GIS-based transit trip allocation methods converting stop-level boarding and alighting trips into TAZ trips

ABSTRACT

This study introduces a framework to improve the utilization of new data sources such as automated vehicle location (AVL) and automated passenger counting (APC) systems in transit ridership forecasting models. The direct application of AVL/APC data to travel forecasting requires an important intermediary step that links stops and activities – boarding and alighting – to the actual locations (at the traffic analysis zone (TAZ) level) that generated/attracted these trips. GIS-based transit trip allocation methods are developed with a focus on considering the case when the access shed spans multiple TAZs. The proposed methods improve practical applicability with easily obtained data. The performance of the proposed allocation methods is further evaluated using transit on-board survey data. The results show that the methods can effectively handle various conditions, particularly for major activity generators. The average errors between observed data and the proposed method are about 8% for alighting trips and 18% for boarding trips.     

Effects of household structure and selected travel characteristics on trip chaining

This paper analyzes trip chaining, focusing on how households organize non-work travel. A trip chaining typology is developed using household survey data from Portland, Oregon. Households are organized according to demographic structure, allowing analysis of trip chaining differences among household types. A logit model of the propensity to link non-work trips to the work commute is estimated. A more general model of household allocation of non-work travel among three alternative chain types — work commutes, multi-stop non-work journeys, and unlinked trips — is also developed and estimated. Empirical results indicate that the likelihood of linking work and non-work travel, and the more general organization of non-work travel, varies with respect to household structure and other factors which previous studies have found to be important. The effects of two congestion indicators on trip chaining were mixed: workers who commuted in peak periods were found to have lower propensity to form work/non-work chains, while a more general congestion indicator had no effect on the allocation of non-work trips among alternative chains.     

Uncertainty modeling for bus selection and allocation in a private transportation system

ABSTRACT

This paper describes the development of a probabilistic formulation that provides global optimum selection and allocation of a fleet of buses in a private transportation system of an organization where a third party is hired to provide transportation for its employees and their dependents. In this private transportation system, a fleet of buses is to be selected and allocated to serve employees and their independents on different prescheduled trips along different routes from the organization’s headquarters and residential compound where round-trip times of scheduled trips are subject to uncertainty due to random delays. We propose a probabilistic approach based on 0-1 integer programming for the selection and allocation to determine the optimal number and size of buses assigned to a set of prescheduled trips in a particular time interval. Examples and a case study are presented to illustrate the applicability and suitability of the proposed approach.     

Spatial transferability assessment of a composite walkability index: The Pedestrian Index of the Environment (PIE)

This paper analyzes the transferability of a composite walkability index, the Pedestrian Index of the Environment (PIE), to the Greater Montréal Area (GMA). The PIE was developed in Portland, Oregon, and is based on proprietary data. It combines six urban form variables into a score ranging from 20 to 100. The measure introduces several methodological refinements which have not been applied concurrently in previous efforts: a wide coverage of the different dimensions of the urban form, together with the use of a distance-based decay function and modelling-based weighing of the variables.This measure is applied to the GMA using local data in order to evaluate the feasibility of its transfer (the possibility of locally replicating the measure). It is then included in a series of mode choice models to assess its transferability (the capacity of the measure to describe walkability and predict mode choice in another urban area). The models, segmented by trip distance or trip purpose, are estimated and validated against observed trip data from the 2013 Origin-Destination survey.Significant positive correlation is found between the PIE and the choice of walking for short trips, for all purposes as well as for four specific trip purposes. The inclusion of the PIE also improves the accuracy of the modelling process as well as the prediction of the choice of walking for short trips. The PIE can therefore be used in the GMA, and potentially in other metropolitan areas, to improve the modelling of travel behavior for short trips.     

Allocating Revenue Risk in Transport Infrastructure Public Private Partnership Projects: How it Matters

Abstract

Transport infrastructure public private partnership (PPP) projects are very diverse and complex in nature not only because of their mode-specific intricacies but also because of their inherent economic characteristics that relate to the scope of involvement of the private sector in the project, the large sunk costs incurred, and ultimately, the competition to which these projects are exposed. The allocation of revenue risk is of paramount importance for the successful implementation of such projects and a sub-optimal allocation may lead to project structuring that is unnecessarily expensive and vulnerable to failure. At the same time, the revenue risk depends critically on the remuneration model used (user-based versus budget-based) and may, in turn, take the form of demand risk, counterparty risk or combinations of the two. This review explores the issues related to revenue risk allocation for transport infrastructure PPP projects. Overarching principles for the allocation of revenue risk that transcend mode-specificity are identified and compared to case studies generated in the context of the COST Action TU1001. The results show that theory and practice are divergent, leading to sub-optimal structuring and exposing projects to potential failure.     

Approximate queueing models for analyzing harbor terminal operations

The purpose of this paper is to present approximate queueing models to help assess the impacts of tug services on congested harbor terminals. The models are intended for harbors in which tug shortages are rare. A congested harbor terminal is modelled as a queueing system with m identical tugs (servers) and n identical berths (customers), and with general probability distributions of tug service time and berth cargo-handling time. The distribution of the number of berths in the system, a basic element to analyze the system performance, was established for two cases. For large m, the distribution was approximated by a binomial model and the respective accuracy tested. For small m, an approximate model for this distribution was developed. Particular emphasis was given to developing explicitly the probability of having one berth in queue and establishing the remaining probabilities of the distribution approximately. The model for small m was validated by means of simulation for various cases of harbor terminal operations exhibiting different ranges of the coefficient of variation of tug service time. The models were found to be reasonably accurate within a certain range covering situations in which tug shortages are in the order of 10% of the time or less.     

Liner container seasonal shipping revenue management

This paper proposes a liner container seasonal shipping revenue management problem for a container shipping company. For a given weekly multi-type shipment demand pattern in a particular season, the proposed problem aims to maximize the total seasonal shipping profit by determining the number of multi-type containers to be transported and assigned on each container route, the number of containerships deployed on each ship route, and the sailing speed of containerships on each shipping leg subject to both the volume and capacity constraints of each containership. By adopting the realistic bunker consumption rate of a containership as a function of its sailing speed and payload (displacement), we develop a mixed-integer nonlinear programing with a nonconvex objective function for the proposed liner container seasonal shipping revenue management problem. A tailored branch and bound (B&B) method is designed to obtain the global ε-optimal solution of the model. Numerical experiments are finally conducted to assess the efficiency of the solution algorithm and to show the applicability of the developed model.     

Network models for seat allocation on flights

This paper examines the problem of proper (optimal) control over the seat allocation on flights. Given a heterogeneous fleet of aircraft types, multi-leg flights, a number of different passenger categories, and cancelations, an airline's objective is to devise an effective system which aids in setting the seat allocation targets for each category of passengers on each flight. This issue is analyzed by a number of authors in the context of economic, simulation based, probabilistic, and mathematical programming studies. We present an attempt to address this problem from the systems prospective emphasizing characteristics such as: passenger cancelations, multi-leg flights, and rolling tactical planning time horizon. Starting from a very simple network flow models for a single flight with a number of intermediate stops, a number of progressively complex models are presented. The airline flights and the seat allocation system are represented as a generalized network flow model (with gains/losses on arcs) with the objective of flow maximization (profit maximization). This modelling approach does not claim to replace the seat allocation approaches presented in Alstrup et al. (1985), Mayer (1976), Richter (1982), Simpson (1985a), and Wang (1983), but rather construct seat allocations utilizing some of those referenced schemes in a parameter setting mode for a large network model. The objective of this paper is not to report on computational experiments, but to present a modeling approach which seems to be promising, if somewhat speculative.     

An eigenmodel for iterative line planning,timetabling and vehicle scheduling in public transportation

Planning a public transportation system is a multi-objective problem which includes among others line planning, timetabling, and vehicle scheduling. For each of these planning stages, models are known and advanced solution techniques exist. Some of the models focus on costs, others on passengers’ convenience. Setting up a transportation system is usually done by optimizing each of these stages sequentially.In this paper we argue that instead of optimizing each single step further and further it would be more beneficial to consider the whole process in an integrated way. To this end, we develop and discuss a generic, bi-objective model for integrating line planning, timetabling, and vehicle scheduling. We furthermore propose an eigenmodel which we apply for these three planning stages and show how it can be used for the design of iterative algorithms as heuristics for the integrated problem. The convergence of the resulting iterative approaches is analyzed from a theoretical point of view. Moreover, we propose an agenda for further research in this field.     

Beyond tele-substitution: disaggregate longitudinal structural equations modeling of communication impacts

Information on the number and types of communication activities (including travel) engaged in over a period of four consecutive days, at two points in time about six months apart, was collected from 91 respondents in the context of the introduction of a community network to the city of Davis, California. Three major types of communication were measured: personal meetings (and in a separate but related measure, trips), transfer of an information object (in-house documents, regular mail, and express or overnight mail), and electronic (phone, fax, and e-mail). A system of structural equations was developed and estimated, expressing the number of instances of each type of communication at time 2 as a function of: the number of instances of each type at time 1, the elapsed time between measurements, and exogenous sociodemographic variables. All “own” lagged effects (that is, the effect of one communication type in wave 1 on the same type of communication in wave 2) were found to be positive and (except for information object delivery) highly significant. The “elapsed time” variable was always positive and (except for personal meetings and, in one model, information object delivery) significant; these effects indicate net generation of communication activities over time. Significant “cross” lagged effects (that is, the effect of one communication type in wave 1 on a different type in wave 2) were mostly positive, indicating the presence of some complementarity effects across modes. However, relationships specifically between electronic forms of communication and personal meetings or trips were not significant in either direction for the final models. Several exogenous variables were significant in logical ways.     

The recoverable robust facility location problem

This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters.For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm.     

The role of alternative fuel vehicles: Using behavioral and sensor data to model hierarchies in travel

Greater adoption and use of alternative fuel vehicles (AFVs) can be environmentally beneficial and reduce dependence on gasoline. The use of AFVs vis-à-vis conventional gasoline vehicles is not well understood, especially when it comes to travel choices and short-term driving decisions. Using data that contains a sufficiently large number of early AFV adopters (who have overcome obstacles to adoption), this study explores differences in use of AFVs and conventional gasoline vehicles (and hybrid vehicles). The study analyzes large-scale behavioral data integrated with sensor data from global positioning system devices, representing advances in large-scale data analytics. Specifically, it makes sense of data containing 54,043,889 s of speed observations, and 65,652 trips made by 2908 drivers in 5 regions of California. The study answers important research questions about AFV use patterns (e.g., trip frequency and daily vehicle miles traveled) and driving practices. Driving volatility, as one measure of driving practice, is used as a key metric in this study to capture acceleration, and vehicular jerk decisions that exceed certain thresholds during a trip. The results show that AFVs cannot be viewed as monolithic; there are important differences within AFV use, i.e., between plug-in hybrids, battery electric, or compressed natural gas vehicles. Multi-level models are particularly appropriate for analysis, given that the data are nested, i.e., multiple trips are made by different drivers who reside in various regions. Using such models, the study also found that driving volatility varies significantly between trips, driver groups, and regions in California. Some alternative fuel vehicles are associated with calmer driving compared with conventional vehicles. The implications of the results for safety, informed consumer choices and large-scale data analytics are discussed.     

Simulation model performance analysis of a multiple station shared vehicle system

As an alternative transportation paradigm, shared vehicle systems have become increasingly popular in recent years. Shared vehicle systems typically consist of a fleet of vehicles that are used several times each day by different users. One of the main advantages of shared vehicle systems is that they reduce the number of vehicles required to meet total travel demand. An added energy/emissions benefit comes when low-polluting (e.g., electric) vehicles are used in the system. In order to evaluate operational issues such as vehicle availability, vehicle distribution, and energy management, a unique shared vehicle system computer simulation model has been developed. As an initial case study, the model was applied to a resort community in Southern California. The simulation model has a number of input parameters that allow for the evaluation of numerous scenarios. Several measures of effectiveness have been determined and are calculated to characterize the overall system performance. For the case study, it was found that the most effective number of vehicles (in terms of satisfying customer wait time) is in the range of 3–6 vehicles per 100 trips in a 24 h day. On the other hand, if the number of relocations also is to be minimized, there should be approximately 18–24 vehicles per 100 trips. Various inputs to the model were varied to see the overall system response. The model shows that the shared vehicle system is most sensitive to the vehicle-to-trip ratio, the relocation algorithm used, and the charging scheme employed when electric vehicles are used. A preliminary cost analysis was also performed, showing that such a system can be very competitive with present transportation systems (e.g., rental cars, taxies, etc.).     

A rule for allocating joint truck-carrier costs

This paper presents a rule for allocating joint vehicle costs between fronthaul and backhaul truck trips on a given route. The rule is derived by extending the De Vany and Saving model of a competitive trucking industry operating in uncertain markets. The rule is based upon the existence of inventory costs related to truck trips and demand interdependency between fronthaul and backhaul truck trips. The rule is compared to an earlier joint cost allocation rule developed by Walters.     

Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems

This study demonstrates the sequential linking of two types of models to permit the comprehensive evaluation of regional transportation and land use policies. First, we operate an integrated urban model (TRANUS), which represents both land and travel markets with zones and networks. The travel and land use projections from TRANUS are outlined, to demonstrate the general reasonableness of the results, as this is the first application of a market-based urban model in the US. Second, the land use projections for each of the 58 zones in the urban model were fed into a Geographic Information System (GIS)-based land allocation model, which spatially allocates the several land uses within each zone according to simple accessibility rules. While neither model is new, this is one of the first attempts to link these two types of models for regional policy assessments. Other integrated urban models may be linked to other GIS land allocation models in this fashion. Pairing these two types of models allows the user to gain the advantages of the urban models, which represent spatial competition across a region and produce measures of user welfare (traveler and locator surplus), and the advantages of the GIS land allocation models, which produce detailed land use maps that can then be used for environmental impact assessment.     

A decision support approach to the computerisation of some operational decision problems in community transport

Community Transport (CT) in the UK operates a diverse range of services, and organisations are computerising management and operational functions. This paper describes the approach which has been taken to computerising four operational decision making functions.

The paper considers models of human decision making and problem solving, with particular reference to an information processing view of cognitive activity and to perception and memory. The design of decision support systems is also discussed.

Four decision problems are considered. For each, the paper considers how people tackle the problem, how computers can be used to tackle it and the approach which has been adopted.

For allocating trips to vehicles using a diary, the approach has been to provide a representation on screen of a manual diary. For vehicle brokerage, vehicles are presented to the operator allocating a booking in an order based on the Sequence Number, an index of how ‘difficult to book’ a vehicle is, and the distance of the vehicle's base from the start point of the trip. For the sorting of passenger pick‐ups into an efficient tour, traditional solutions to the travelling salesperson problem have been rejected in favour of a solution using spacefilling curves. Finally, for allocating dial‐a‐ride passenger trips to vehicle shifts an approach has been chosen which presents the operator with appropriate information rather than attempting to automate the scheduling.

The paper concludes that the approach to the diary has been successful and accepted by operators, although the similar approach to the dial‐a‐ride scheduling has not, as the system has not yet been able to replace manual scheduling aids. The facility to order passenger pick‐ups is little used by operators. Finally, it is suggested that the vehicle brokerage problem may be an appropriate use of fuzzy logic.     

Determining structural route components from GPS traces

Analysis of GPS traces shows that people often do not use the least cost path through the transportation network while making trips. This leads to the question which structural path characteristics can be used to construct realistic route choice sets for use in traffic simulation models. In this paper, we investigate the hypothesis that, for utilitarian trips, the route between origin and destination consists of a small number of concatenated least cost paths. The hypothesis is verified by analyzing routes extracted from large sets of recorded GPS traces which constitute revealed preference information. Trips have been extracted from the traces and for each trip the path in the transportation network is determined by map matching. This is followed by a path decomposition phase for which the algorithm constitutes the first contribution of this paper. There are multiple ways to split a given path in a directed graph into a minimal number of subpaths of minimal cost. By calculating two specific path splittings, it is possible to identify subsets of the vertices (splitVertexSuites) that can be used to generate every possible minimum path splitting by taking one vertex from each such subset. As a second contribution, we show how the extracted information is used in microscopic travel simulation. The distribution for the size of the minimum decomposition, extracted from the GPS traces, can be used in constrained enumeration methods for route choice set generation. The sets of vertices that can act as boundary vertices separating consecutive route parts contain way points (landmarks) having a particular meaning to their user. The paper explains the theoretical aspects of route splitting as well as the process to extract splitVertexSuites from big data. It reports statistical distributions extracted from sets of GPS traces for both multimodal person movements and unimodal car trips.     

A note on the calculation and calibration of doubly constrained trip distribution models

The use of growth factor models for trip distribution has given way in the past to the use of more complex synthetic models. Nevertheless growth factor models are still used, for example in modelling external trips, in small area studies, in input-output analysis, and in category analysis. In this article a particular growth factor model, the Furness, is examined. Its application and functional form are described together with the method of iteration used in its operation. The expected information statistic is described and interpreted and it is shown that the Furness model predicts a trip distribution which, when compared with observed trips, has the minimum expected information subject to origin and destination constraints. An equivalent entropy maximising derivation is described and the two methods compared to show how the Furness iteration can be used in gravity models with specified deterrence functions. A trip distribution model explicitly incorporating information from observed trips, is then derived.It is suggested that if consistency is to be maintained between iteration, calibration, and the derivation of gravity models, then expected information should be used as the calibration statistic to measure goodness of fit. The importance of consistency in this respect is often overlooked.Lastly, the limitations of the models are discussed and it is suggested that it may be better to use the Furness iteration rather than any other, since it is more fully understood. In particular its ease of calculation makes it suitable for use in small models computed by hand.