Demand Responsive Transit Service Research Articles

Critical street links for demand responsive feeder transit services

This paper presents a methodology to identify and locate critical links in a grid street network system for feeder transit services. A ‘critical’ link can be defined as a link that—when eliminated from or appended to an existing network—would cause the largest change in the network connectivity and consequently in the transit performance. The most significant contribution of this study is to present a simple analytical approach to locating the critical link(s) for a grid street network system of any size with uniform passenger demand across the service area. The distance between demands points have been used as the basic measure of impedance in the final derived closed-form equations. Easily computable formulas for identifying the critical links have been validated by simulation analyses with the street network system from the City of St. Joseph, Missouri. Useful insights from the analytical derivations and simulation results indicate a monotonic decrease in link criticality when moving from the centrally located links to those located at the periphery in a grid street network system.

A model for estimating the optimal cycle length of demand responsive feeder transit services

The general lack of first/last mile connectivity is one of the main challenges faced by today’s public transit. One of the possible actions towards a solution to this problem is the planning, design and implementation of efficient feeder transit services. This paper develops an analytical model which allows for an easy computation of near optimal terminal-to-terminal cycle length of a demand responsive feeder service to maximize service quality provided to customers, defined as the inverse of a weighted sum of waiting and riding times. The model estimates the recommended cycle length by only plugging in geometrical parameters and demand data, without relying on extensive simulation analyses or rule of thumbs. Simulation experiments and comparisons with real services validate our model, which would allow planners, decision makers and practitioners to quickly identify the best feeder transit operating design of any given residential area.

A new street connectivity indicator to predict performance for feeder transit services

This paper defines a novel street Connectivity Indicator (C.I.) to predict transit performance by identifying the role that street network connectivity plays in influencing the service quality of demand responsive feeder transit services. This new C.I. definition is dependent upon the expected shortest path between any two nodes in the network, includes spatial features and transit demand distribution information and is easy to calculate for any given service area. Simulation analyses over a range of networks have been conducted to validate the new definition. Results show a desirable monotonic relationship between transit performance and the proposed C.I., whose values are directly proportional and therefore good predictors of the transit performance, outperforming other available indicators, typically used by planners.

수요대응형 교통수단 시뮬레이션 방안: Real-Time Shared-Taxi 적용예시

Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.

A Transportation Model For Demand Responsive Fleet Operation In A Manufacturing Firm

We study the problem of determining the number of vehicles needed to provide a demand responsive transit service with a predetermined quality for the user in terms of waiting time at the stops and maximum allowed detour. We propose a probabilistic model that requires only the knowledge of the distribution of the demand over the service area and the quality of the service in terms of time windows associated with pickup and delivery nodes. This methodology can be much more effective and straight forward compared to a simulation approach whenever detailed data on demand patterns are not available. Computational results under a fairly broad range of test problems show that the model can provide an estimation of the required size of the fleet in several different scenarios.

Innovative on-demand bus system in Japan

The innovative on-demand bus system is developed and the result of field tests shows that the system is valid for different city types. On-demand is a demand-responsive transit service where the vehicles transport users after they reserve their seats, and the vehicle does not move if there is no reservation. On-demand bus is an existing technology and it runs all over the world, but the high running cost is a problem. The aim of the developed system is practical introduction of the system from cost viewpoint. Local government can start the service in low cost with cloud computing technology. In order to build up the cloud computing system, schedule calculation system and the communication device in the car are required. In order to validate the developed system, simulation and field test are held. The result of computer simulation shows that the developed calculation algorithm works well as designed. The result of field test shows that the on-demand bus service in three different type cities are provided through the Internet with cloud computing technology and it is evaluated to enable new public transportation system.

A methodology for comparing distances traveled by performance-equivalent fixed-route and demand responsive transit services

Public transport systems are confronted by the need to improve their economic effectiveness in order to meet customer requirements at acceptable costs for transit providers, which are often heavily subsidized. Our goal is to understand how the organizational form of the transit system impacts on system productivity. Our methodology consists of comparing performance in terms of distance traveled of two competing transit services, a traditional fixed-route and a demand responsive service, while ensuring a comparable service to the same set of customers. We consider several scenarios, which depend on the road network, service quality level, and demand density. According to our findings, demand responsive transit services perform better for high-quality service levels and low demand density scenarios.

A simulation study of demand responsive transit system design

In this paper we study the impact on productivity of specific operating practices currently used by demand responsive transit (DRT) providers. We investigate the effect of using a zoning vs. a no-zoning strategy and time-window settings on performance measures such as total trip miles, deadhead miles and fleet size. It is difficult to establish closed-form expressions to assess the impact on the performance measures of a specific zoning practice or time-window setting for a real transportation network. Thus, we conduct this study through a simulation model of the operations of DRT providers on a network based on data for DRT service in Los Angeles County. However, the methodology is quite general and applicable to any other service area. Our results suggest the existence of linear relationships between operating practices and performance measures. In particular we observe that for each minute increase in time-window size the service saves approximately 2 vehicles and 260 miles driven and that a no-zoning strategy is able to satisfy the same demand by employing 60 less vehicles and driving 10,000 less total miles with respect to the current zoning strategy.

Emissions of demand responsive services as an alternative to conventional transit systems

The environmental performance of public transport plays a key role in improving air quality in urban areas. An important way of improving existing transit services is to use innovative propulsive systems; however, this needs considerable financial resources that are not always available. Here we assess how the organizational form of the transit system may impact the environment relying on a new methodology that permits comparisons in terms of distance traveled between a traditional fixed-route and a demand responsive transit service. We apply an emission model to find the least polluting transit system under a broad range of scenarios with different road networks, service quality levels and demand densities. Results indicate that demand responsive transit services minimize emissions for high quality service level and low demand density scenarios. Furthermore, the possibility of employing smaller vans with lower emission factors guarantees additional substantial benefits in terms of atmospheric pollution for demand responsive transit services, thereby giving them a competitive advantage in virtually every case.

A model for the fleet sizing of demand responsive transportation services with time windows

We study the problem of determining the number of vehicles needed to provide a demand responsive transit service with a predetermined quality for the user in terms of waiting time at the stops and maximum allowed detour. We propose a probabilistic model that requires only the knowledge of the distribution of the demand over the service area and the quality of the service in terms of time windows associated of pickup and delivery nodes. This methodology can be much more effective and straightforward compared to a simulation approach whenever detailed data on demand patterns are not available. Computational results under a fairly broad range of test problems show that our model can provide an estimation of the required size of the fleet in several different scenarios.

Emerging Techniques for Urban Transportation Planning

Despite several decades of intense effort, urban transportation planning is in its infancy of development and refinement, as evidenced by the fast pace of new techniques and methodologies being proposed and developed. In this series of two special issues on urban transportation planning, the first issue @Journal of Urban Planning and Development, 128~4!, 2002# focused on reviews of recent methodological advances. This second issue covers emerging techniques that extend the boundries beyond the traditional four-step planning methodology. Some of these techniques are drawn from other fields of studies. Others introduce new dimensions to reconsider the problem. All in all, these approaches open up new possibilities and dimensions as well as make planning procedures more robust, thereby enabling the planning results to be applicable to a wider range of scenarios and for the longerterm future. Six papers are contained in this special issue. Drawing from business and organizational scenario planning techniques, the paper by Zegras, Sussman, and Conklin, ‘‘Scenario Planning for Strategic Regional Transportation Planning,’’ proposes a scenarioplanning framework for regional transportation planning. The study reviews the context of scenario planning for regional transportation planning, illustrates the approach through application to the Houston, Texas, metropolitan area, and concludes with findings, lessons learned, and future potentials and refinements of the approach. To improve the analysis of multicommodity demand and traffic patterns of a city with multiple regional activity centers, the paper by Wong, Zhou, Lo, and Yang, ‘‘Improved Solution Algorithm for the Multicommodity Continuous Distribution and Assignment Model’’ develops a new combined distribution and assignment model. A unique feature of this approach is that the dispersion of demand is modeled as a continuous function over space, in contrast to the traditional approach where demands are lumped at origin nodes or centroids. The study then proposes an efficient algorithm to solve the formulation. In the third paper, ‘‘Balance of Car Ownership under User Demand and Road Network Supply Conditions—Case Study in Hong Kong,’’ Tam and Lam propose a new concept for estimating car ownership. It considers the interactions between user demands and road network supply conditions, thereby factoring in the congestion effect to the estimation of car ownership on top of the traditional socioeconomic characteristics of the population. The paper then illustrates the approach through a case study in Hong Kong. Understanding users’ routing strategies is important, as it will lead to the design of more robust transportation networks. The paper by Bell, ‘‘Games, Heuristics, and Risk Averseness in Vehicle Routing Problems,’’ develops an approach for vehicle routing in networks with uncertain travel times. The study focuses on the case of freight carriers, wherein the dispatcher seeks a riskaverse routing and scheduling strategy. The writer formulates the problem with a game theoretic approach and solves it with a method of successive averages scheme. For low-density urban developments that render conventional transit services less competitive or cost-effective, perhaps only demand-responsive transit services are viable, if any at all. The paper by Khattak and Yim, ‘‘Traveler Response to Innovative Personalized Demand-Responsive Transit in the San Francisco Bay Area,’’ investigates the market for Personalized Demand Responsive Transit ~PDRT!. The study attempts to understand travelers’ willingness to use and pay for PDRT based on focus group meetings and a computer-assisted telephone survey. Such results are indicative for the planning of demand-responsive transit services. Finally, the paper by Ceder, ‘‘New Urban Public Transportation Systems: Initiatives, Effectiveness, and Challenges,’’ examines the major elements and challenges for the introduction of a new or an improved public transportation system. Drawing upon experiences in Europe and North America, the paper reviews the current state of practice and covers issues related to the use of public transportation services. The paper concludes by illustrating the case of the city of Auckland, New Zealand. These papers illustrate the range of research directions to improve the urban transportation planning process. Some focus on the methodological framework, others on broader and more connected considerations, better understanding of travelers’ choices, and issues that ought to be carefully considered in new initiatives or improvement schemes. We trust that, collectively, these two special issues serve to broaden the perspective on the new approaches for urban transportation planning. It is our hope that they will inspire and stimulate new research initiatives and efforts in this still evolving field.

Traveler Response to Innovative Personalized Demand-Responsive Transit in the San Francisco Bay Area

Urban sprawl makes conventional transit less competitive and points to the need for more innovative and flexible demand-responsive transit systems in the future. To increase their efficiency, such systems can take advantage of the emerging advanced public transportation systems technologies, e.g., vehicle location and information systems. However, little is known about how consumers might respond to such systems and what they desire. This paper explores the demand for a consumer-oriented Personalized Demand-Responsive Transit (PDRT) service in the San Francisco Bay Area. Such a system could provide services to the traveling public for journeys to work and to nonwork destinations. Results from six focus group meetings and a computer-assisted telephone survey of commuters and noncommuters are reported. While about 60% of those surveyed were willing to consider PDRT as an option, about 12% reported that they were “very likely” to use PDRT (\iN = 1,000). Many were willing to pay for the service and valued highly the flexibility in scheduling the service. Spatial analysis of the survey responses suggests localities where a PDRT may be field-tested.

Recruitment, Selection, and Retention of Personnel at North Carolina Community Transportation Systems: Findings and Recommendations from a Study

The hiring and the retention of personnel have been a long-standing issue in the public transportation industry. This involves finding and recruiting potential employees, selecting and hiring the most qualified candidates, training and developing employees, monitoring performance and retaining employees, and reducing excessive turnover and absenteeism. While human resources topics have typically been investigated at urban transit systems operating fixed-route services, hiring and retention have not been studied extensively at smaller rural transit systems operating demand-responsive transit services. This research focused on such rural systems and on the various factors that most impact on the issue at nine North Carolina community transportation systems. This effort included various human resources policies and practices such as recruiting, selecting, compensating, training, evaluating, and motivating. Practices at the nine case study systems and recommendations to improve policies and procedures are described.