Academic literature on the topic 'Transit Shuttle Buses'

Urban rail systems frequently suffer from unexpected service disruptions, which can result in severe delays and user dissatisfaction. “Bus bridging” is the strategy most commonly applied in responding to rail service interruptions in North America and Europe. Buses are pulled from regular routes and dispatched to serve as shuttles along the disrupted rail segment until regular train service is restored. In determining the required number of buses and source routes, most transit agencies rely on ad hoc approaches based on operational experience and constraints, which do not necessarily alleviate the extensive delays and queue build-ups at affected stations, nor do they minimize system-wide impacts in an optimal manner. This paper proposes a genetic algorithm-based optimization model to determine the optimal number of shuttle buses and route allocation to minimize overall subway- and bus rider delay for any given rail disruption incident. The generated optimal solutions were sensitive to bus-bay capacity constraints along the shuttle service corridor of any given disrupted subway segment, utilizing methods found in the Transit Capacity and Quality of Service Manual. The model was used in an analysis of real-world incident data obtained from the Toronto Transit Commission and supplemented by other passenger and travel time data. The bus bridging toolkit showed strong potential to produce efficient shuttle response plans that reduced the transit user delays by more than 50% while ensuring minimum queue formation at disrupted stations and maximizing the utilization of shuttle buses.

Bus bridging is a key strategy used by transit agencies to handle rail service interruptions. In practice, buses are dispatched from scheduled services to act as temporary shuttles along the disrupted rail segment. This study provides a robust analysis of four factors affecting bus bridging policies: 1) initial dispatch direction of shuttle buses, 2) dispatch time (i.e., the response time for requesting shuttle buses), 3) uncertainty in predicting the incident duration, and 4) reduction of metro passengers demand because of disruption. A user delay modeling tool is used to assess various bus bridging policies based on their resulting users’ delays (for affected passengers) and other system performance measures. The tool was validated, and sensitivity analysis was conducted based on real disruption scenarios that suspended various segments of the metro service in the City of Toronto. The main results indicate that: 1) the initial dispatch direction of shuttle buses should take into consideration the demand at the disrupted segment while maintaining a moderate level of shuttle bus utilization; 2) a 1-min increase in the dispatch time causes about 0.4 min additional waiting time at disrupted metro stations per passenger; 3) incidents with high forecasting errors can cause excessive delays for metro passengers and significant wasted time of non-utilized shuttle buses; and, 4) significant users’ delay savings are observed at higher demand reduction levels. This paper provides transportation practitioners and planners with a better understanding of the different aspects of bus bridging policies based on users’ delays and shuttle buses’ performance metrics.

High-quality transit service is a vital aspect of any modern city. When unexpected interruptions to the transit service occur, they reduce the quality of service provided to the public. One of the main strategies that is employed to deal with rail service interruptions is “bus bridging,” whereby buses from scheduled services are deployed to offer shuttle services. Very few efforts are found in the literature that have investigated this policy’s effectiveness. Therefore, this study aims at exploring the different aspects and impacts of retracting buses from scheduled services in response to subway and streetcar service interruptions in Toronto. It explores the size of the deployment, as well as the system response and recovery times using detailed subway and streetcar shuttle service reports collected in 2015. The paper shows remarkable fluctuations not only in the utilized number of shuttle service buses over time, but also on the service response and recovery times.

As transit authorities increasingly adopt electric buses (EBs) to mitigate air quality concerns and greenhouse gas emissions, new challenges arise in bus scheduling and timetabling. Unlike traditional buses, EBs face operational obstacles due to their shorter range and extended charging times. Existing mathematical optimization models for operation planning of traditional buses must be revised to address these unique characteristics of EBs. This study introduces a new approach to integrate timetabling and bus scheduling to enhance the level of service and minimize operational costs, using a case study of a University shuttle bus service in Montreal, Canada. The level of service will be enhanced by reducing students waiting time and improving their in-vehicle comfort through seat availability. The scheduling aspect seeks to reduce the total operational costs, which include travel, electricity consumption, and usage costs of EBs. The proposed algorithm calculates the waiting time and seat availability for different headway values and addresses the scheduling problem using a mixed-integer linear programming (MILP) model with an arc-based approach, solved using the Cplex Optimization Studio software version 12.8. A normalized weighted sum technique is then applied to select the optimal headway, balancing waiting time, seat availability, and operational costs. The effectiveness of our approach was tested through a case study of Concordia University’s shuttle bus service. Comparative analysis of the current and proposed schedules shows that our approach significantly improves service quality by decreasing waiting times and increasing seat availability while optimizing cost-effectiveness compared to the existing timetable of the Concordia shuttle bus. The proposed approach ensures a smooth transition to a fully electric transit system for shuttle bus services.

Purpose The purpose of the present study is to examine the effectiveness of tourist shuttle bus advertising for the corporate brand image of gaming and hospitality operators. Design/methodology/approach Grounded in the theoretical framework of Message Response Involvement (MRI) theory, a multilevel design with hierarchical modeling was adopted to examine the hypothesized paths between consumers’ message processing components and corporate brand equity. The moderating effects of shuttle bus design were also investigated. The data were collected via a self-administered questionnaire from 595 tourists visiting Macao. Findings The results indicated that advertising effectiveness (i.e., corporate brand equity) was largely dependent on consumers’ motivation and ability to process information. When design was included as a moderator, it enhanced the influence of consumers’ motivation to process information on advertising effectiveness. Research limitations/implications The findings highlight the importance of tourist shuttle buses as an advertising platform in the hospitality and gaming industry and depict important aspects of consumers and executional cues that corporations should focus on improving shuttle bus advertising effectiveness. Originality/value This study examines an underexplored, yet frequently used, advertising channel – the shuttle bus. Specifically, it offers a better understanding of transit advertising effectiveness from the corporate level (design) and individual level (consumers’ motivation, ability and opportunity) in the tourism and hospitality industry.

Public transportation is an essential component of building sustainable communities. However, its ridership remains low in most cities in the United States. Among the major barriers is the long distance to the bus stops, called the first-mile problem. Using a stated preference survey among 1056 residents of El Paso, Texas, this study addresses this problem by estimating additional transit trips that can be expected from the implementation of hypothetical, free shuttles between one’s home and the closest bus stops. Participants reported 7.73 additional transit trips per week (469% increase from the current baseline), including 3.03 additional trips for work, 1.94 for daily errands, 1.64 for leisure or social, and 0.93 for exercise or sports. The percentage of transit non-users dropped from 77.6% (baseline) to 38.2%. With the free shuttle service, respondents would favor bus rapid transit more than regular buses (4.72 vs. 3.00 additional trips). Residents identifying as an existing transit user, being Hispanic/Latino, owning at least one automobile, living within 1 mile of a transit stop, and feeling safe while riding the bus would make significantly more transit trips due to the service. This study suggests that programs to address/reduce the first-mile problem could increase transit demand and, therefore, contribute to creating sustainable and more connected communities.

Airport shuttle buses, as a specialized form of bus service, serve as an economical, efficient, and sustainable transportation option for air travelers. In contrast to conventional bus services, airport shuttle bus operations exhibit more pronounced market-oriented characteristics, striving to balance extensive public transport coverage with the optimization of corporate profitability. Although these services outperform regular bus transit in terms of efficiency, they incur higher operational costs. However, existing studies on enhancing profitability and optimizing resource allocation for airport shuttle buses are inadequate. This study proposes a differential pricing strategy based on historical ticketing data. Initially, we analyze the characteristics of orders, users, and reservations within the context of customized bus operations. Leveraging the differences among various groups, we employ clustering techniques to classify seat grades and segment users. Based on the clustering outcomes, we determine distinct price elasticity values for each segment. As the strategies are developed based on seat grades, booking time, and user travel patterns, the numerical experiments indicate that the proposed differentiated pricing strategy can increase the revenue of customized public transport services by at least 41%. This strategy not only enhances the efficiency of resource allocation and service accessibility but also makes the service more financially sustainable.

The Campus Shuttle Tracker System is an innovative solution designed to enhance the commuting experience for students by providing real-time tracking of college shuttle buses. This system leverages GPS technology to deliver accurate location updates and estimated arrival times, ensuring that students can plan their travel efficiently. Additionally, the system integrates an attendance management feature, simplifying the process of logging attendance for both students and administration. By linking attendance records with shuttle usage, it provides a seamless and automated approach to tracking student participation. To support operational efficiency, it monitors fuel consumption and generates digital request forms for refuelling, helping to maintain optimal fuel management. It also collects the data for daily running of the bus from start of the day. Additionally, it includes an integrated online payment gateway for collecting bus fees, generating digital bus passes to promote a paperless and seamless process. The system incorporates RFID technology to automate student attendance during transit, ensuring accurate and tamper-proof records. It would be upcoming feature with a user-friendly interface and robust backend, the Campus Shuttle Tracker System aims to address common challenges faced in campus transportation while fostering convenience, safety, and time management for students and staff alike.

The capability of ‘demand-responsive transport’, particularly in autonomous shared form, to better facilitate road-based mobility is considered a significant advantage because improved mobility leads to enhanced quality of life and wellbeing. A central point in implementing a demand-responsive transit system in a new area is adapting the operational concept to the respective structural and socioeconomic conditions. This requires an extensive analysis of the users’ needs. There is presently limited understanding of public perceptions and attitudes toward the adoption of autonomous demand-responsive transport. To address this gap, a theory-based conceptual framework is proposed to provide detailed empirical insights into the public’s adoption intention of ‘autonomous shuttle buses’ as a form of autonomous demand-responsive transport. South East Queensland, Australia, was selected as the testbed. In this case study, relationships between perceptions, attitudes, and usage intention were examined by employing a partial least squares structural equation modeling method. The results support the basic technology acceptance model casual relationships that correspond with previous studies. Although the direct effects of perceived relative advantages and perceived service quality on usage intention are not significant, they could still affect usage intention indirectly through the attitude factor. Conversely, perceived risks are shown to have no association with perceived usefulness but can negatively impact travelers’ attitudes and usage intention toward autonomous shuttle buses. The research findings provide implications to assist policymakers, transport planners, and engineers in their policy decisions and system plans as well as achieving higher public acknowledgment and wider uptake of autonomous demand-responsive transport technology solutions.

This paper presents research on a real-time bus-holding control strategy that minimizes passenger waiting time. This bus-holding strategy forces buses to hold at stations for a while after a passenger exchange is finished. A mathematical model is proposed to determine the optimal holding time. Both onboard and on-station passenger waiting times have been taken into account. Given the real-time nature of the problem, a heuristic method based on gradient descent algorithms was developed. The proposed control strategy was evaluated by using data derived from a shuttle bus rapid transit (BRT) line in the city of Mashhad, Iran. The BRT line was simulated and calibrated by available empirical and real-time data from the automatic vehicle location and automatic passenger counting systems. The results indicate that the proposed bus-holding strategy reduces total passenger waiting time by 8.65%.

The first and last mile of a trip has been used to describe passenger travel with regards to getting to and from transit stops/stations. Solving the first and last mile (FMLM) problem extends the access to transportation systems and enlarges the number of passengers from a remote community, such as rural areas. The FMLM problem has been addressed in different public transit contexts, mainly within urban areas. However, it is also an important part of the journey in an intercity trip; yet, limited research efforts have been undertaken to examine the FMLM problem that intercity passenger train riders face. This paper fills in this gap and further, aims to identify the best strategies that could serve as a FMLM solution for short distance intercity passenger rail service (i.e., corridors that are less than 750 miles long according to the Passenger Rail Improvement and Investment Act, 2008). The Hoosier State Train (HST) service, a short-distance intercity passenger rail that connects Chicago and Indianapolis four days a week, was chosen as a case of study. The HST has four intermediate stops located in Indiana. For some of those intermediate stops HST is the only intercity public transit service offered to reach either Chicago or Indianapolis. In order to explore opportunities to enhance the HST ridership, an on-board survey was conducted in November and December 2016. The findings of this survey suggested that there are riders who travel from counties further away from a county with a station to reach and complete their journey on the train. Moreover, it was found that most of the respondents drove or rented a car, or were dropped off to reach a train station in Indiana. Unlike the results from the Chicago station, the majority of riders boarding the train from one of the Indiana stations did not use ridesharing services or public transportation. These findings suggest that there is a possible gap into the FMLM travel options for intercity rail riders and alternative options to fill this gap should be considered. This paper discusses the case study results of an accessibility analysis aiming to identify the areas in need of first/last mile service where there are no public transportation services and/or it is costly to reach a station from a desired origin. To that end, a cost surface for the different modes available in the area of study was created to determine the average travel cost to the nearest station. The analysis was carried out in ArcGIS using origin-destination data from the on-board survey, transportation network information from the U.S. Bureau Transportation Statistics, and general transit feed specification (GTFS) data. Subsequently, some of the best strategies identified were modeled around the station (e.g., shuttle buses to/from the station) in order to examine how the accessibility would increase after a strategy implementation. The results of this study may have far-reaching implications for planning strategies that can enhance access to the train stations. Finally, the FMLM strategies could assist intercity passenger rail service providers attract a larger number of passengers.

Public transit ridership in California declined in the five years before the pandemic of 2020–21 and dropped significantly further after the pandemic began. A sharp downward step in the level of transit boarding occurred after February 2020, and continues to the date of this report as a result of the public-health guidance on social distancing, expanded work-at-home, and a travel mode shift from public transit to private cars. A critical issue has come to the foreground of public transportation policy, namely, how to increase the quality and geographic reach of transit service to better serve the essential trips of mobility disadvantaged citizens who do not have access to private vehicle travel. The research focus of this report is an examination of the circumstances where fixed route bus route service could cost-effectively be replaced by on-demand microtransit, with equivalent overall zone-level efficiency and a higher quality of complete trip service. Research methods were reviews of documented agency experience, execution of simple simulations, and sketch-level analysis of 2019 performance reported in the National Transit Database. Available evidence is encouraging and suggestive, but not conclusive. The research found that substitutions of flexible microtransit for fixed route buses are already being piloted across the U.S., with promising performance results. The findings imply that action steps could be taken in California to expand and refine an emphasis on general purpose microtransit in corridors and zones with a relatively high fraction of potential travelers who are mobility disadvantaged, and where traditional bus routes are capturing fewer than 15 boardings per vehicle hour. To be sufficiently productive as fixed route replacements, microtransit service technologies in the same or larger zones need to be capable of achieving vehicle boardings of five per hour, a challenge worth addressing with technology applications. Delivery of microtransit service can be undertaken through contracts with a growing set of private sector firms, which are developing processes to merge general purpose customers with those now assigned to ADA-required paratransit and Medi-Cal-supported non-emergency medical transport.