scale multi-modal transit network

This paper describes a practical automated procedure to calibrate and validate a transit assignment model. An optimization method based on particle swarm algorithm is adopted to minimize a defined error term. This error term which is based on the percentage of root mean square error and the mean absolute percent error encompasses deviation of model outputs from observations considering both segment level as well as the mode level and can be applied to a large scale network. This study is based on the frequency-based assignment model using the concept of optimal strategy while any transit assignment model can be used in the proposed methodological framework. Lastly, the model is validated using another weekday data. The proposed methodology uses automatic fare collection (AFC) data to estimate the origin–destination matrix. This study combines data from three sources: the general transit feed specification, AFC, and a strategic transport model from a large-scale multimodal public transport network. The South-East Queensland (SEQ) network in Australia is used as a case study. The AFC system in SEQ has voluminous and high quality data on passenger boardings and alightings across bus, rail and ferry modes. The results indicate that the proposed procedure can successfully develop a multi-modal transit assignment model at a large scale. Higher dispersions are seen for the bus mode, in contrast to rail and ferry modes. Furthermore, a comparison is made between the strategies used by passengers and the generated strategies by the model between each origin and destination to get more insights about the detailed behaviour of the model. Overall, the analysis indicates that the AFC data is a valuable and rich source in calibrating and validating a transit assignment model.

     

Planning and Evaluation of Passenger Ferry Service in Hong Kong

A predominant observation in Hong Kong is the continuous loss in ferry patronage. There are two main reasons for this: poor level-of-service and better competitors. New roads, bridges, and tunnels are serving the buses, and to some extent the railways; whereas the investment in ferry terminals is relatively at a lower level. On the one hand, there is no need to promote the ferries in a free market environment; but on the other hand, the ferries have the best safety record, can only relieve some traffic congestion and need water access that is one of the characteristics of Hong Kong. The goal of this paper is to design a planning approach combined with an evaluation procedure on how to make the best use of the existing water and pier resources in Hong Kong through the provision of commercially viable ferry services. The approach used covers the impact of future developments planning up to 2006 comprising all public transport modes in Hong Kong (heavy rail, metro, bus, and ferry). The planning tool is based on a newly developed multi-objective evaluation method in order to assess the ferry routes with scientific, practical, and simplified analyses for future use. This assessment is applied to the existing ferry routes and candidate routes and can also be carried out on an individual route basis or on a given set of routes. The objective functions set forth analytically in the evaluation method take into account the interests of the three participants: the passengers, the operators and the government. The proposed ferry network design formulation and the suggested new ferry routes will have a positive impact on changing the ferry system’s image in Hong Kong.     

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.     

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.     

The characteristics,uses and potentials of taxicab transportation

Taxicab transportation is a significant segment of urban transportation. Taxicabs, along with other “paratransit” type systems, provide service with characteristics between the automobile and mass transportation. Consequently, they are well suited to a number of special purposes. Taxicabs currently serve a wide range of trip purposes by travellers with varied socio-economic characteristics. Taxicab transportation is most attractive for serving lower density area and off-peak travel particularly where there is only minimal mass transit service. In this regard, taxicabs are a supplement to conventional mass transit. The use of taxicabs for collection and distribution functions for both passengers and freight is gradually being realized. The multiple use of taxicabs offers advantages of increasing taxicab productivity and reducing individual trip costs. Many of the problems related to taxicabs are regulatory and institutional in nature. Unless these constraints are eased or removed, wider application of taxicab transportation, including productivity gains, will be limited.     

A congested and dwell time dependent transit corridor assignment model

This research proposes an equilibrium assignment model for congested public transport corridors in urban areas. In this model, journey times incorporate the effect of bus queuing on travel times and boarding and alighting passengers on dwell times at stops. The model also considers limited bus capacity leading to longer waiting times and more uncomfortable journeys. The proposed model is applied to an example network, and the results are compared with those obtained in a recent study. This is followed by the analysis and discussion of a real case application in Santiago de Chile. Finally, different boarding and alighting times and different vehicle types are evaluated. In all cases, demand on express services tends to be underestimated by using constant dwell time assignment models, leading to potential planning errors for these lines. The results demonstrate the importance of considering demand dependent dwell times in the assignment process, especially at high demand levels when the capacity constraint should also be considered. Copyright © 2017 John Wiley & Sons, Ltd.     

Analyzing year-to-year changes in public transport passenger behaviour using smart card data

In recent years, there has been increased interest in using completely anonymized data from smart card collection systems to better understand the behavioural habits of public transport passengers. Such an understanding can benefit urban transport planners as well as urban modelling by providing simulation models with realistic mobility patterns of transit networks. In particular, the study of temporal activities has elicited substantial interest. In this regard, a number of methods have been developed in the literature for this type of analysis, most using clustering approaches. This paper presents a two-level generative model that applies the Gaussian mixture model to regroup passengers based on their temporal habits in their public transportation usage. The strength of the proposed methodology is that it can model a continuous representation of time instead of having to employ discrete time bins. For each cluster, the approach provides typical temporal patterns that enable easy interpretation. The experiments are performed on five years of data collected by the Société de transport de l’Outaouais. The results demonstrate the efficiency of the proposed approach in identifying a reduced set of passenger clusters linked to their fare types. A five-year longitudinal analysis also shows the relative stability of public transport usage.     

Stochastic transit equilibrium

We present a transit equilibrium model in which boarding decisions are stochastic. The model incorporates congestion, reflected in higher waiting times at bus stops and increasing in-vehicle travel time. The stochastic behavior of passengers is introduced through a probability for passengers to choose boarding a specific bus of a certain service. The modeling approach generates a stochastic common-lines problem, in which every line has a chance to be chosen by each passenger. The formulation is a generalization of deterministic transit assignment models where passengers are assumed to travel according to shortest hyperpaths. We prove existence of equilibrium in the simplified case of parallel lines (stochastic common-lines problem) and provide a formulation for a more general network problem (stochastic transit equilibrium). The resulting waiting time and network load expressions are validated through simulation. An algorithm to solve the general stochastic transit equilibrium is proposed and applied to a sample network; the algorithm works well and generates consistent results when considering the stochastic nature of the decisions, which motivates the implementation of the methodology on a real-size network case as the next step of this research.     

A model of stoppings on urban bus routes

The amount of time required to pick up and discharge passengers is an important issue in the planning and modeling of urban bus systems. Several past studies have employed models of this component of bus travel time which are based, in part, on a model of the number of stoppings the bus makes to pick up or discharge passengers. Most past versions of this model have assumed that expected demand does not vary from stop to stop or from trip to trip, but that the number of passengers demanding service at any given stop during any given trip follows a Poisson distribution. An alternative model is derived, based on the assumption that expected demand varies among stops and times of day but is fixed from day to day at any given stop and time of day. Boarding and alighting survey data are used to verify that the “average-demand” Poisson model consistently overestimates the number of stoppings and to calibrate an approximate version of the alternative model. A stop-spacing optimization model previously developed by Kikuchi and Vuchic is reevaluated using the alternative stopping model in place of the average demand model used in the original version. The results are found to be considerably different, thus indicating that transit route optimization models are sensitive to the way in which stopping processes are modeled.     

Privatization of urban transit: The Los Angeles jitney experience

This paper reports on a recent attempt to provide private transit in the form of jitney service in downtown Los Angeles. It describes the process undertaken to initiate jitney service and the resultant organization's structure and operation. A survey of jitney passengers provided information on the users and their tripmaking characteristics. A group of loyal jitney riders emerged who patronized the service because of its lower travel times and more personalized atmosphere. This group formed the core of frequent users. The Los Angeles experience is analyzed in terms of the economic feasibility of jitney service and the impact on the financial status of public transit. The public transit agency experienced a slight negative financial impact as a result of the jitney service. Ridership during peak hours declined somewhat but the jitney service was not frequent enough to carry sufficient passengers to allow the transit agency to cut costly peak hour service. This analysis shows that the jitney service ultimately was not an economically successful operation. The factors which would have increased the likelihood of success were increased frequency of service and higher fares, which would have been sustainable if not for unexpected developments in public transit financing. A labor pool willing to work for low wages, high transit use in the central city, relatively high transit fares and the availability of inexpensive vehicles appear to be prerequisites to a successful urban jitney operation.     

Modeling and optimizing urban bus transit considering headway variation for cost and service reliability analysis

Due to the stochastic nature of traffic conditions and demand fluctuations, it is a challenging task for operators to maintain reliable services, and passengers often suffer from longer travel times. A failure to consider this issue while planning bus services may lead to undesirable results, such as higher costs and a deterioration in level of service. Considering headway variation at route stops, this paper develops a mathematical model to optimize bus stops and dispatching headways that minimize total cost, consisting of both user and operator costs. A Genetic Algorithm is applied to search for a cost-effective solution in a real-world case study of a bus transit system, which improves service reliability in terms of a reduced coefficient of variation of headway.     

Transit network design based on travel time reliability

This paper presents a transit network optimization method, in which travel time reliability on road is considered. A robust optimization model, taking into account the stochastic travel time, is formulated to satisfy the demand of passengers and provide reliable transit service. The optimization model aims to maximize the efficiency of passenger trips in the optimized transit network. Tabu search algorithm is defined and implemented to solve the problem. Then, transit network optimization method proposed in this paper is tested with two numerical examples: a simple route and a medium-size network. The results show the proposed method can effectively improve the reliability of a transit network and reduce the travel time of passengers in general.     

Comfort and Safety as Perceived by Wheelchair-Seated Bus Passengers

Abstract

Wheelchair-seated passengers on European and Swedish urban transit buses can travel rearwards, resting against a bulkhead, without the use of tie-down equipment. However, users sometimes disapprove of being the only passengers who have to travel rearwards, and also unrestrained. In order to investigate comfort and safety as perceived by wheelchair-seated bus passengers riding either forwards or rearwards, an experimental field study was carried out. Participating subjects were 31 wheelchair users and a group of 44 ambulant passengers. Each subject made two consecutive, identical 15-minute trips, randomly beginning either forwards or backwards, and interviews were conducted after each trip. During the trips, three-axis bus motion was recorded. The concept of categorization was used as a theoretical background and basis for discussion of the comfort and safety constructs. The results indicated that while the majority preferred the forward-facing position regarding comfort issues, a minority felt that the level of perceived safety was better. Wheelchair-seated passengers were more positive towards the rearward position than the ambulant group.     

Does regional travel time unreliability influence mode choice?

Researchers and practitioners highlight the unreliability of travel as a potential weak link in the transportation system which may inhibit individuals’ accessibility and urban economic activity. With the trend towards increasing traffic congestion, the outlook suggests that travel conditions will become structurally less reliable over time, but that not all places will be equally affected. But is travel time unreliability a problem? This study uses global positioning systems travel survey data for Chicago to build a regional model of travel time unreliability. The results suggest that unreliability varies spatially during different time periods, but that the average overall network unreliability varies little across times in the day. Using the Chicago Metropolitan Agency for Planning (CMAP)’s 2007 Travel Tracker Survey, a household travel diary survey including both GPS and non-GPS components, we estimate a mode choice model for work trips to explore the influence of unreliability on travel behavior. The results suggest that unreliable auto travel conditions induce mode switching to transit and that the influence is strongest when service by train is already faster than by car. This further suggests that auto travel unreliability may have the strongest influence in metropolitan regions with highly-competitive transit systems. Nevertheless, the influence of travel unreliability is limited and is not the underlying driver of travel decision-making.