An optimization approach to resolve activity scheduling conflicts in ADAPTS activity-based model

Activity conflict resolution as the core of scheduling process in activity-based modeling is a challenging step because the activity diary databases mostly report the outcome of the scheduling decisions and often fail to capture key factors influencing the resolution process itself. Consequently, most activity-based frameworks ignore modeling this process by using either predefined set of activity patterns or priority-based assumptions to schedule daily activities and prevent conflict occasions. ADAPTS is one of the few activity-based models that attempts to simulate the process of activity scheduling and resolve the conflicts as they occur. This paper advances the current rule-based conflict resolution model of ADAPTS by implementing an advanced and flexible non-linear optimization model. A set of linear optimization sub-models is then proposed that together perform the same task as the non-linear model, however they are much easier to implement and maintain, while fast to run and flexible to extend. The proposed approach defines an objective function, which aims to minimize the extent of changes in timing and duration of conflicting activities, while fitting them in the schedule. Comparing performance of the proposed model with TASHA scheduler and former resolution module of ADAPTS using CHASE scheduling process data reveals significant improvement in fitting the newly planned activities in the schedules with the minimal modifications in the timing and duration of activities.     

Measuring the satisfaction of multimodal travelers for local transit services in different urban contexts

The importance of measuring customer satisfaction for a public transport service is apparent, even beyond more immediate marketing purposes. The present paper shows how satisfaction measures can be exploited to gain insights on the relationship between personal attitudes, transit use and urban context. We consider nine satisfaction measures of urban transit services, as expressed by a representative sample of Italian multimodal travelers (i.e. users of both private cars and public transport). We use correlations and correspondence analyses to show if and how each attribute is related to the levels of use of public transport, and how the relationship is affected by the urban context. Then we apply a recently developed method to combine ordinal variables into one score, by adapting it to work with large samples and with satisfaction measures which have a neutral point in the scale (i.e. “neither satisfied nor dissatisfied”). The resulting overall satisfaction levels and frequency of use were not correlated in our sample. We also found the highest satisfaction levels in smaller towns and the lowest ones in metropolitan cities. Since we focus on multimodal travelers, an interpretation paradigm is proposed according to which transit services must be well evaluated by car drivers in smaller towns in order to be considered a real alternative to cars. On the other hand, transit is more competitive on factual elements in larger cities, so that it can still be used by drivers, even if it is not very well evaluated.     

An agent-based multimodal simulation model for capacity planning of a cross-border transit facility

Cross-border transit facilities constitute major public investment, and thus must serve the long-term needs of the communities, such as providing access to schools and businesses, contributing to a shared regional culture and lifestyle, fostering international trade, and supporting jobs for the region’s residents. Numerous studies have been conducted to evaluate the economic implications of vehicular flow delays at border crossings, however none of the studies focused on assessing cross-border flow of bus passengers and pedestrians. Since pedestrians are considered to be autonomous, intelligent, and perceptive, it is a challenging task to predict pedestrian movement and behavior in comparison to vehicular flows which follow a specific set of traffic rules. This paper presents a multiagent based multimodal simulation model to evaluate the capacity and performance of a cross-border transit facility. The significance of this research is the use of dynamic mode choice functionality in the model, which allows an individual person to make instantaneous choices between available modes of transportation. The scope of interest of the paper is limited to simulating access interface, circulation areas, ancillary and processing facilities. The developed model was calibrated to ensure realistic performance, and validated against specific performance criteria such as throughput per processing facility. In order to demonstrate the applicability of the developed simulation model, capacity and operational planning of a pedestrian transit facility was performed. The relative performance of alternative design or configuration was evaluated using the level of service criteria. Lastly, the effectiveness of each proposed capacity or operational improvement strategy was compared to the “do-nothing” scenario.     

Modeling competitive multi-modal transit services: a nested logit approach

In metropolitan areas where multi-modal trips are common, modeling the combined-mode choices of travelers, and the strategic interactions between the private service operators are important issues. This study developed a novel network approach, designated as state-augmented multi-modal (SAM) network, to explicitly consider transfer behaviors and non-linear fare structures. To overcome the independence of irrelevant alternatives (IIA) assumption associated with the standard logit approach, we integrated the SAM network with the nested logit (NL) approach. Specifically, we developed a three-level NL choice model to deal with the complex and inter-related decisions in a multi-modal network: the first level focuses on combined-mode choice, the second on transfer location choice, and the third on route choice. Using this NL SAM network as a platform, we examined the effect of fare competition on company profitability as well as on overall network congestion. A case study of the ground transportation system connecting the Hong Kong International Airport to the downtown area is provided to illustrate the approach.     

An activity-based approach of investigating travel behaviour of older people

The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.     

Evaluating the impacts of shared automated mobility on-demand services: an activity-based accessibility approach

Transportation - Autonomous vehicle (AV) technologies are under constant improvement with pilot programs now underway in several urban areas worldwide. Modeling and field-testing efforts are...     

An AI-based approach for transit route system planning and design

We present an AI-based solution approach to the transit network design problem (TNDP). Past approaches fall into three categories: optimization formulations of idealized situations, heuristic approaches, or practical guidelines and ad hoc procedures reflecting the professional judgement and practical experience of transit planners. We discuss the sources of complexity of the TNDP as well as the shortcomings of the previous approaches. This discussion motivates the need for AI search techniques that implement the existing designer's knowledge and expertise to achieve better solutions efficiently. Then we propose a hybrid solution approach that incorporates the knowledge and expertise of transit network planners and implements efficient search techniques using AI tools, algorithmic procedures developed by others, and modules for tools implemented in conventional languages. The three major components of the solution approach are presented, namely, the lisp-implemented route generation design algorithm (RGA), the analysis procedure TRUST (Transit Route Analyst), and the route improvement algorithm (RIA). An example illustration is included.     

A network equilibrium approach for modelling activity-travel pattern scheduling problems in multi-modal transit networks with uncertainty

An understanding of the interaction between individuals’ activities and travel choice behaviour plays an important role in long-term transit service planning. In this paper, an activity-based network equilibrium model for scheduling daily activity-travel patterns (DATPs) in multi-modal transit networks under uncertainty is presented. In the proposed model, the DATP choice problem is transformed into a static traffic assignment problem by constructing a new super-network platform. With the use of the new super-network platform, individuals’ activity and travel choices such as time and space coordination, activity location, activity sequence and duration, and route/mode choices, can be simultaneously considered. In order to capture the stochastic characteristics of different activities, activity utilities are assumed in this study to be time-dependent and stochastic in relation to the activity types. A concept of DATP budget utility is proposed for modelling the uncertainty of activity utility. An efficient solution algorithm without prior enumeration of DATPs is developed for solving the DATP scheduling problem in multi-modal transit networks. Numerical examples are used to illustrate the application of the proposed model and the solution algorithm.     

Dynamic transit scheduling under efficiency constraints

The problem of dynamic transit scheduling is addressed, and a method for transient and steady-state solutions is developed. The dynamic demand-supply formulation employed is based on previously calibrated disaggregate demand specifications. The existence and feasibility of solutions are examined, and stability conditions are derived. Numerical examples for both urban and rural conditions are given. The new methodology does not require time-series endogenous data but only initial conditions to provide long- or short-term scheduling plans. Futhermore, it takes into account passenger demand fluctuations and explicitly deals with management responsiveness and time lags in implementing scheduling decisions. Owing to its dynamic nature the methodology can be used as a design tool in transit scheduling and for assessing the effects of time-varying exogenous events such as gasoline price fluctuations, transport budget restrictions and other contingencies.     

Passenger-demands-oriented train scheduling for an urban rail transit network

This paper considers the train scheduling problem for an urban rail transit network. We propose an event-driven model that involves three types of events, i.e., departure events, arrival events, and passenger arrival rates change events. The routing of the arriving passengers at transfer stations is also included in the train scheduling model. Moreover, the passenger transfer behavior (i.e., walking times and transfer times of passengers) is also taken into account in the model formulation. The resulting optimization problem is a real-valued nonlinear nonconvex problem. Nonlinear programming approaches (e.g., sequential quadratic programming) and evolutionary algorithms (e.g., genetic algorithms) can be used to solve this train scheduling problem. The effectiveness of the event-driven model is evaluated through a case study.     

Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data

This paper studies electric vehicle charger location problems and analyzes the impact of public charging infrastructure deployment on increasing electric miles traveled, thus promoting battery electric vehicle (BEV) market penetration. An activity-based assessment method is proposed to evaluate BEV feasibility for the heterogeneous traveling population in the real world driving context. Genetic algorithm is applied to find (sub)optimal locations for siting public charging stations. A case study using the GPS-based travel survey data collected in the greater Seattle metropolitan area shows that electric miles and trips could be significantly increased by installing public chargers at popular destinations, with a reasonable infrastructure investment.     

Estimating multimodal transit ridership with a varying fare structure

This paper studies public transport demand by estimating a system of equations for multimodal transit systems where different modes may act competitively or cooperatively. Using data from Athens, Greece, we explicitly correct for higher-order serial correlation in the error terms and investigate two, largely overlooked, questions in the transit literature; first, whether a varying fare structure in a multimodal transit system affects demand and, second, what the determinants of ticket versus travelcard sales may be. Model estimation results suggest that the effect of fare type on ridership levels in a multimodal system varies by mode and by relative ticket to travelcard prices. Further, regardless of competition or cooperation between modes, fare increases will have limited effects on ridership, but the magnitude of these effects does depend on the relative ticket to travelcard prices. Finally, incorrectly assuming serial independence for the error terms during model estimation could yield upward or downward biased parameters and hence result in incorrect inferences and policy recommendations.     

Development of multimodal performance measures for transit systems in New York State

The New York State Department of Transportation was required to certify as to the economy and efficiency of transit operators participating in the State's public transportation operating assistance program. This paper describes the efforts undertaken to meet this mandate.Discussed are past efforts to link performance measures to funding programs; reasons for modifying measures which had been used in previous efforts; and some of the problems and issues raised by the use of such criteria. The paper identifies 15 performance measures being used by New York State in its evaluations, the actual ranges encountered in the transit operations being funded through the state program, and tentative acceptable and desirable levels of those measures which the Transportation Department is using in its evaluation. The role these measures play in the state's operating assistance policy decision process is also described.     

An actuary method for the estimation and comparison of urban bus transit cost of services

This paper presents a new cost allocation method developed for estimating the fully-allocated costs of the excess peak hour bus transit service provided by two public transit systems. The estimates were produced for the explicit purpose of carrying out a realistic comparison of these costs and the costs of the potential provision of the same service by private operators. The method utilizes the same service data for the analysis. The pragmatic estimation of the fully allocated costs of service by the public and private sectors enables a more accurate estimation of potential cost savings. Sensitivity analysis was also performed using the same costing procedure to determine the range of cost savings that are feasible in a competitive contract arrangement of private sector providers. The new method separates costs of the direct provision of service from other indirect costs and thus facilitates the identification of each cost item and its significance in comparative cost estimates.     

Estimation of origin‐destination matrices for a multimodal public transit network

This paper presents a procedure for the estimation of origin‐destination (O‐D) matrices for a multimodal public transit network. The system consists of a number of favored public transit modes that are obtained from a modal split process in a traditional four‐step transportation model. The demand of each favored mode is assigned to the multimodal network, which is comprised of a set of connected links of different public transit modes. An entropy maximization procedure is proposed to simultaneously estimate the O‐D demand matrices of all favored modes, which are consistent with target data sets such as the boarding counts and line segment flows that are observed directly in the network. A case study of the Hong Kong multimodal transit network is used to demonstrate the effectiveness of the proposed methodology.     

An evaluation of activity-based travel analysis

This paper is a review and assessment of the contributions made by activity-based approaches to the understanding and forecasting of travel behavior. In their brief history of approximately a decade, activity-based analyses have received extensive interest. This work has led to an accumulation of empirical evidence and new insights and has made substantial contributions toward the better understanding of travel behavior. However, practical applications of the approach in transportation planning and policy development have been scarce. Based on an analysis of the inherent characteristics of the activity-based approach, a review of recent (after the 1981 Oxford conference) developments, and a synthesis of the findings from past empirical studies, this study attempts to evaluate the contribution made by activity-based analyses and determine the reasons for the limited practical application. Recommendations are made for the future development of activity-based analysis as a science of travel behavior and as a tool in the practice of transportation planning and policy development.     

Learning to use transit services: adapting to unfamiliar transit travel

Transportation - Travel behavior change has become an area of interest in many cities around the world, particularly to encourage people to change from car use to transit use. Previous research...     

Fleet scheduling and dispatching for demand-responsive passenger services

This paper describes a software system designed to manage the deployment of a fleet of demand-responsive passenger vehicles such as taxis or variably routed buses. Multiple modes of operation are supported both for the fleet and for individual vehicles. Booking requests can be immediate (i.e. with zero notice) or in advance of travel. An initial implementation is chosen for each incoming request, subject to time-window and other constraints, and with an objective of minimising additional travel time or maximising a surrogate for future fleet capacity. This incremental insertion scheme is supplemented by post-insert improvement procedures, a periodically executed steepest-descent improvement procedure applied to the fleet as a whole, and a “rank-homing” heuristic incorporating information about future patterns of demand. A simple objective for trip-insertion and other scheduling operations is based on localised minimisation of travel time, while an alternative incorporating occupancy ratios has a more strategic orientation. Apart from its scheduling functions, the system includes automated vehicle dispatching procedures designed to achieve a favourable combination of customer service and efficiency of vehicle deployment. Provision is made for a variety of contingencies, including travel slower or faster than expected, unexpected vehicle locations, vehicle breakdowns and trip cancellations. Simulation tests indicate that the improvement procedures yield substantial efficiencies over more naı̈ve scheduling methods and that the system will be effective in real-time applications.     

Integrated transit services for minimum cost operation considering heterogeneous demand

Abstract

In large metropolitan areas, public transit is a major mode choice of commuters for their daily travel, which has an important role in relieving congestion on transportation corridors. The purpose of this study is to develop a model which optimizes service patterns (SPs) and frequencies that yield minimum cost transit operation. Considering a general transit route with given stops and origin-destination demand, the proposed model consists of an objective total cost function and a set of constraints to ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is provided to demonstrate the effectiveness of the developed model, in which the demand and facility data of a rail transit route were given. Results show that the proposed model can be applied to optimize integrated SPs and headways that significantly reduce the total cost, while the resulting performance indicators are generated.     

Exploring the correlation between ride-hailing and multimodal transit ridership in toronto

Transportation - Ride-hailing (RH) services have been growing rapidly and gaining popularity worldwide. However, many transit agencies are experiencing ridership stagnation or even decline....