Design and development of interactive trip planning for web-based transit information systems

This article presents a Web-based transit information system design that uses Internet Geographic Information Systems (GIS) technologies to integrate Web serving, GIS processing, network analysis and database management. A path finding algorithm for transit network is proposed to handle the special characteristics of transit networks, e.g., time-dependent services, common bus lines on the same street, and non-symmetric routing with respect to an origin/destination pair. The algorithm takes into account the overall level of services and service schedule on a route to determine the shortest path and transfer points. A framework is created to categorize the development of transit information systems on the basis of content and functionality, from simple static schedule display to more sophisticated real time transit information systems. A unique feature of the reported Web-based transit information system is the Internet-GIS based system with an interactive map interface. This enables the user to interact with information on transit routes, schedules, and trip itinerary planning. Some map rendering, querying, and network analysis functions are also provided.     

Electric vehicle tour planning

This study extends the orienteering problem with time windows by considering electric vehicles (EV) with limited range. The model can simulate the change in the battery’s state of charge at each point along the routes, and thus can be used to solve the problem of EV tourist trip design with time windows. A land-sea integrated network for Penghu low-carbon islands was tested, and then the optimal green trip designs are obtained using a heuristic method. Some unique properties of the model are also discussed, as well as a number of management or planning implications.     

Managing rush hour travel choices with tradable credit scheme

This paper Analyzes a new tradable credit scheme (TCS) for managing commuters’ travel choices, which seeks to persuade commuters to spread evenly within the rush hour and between primary and alternative routes so that excessive traffic congestion can be alleviated. The scheme defines a peak time window and charges those who use the primary route within that window in the form of mobility credits. Those who avoid the peak-time window, by either traveling outside the peak time window or switching to the alternative route, may be rewarded credits. A market is created such that those who need to pay credits can purchase them from those who acquire them from their rewarding travel choices. A general analytical framework is proposed for a system of two parallel routes. The framework (1) considers a variety of assumptions about commuters’ behavior in response to the discontinuous credit charge introduced at the boundary of the peak-time window, (2) allows modeling congestion effects (or demand elasticity) on the alternative route, and (3) enables both the design of system optimal TCS and the analysis of the efficiency of any given TCS. Our analyses indicate that the proposed TCS not only achieves up to 33% efficiency gains in the base scenario, but also distributes the benefits among all the commuters directly through the credit trading. The results also suggest that very simple TCS schemes could provide substantial efficiency gains for a wide range of scenarios. Such simplicity and robustness are important to practicability of the proposed scheme. Numerical experiments are conducted to examine the sensitivity of TCS designs to various system parameters.     

Customers’ selections between premium electric taxis and liquefied petroleum gas taxis

Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, conventional liquefied petroleum gas taxis are one of the main contributors to roadside emissions as they operate on the streets 24 h a day with a long daily driving mileage. Moreover, these taxis suffer from a severely poor service reputation. To enhance the environmental friendliness and service quality of the taxi industry, this study explores the market potential of operating premium electric taxis in the dispatching mode. A stated preference survey was conducted to 1410 taxi customers about their taxi-riding choices between premium electric taxis and conventional liquefied petroleum gas taxis. In total, 5640 observations were obtained and used to develop a series of binary logistic regression models with different model formulations for the determination of the significant factors influencing customers’ selections. The findings indicate that walk time to and wait time for taxis were the most critical concerns to the customers, and they were more willing to take premium taxis if their journey distance was longer and their desired improvement on taxi service quality was greater. The socio-demographic status of taxi customers also influences their choices. The associated policy implications are discussed for promoting taxis with better service quality and fewer roadside emissions. The findings provide some policy insights to other international cities that have a similar taxi market to Hong Kong.     

A heuristic model for frequency planning and aircraft routing in small size airlines

The flight schedule of an airline is the primary factor in finding the most effective and efficient deployment of the airline's resources. The flight schedule process aims at finding a set of routes with associated aircraft type, frequency of service and times of departures and arrivals in order to satisfy a specific objective such as profit maximization. In this paper, we develop a two‐phase heuristic model for airline frequency planning and aircraft routing for small size airlines. The first phase develops a frequency plan using an economic equilibrium model between passenger demand for flying a particular route and aircraft operating characteristics. The second phase uses a time‐of‐day model to develop an assignment algorithm for aircraft routing.     

A GIS‐based method to identify cost‐effective routes for rural deviated fixed route transit

Deviated fixed route transit (DFRT) service connecting rural and urban areas is a growing transportation mode in the USA. Little research has been done to develop frameworks for route design. A methodology to explore the most cost‐effective DFRT route is presented in this paper. The inputs include potential DFRT demand distribution and a road network. A heuristic is used to build possible routes by starting at urban cores and extending in all network directions in certain length increments. All the DFRT routes falling in the length range desired by the users are selected. The cost effectiveness of those routes, defined by operating cost per passenger trip, is compared. The most cost‐effective route is selected and presented in a GIS map. A case study illustrates the methodology in several Tennessee metropolitan regions. The most cost‐effective route length is case specific; some routes (e.g. those out of our Nashville case) are most cost effective when short, while others (e.g. those out of Memphis) are most cost effective when long. Government agencies could use the method to identify routes with the lowest operating cost per passenger given a route length or an operating cost budget. Copyright © 2016 John Wiley & Sons, Ltd.     

Is equilibrium in transport pure Nash,mixed or Stochastic?

The classical theory of transport equilibrium is based on the Wardrop’s first principle that describes a Nash User Equilibrium (UE), where in no driver can unilaterally change routes to improve his/her travel times. A growing number of economic laboratory experiments aiming at testing Nash-Wardrop equilibrium have shown that the Pure Strategy Nash Equilibrium (PSNE) is not able to explain the observed strategic choices well. In addition even though Mixed Strategy Nash Equilibrium (MSNE) has been found to fit better the observed aggregate choices, it does not explain the variance in choices well. This study analyses choices made by users in three different experiments involving strategic interactions in endogenous congestion to evaluate equilibrium prediction. We compare the predictions of the PSNE, MSNE and Stochastic User Equilibrium (SUE). In SUE, the observed variations in choices are assumed to be due to perception errors. The study proposes a method to iteratively estimate SUE models on choice data with strategic interactions. Among the three sets of experimental data the SUE approach was found to accurately predict the average choices, as well as the variances in choices. The fact that the SUE model was found to accurately predict variances in choices, suggests its applicability for transport equilibrium models that attempt to evaluate reliability in transportation systems. This finding is fundamental in the effort to determining a behaviourally consistent paradigm to model equilibrium in transport networks. The study also finds that Fechner error which is the inverse of the scale parameter in the SUE model is affected by the group sizes and the complexity of the cost function. In fact, the larger group sizes and complexity of cost functions increased the variability in choices. Finally, from an experimental design standpoint we show that it is not possible to estimate a noise parameter associate to Fechner error in the case when the choices are equally probable.     

An improved algorithm for matching partial registration numbers

In order to identify route choice, registration number surveys were carried out and the numbers were then matched. Because of the nature of the routes being investigated, it was found that the level of spurious matches was large relative to the number of tripmakers. This cast considerable doubt on the estimated number of tripmakers and their mean journey times. Accordingly, it was necessary to devise an algorithm which minimised the effect of such errors. This algorithm and a method of estimating the number of residual spurious matches is discussed in this paper and is compared with the original algorithm for an actual example.     

A computer model for finding the time-dependent minimum path in a transit system with fixed schedules

This paper describes the development of a computer model and algorithms for finding the time-dependent minimum path between two stations in a multi-route, multi-mode transit system running to fixed schedules. Selection of the minimum path can be based either on journey time or on weighted time. A worked example using a simple transit network is given to illustrate how the model works. The model has several applications in transport planning: it can be used for generating route schedule information to guide transit users, for assisting in route schedule coordination, and for analyzing transit system accessibility.     

Evaluating a concept design of a crowd-sourced ‘mashup’ providing ease-of-access information for people with limited mobility

This study investigates the impact of using a concept map-based ‘mashup’ (www.accessadvisr.net) to provide volunteered (i.e. user contributed) ease of access information to travellers with limited mobility. A scenario-based user trial, centred around journey planning, was undertaken with 20 participants, divided equally between (1) those who have physical restrictions on their mobility, due to disability, illness or injury, and (2) those with practical mobility constraints due to being parents with young children who have to use a child’s pushchair when using public transport. Both user groups found the concept useful, but its potential impact was less for the pushchair user group. There were mixed views in relation to the ability of the mashup to convey the trustworthiness, credibility and reliability of information necessary for journey planning. The study identified a number of key information-related user requirements which help enable effective design of user contributed web-based resources for travellers with mobility-related issues.     

Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review

Accurate measurement of travel behaviour is vital for transport planning, modelling, public health epidemiology, and assessing the impact of travel interventions. Self-reported diaries and questionnaires are traditionally used as measurement tools; advances in Global Positioning Systems (GPS) technology allow for comparison. This review aimed to identify and report about studies comparing self-reported and GPS-measured journey durations. We systematically searched, appraised, and analysed published and unpublished articles from electronic databases, reference lists, bibliographies, and websites up to December 2012. Included studies used GPS and self-report to investigate trip duration. The average trip duration from each measure was compared and an aggregated, pooled estimate of the difference, weighted by number of trips, was calculated. We found 12 results from eight eligible studies. All studies showed self-reported journey times were greater than GPS-measured times. The difference between self-report and GPS times ranged from over-reporting of +2.2 to +13.5 minutes per journey. The aggregated, pooled estimate of the difference, weighted by number of trips, was over-report of +4.4 minutes (+28.6%). Studies comparing self-reported and GPS-measured journey duration have shown self-reported to be consistently over-reported across the study sample. Our findings suggest that when using self-reported journey behaviour, the journey durations should be treated as an over-estimation.     

Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Mind the map! The impact of transit maps on path choice in public transit

This paper investigates the impact of schematic transit maps on passengers’ travel decisions. It does two things: First, it proposes an analysis framework that defines four types of information delivered from a transit map: distortion, restoration, codification, and cognition. It then considers the potential impact of this information on three types of travel decisions: location, mode, and path choices.¹ Second, it conducts an empirical analysis to explore the impact of the famous London tube map on passengers’ path choice in the London Underground (LUL). Using data collected by LUL from 1998 to 2005, the paper develops a path choice model and compares the influence between the distorted tube map (map distance) and reality (travel time) on passengers’ path choice behavior. Results show that the elasticity of the map distance is twice that of the travel time, which suggests that passengers often trust the tube map more than their own travel experience on deciding the “best” travel path. This is true even for the most experienced passengers using the system. The codification of transfer connections on the tube map, either as a simple dot or as an extended link, could affect passengers’ transfer decisions. The implications to transit operation and planning, such as trip assignments, overcrowding mitigation, and the deployment of Advanced Transit Information System (ATIS), are also discussed.     

Design of public transit network in urban area with elastic demand

This research focuses on an efficient design of transit network in urban areas. The system developed is used to create, analyze and optimize routes and frequencies of transit system in the network level. The analysis is based on elastic demand, so the shift of demand between modes in network due to different service level is of prime consideration. The developed system creates all feasible routes connecting all pairs of terminals in the network. Out of this vast pool of routes, a set of optimal routes is generated for a certain predetermined number that maintains connectivity of significant demand. Based on these generated routes, the system fulfils transportation demand by assigning demand that considers path and route choices for non-transit users and transit users. Together with the assignment of demand, transit frequencies are optimized and the related fleet-size is calculated. Having an optimal setting of solution, the system is continued by reconnecting the routes to find some other better solutions in the periphery of the optimal setting. A set of mathematical programming modules is developed. Real data from Sioux Falls city network is used to evaluate the performance of the model and compare with other heuristic methods.     

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.     

A combined destination and route choice model for a bicycle sharing system

This paper studies the supply variables that influence the destination and route choices of users of a bicycle sharing system in the Chilean city of Santiago. A combined trip demand logit model is developed whose explanatory variables represent attributes relating to the topology of the possible routes and other characteristics such as the presence of bikeways, bus service and controlled intersections. The data for the explanatory variables and system users were collected through field surveys of the routes and interviews conducted at the system stations. The results of the model show that proximity to stops on the Santiago Metro and the existence of bikeways are the main factors influencing destination and route choices. Also indicated by the model estimates are gender differences, a preference for tree-lined routes and an avoidance of routes with bus services. Finally, the outcomes reveal considerable potential for the integration of bicycle sharing systems with Metro transit.     

Exploration of route choice behavior with advanced traveler information using neural network concepts

A model of driver's route choice behavior under advanced traveler information system (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. The experiment subjected drivers to 32 simulated days in which they were to choose between the freeway or a side road. A neural network model is used as a convenient modeling technique in this initial phase of the analysis. The results indicated that most subjects made route choices based mainly on their recent experiences. It was also demonstrated that route choice behaviors are related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences have less effect on the choice of the side road compared to the freeway and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely correlated. The model developed here was for advice consistently provided at a level of 75 percent accuracy. The paper concludes with a discussion of experimental limitations and suggestions for future research.     

Optimal transit service atop ring-radial and grid street networks: A continuum approximation design method and comparisons

Two continuum approximation (CA) optimization models are formulated to design city-wide transit systems at minimum cost. Transit routes are assumed to lie atop a city’s street network. Model 1 assumes that the city streets are laid out in ring-radial fashion. Model 2 assumes that the city streets form a grid. Both models can furnish hybrid designs, which exhibit intersecting routes in a city’s central (downtown) district and only radial branching routes in the periphery. Model 1 allows the service frequency and the route spacing at a location to vary arbitrarily with the location’s distance from the center. Model 2 also allows such variation but in the periphery only.The paper shows how to solve these CA optimization problems numerically, and how the numerical results can be used to design actual systems. A wide range of scenarios is analyzed in this way. It is found among other things that in all cases and for both models: (i) the optimal headways and spacings in the periphery increase with the distance from the center; and (ii) at the boundary between the central district and the periphery both, the optimal service frequency and line spacing for radial lines decrease abruptly in the outbound direction. On the other hand Model 1 is distinguished from Model 2 in that the former produces in all cases: (i) a much smaller central district, and (ii) a high frequency circular line on the outer edge of that central district.Parametric tests with all the scenarios further show that Model 1 is consistently more favorable to transit than Model 2. Cost differences between the two designs are typically between 9% and 13%, but can top 21.5%. This is attributed to the manner in which ring-radial networks naturally concentrate passenger’s shortest paths, and to the economies of demand concentration that transit exhibits. Thus, it appears that ring-radial street networks are better for transit than grids.To illustrate the robustness of the CA design procedure to irregularities in real street networks, the results for all the test problems were then used to design and evaluate transit systems on networks of the “wrong” type – grid networks were outfilled with transit systems designed with Model 1 and ring-radial networks designed with Model 2. Cost increased on average by only 2.7%. The magnitude of these deviations suggests that the proposed CA procedures can be used to design transit systems over real street networks when they are not too different from the ideal and that the resulting costs should usually be very close to those predicted.     

Validating the results of a route choice simulator

This paper describes the validation of a route choice simulator known as VLADIMIR (Variable Legend Assessment Device for Interactive Measurement of Individual Route choice). VLADIMIR is an interactive computer-based tool designed to study drivers’ route choice behaviour. It has been extensively used to obtain data on route choice in the presence of information sources such as Variable Message Signs or In-Car Navigation devices. The simulator uses a sequence of digitized photographs to portray a real network with junctions, links, landmarks and road signs. Subject drivers are invited to make journeys between specified origins and destinations under a range of travel scenarios, during which the simulator automatically records their route choices. This paper describes validation experiments carried out during the period Summer 1994 to Autumn 1995 and reports on the results obtained. Each experiment involved a comparison of routes selected in real life with those driven under simulated conditions in VLADIMIR. The analysis included investigation of the subjects’ own assessment of the realism of the VLADIMIR routes they had chosen, a comparison of models based on the real life routes with models based on VLADIMIR routes, and a statistical comparison of the two sets of routes. After an extensive series of data collection exercises and analyses, we have concluded that a well designed simulator is able to replicate real life route choices with a very high degree of detail and accuracy. Not only was VLADIMIR able to precisely replicate the route choices of drivers who were familiar with the network but it also appears capable of representing the kind of errors made and route choice strategies adopted by less familiar drivers. Furthermore, evidence is presented to suggest that it can accurately replicate route choice responses to roadside VMS information.