An integrated Bayesian approach for passenger flow assignment in metro networks

This paper proposes an integrated Bayesian statistical inference framework to characterize passenger flow assignment model in a complex metro network. In doing so, we combine network cost attribute estimation and passenger route choice modeling using Bayesian inference. We build the posterior density by taking the likelihood of observing passenger travel times provided by smart card data and our prior knowledge about the studied metro network. Given the high-dimensional nature of parameters in this framework, we apply the variable-at-a-time Metropolis sampling algorithm to estimate the mean and Bayesian confidence interval for each parameter in turn. As a numerical example, this integrated approach is applied on the metro network in Singapore. Our result shows that link travel time exhibits a considerable coefficient of variation about 0.17, suggesting that travel time reliability is of high importance to metro operation. The estimation of route choice parameters conforms with previous survey-based studies, showing that the disutility of transfer time is about twice of that of in-vehicle travel time in Singapore metro system.     

An integrated measure of accessibility and reliability of mass transit systems

The growth of a city or a metropolis requires well-functioning transit systems to accommodate the ensuing increase in travel demand. As a result, mass transit networks have to develop and expand from simple to complex topological systems over time to meet this demand. Such an evolution in the networks’ structure entails not only a change in network accessibility, but also a change in the level of network reliability on the part of stations and the entire system as well. Network accessibility and reliability are popular measures that have been widely applied to evaluate the resilience and vulnerability of a spatially networked system. However, the use of a single measure, either accessibility or reliability, provides different results, which demand an integrated measure to evaluate the network’s performance comprehensively. In this paper, we propose a set of integrated measures, named ACCREL (Integrated Accessibility and Reliability indicators) that considers both metrics in combination to evaluate a network’s performance and vulnerability. We apply the new measures for hypothetical mass transit system topologies, and a case study of the metro transit system in Seoul follows, highlighting the dynamics of network performance with four evolutionary stages. The main contribution of this study lies in the results from the experiments, which can be used to inform how transport network planning can be prepared to enhance the network functionality, thereby achieving a well-balanced, accessible, and reliable system. Insights on network vulnerability are also drawn for public transportation planners and spatial decision makers.     

Evaluation of urban accessibility indicators based on internal and external environmental costs

This paper estimates urban accessibility considering types of transport and destinations, taking into account the internal travel time costs, and the ensuing external environmental impacts. Based on online and local surveys, an accessibility function is developed to allow for the construction of an accessibility curve for each transport mode that decreases with distance to represent decaying accessibility. An external environmental impact is associated with the accessibility indicators, taking into account the influence of the cold-start emissions that are particularly relevant for short-distance trips. The methodology is applied to neighborhoods in Lisbon, Portugal, with significant differences in their urban planning, mobility patterns, concentration of services and availability of public transportation.     

Dynamic network equilibrium for daily activity-trip chains of heterogeneous travelers: application to large-scale networks

Applications of dynamic network equilibrium models have, mostly, considered the unit of traffic demand either as one-way trip, or as multiple independent trips. However, individuals’ travel patterns typically follow a sequence of trips chained together. In this study we aim at developing a general simulation-based dynamic network equilibrium algorithm for assignment of activity-trip chain demand. The trip chain of each individual trip maker is defined by the departure time at origin, sequence of activity destination locations, including the location of their intermediate destinations and their final destination, and activity duration at each of the intermediate destinations. Spatial and temporal dependency of subsequent trips on each other necessitate time and memory consuming calculations and storage of node-to-node time-dependent least generalized cost path trees, which is not practical for very large metropolitan area networks. We first propose a reformulation of the trip-based demand gap function formulation for the variational inequality formulation of the Bi-criterion Dynamic User Equilibrium (BDUE) problem. Next, we propose a solution algorithm for solving the BDUE problem with daily chain of activity-trips. Implementation of the algorithm for very large networks circumvents the need to store memory-intensive node-to-node time-dependent shortest path trees by implementing a destination-based time-dependent least generalized cost path finding algorithm, while maintaining the spatial and temporal dependency of subsequent trips. Numerical results for a real-world large scale network suggest that recognizing the dependency of multiple trips of a chain, and maintaining the departure time consistency of subsequent trips provide sharper drops in gap values, hence, the convergence could be achieved faster (compared to when trips are considered independent of each other).     

Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data

Accessibility is a key concept in transportation research and an important indicator of people’s quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents’ real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone’s real-travel covered area. We then apply this DMAG methodology to Shanghai’s central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.     

Travel time ratio: the key factor of spatial reach

An important aspect of reach and accessibility is the time people are willing to spend on reaching activity places. In this paper we see the issue of travel time in an alternative way. Instead of looking at travel time separated from time spent on activities, we examine the relation between travel time and stay time. We operationalize this relation with the concept “travel time ratio”. A hypothetical framework underlying these travel time ratios is displayed. We show that for similar types of activity places the value of travel time ratio are in accordance with each other. We find large differences between trips for mandatory activities and trips for discretionary activities. The results indicate the stability of the travel time ratios. Finally, some implications for future research and policy will be mentioned. This revised version was published online in June 2006 with corrections to the Cover Date.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Effects of built environment on walking at the neighbourhood scale. A new role for street networks by modelling their configurational accessibility?

The hypothesis of this paper is that some features of the built environment, particularly those concerned with the accessibility of the street network, could be associated with the proportion of pedestrians on all trips (modal split) found in different parts of a city. Quantitative analysis (bi-variate correlation and a multiple regression model) was used to establish the association between variables. The study area covered a substantial part of the metropolitan area in Madrid, Spain. Results showed a consistent influence of five particular indexes in the multi-variate model. Not surprisingly for this kind of research, four of them described density and mix of land uses. But perhaps more interestingly, the first one was a measure of the accessibility of the public space network, a less prominent variable in literature to date. This variable is called herein configurational accessibility, calculated using Space Syntax, an urban morphology theory. The relevance of configurational accessibility is probably related to its surprising ability to synthesize global and perceived properties of street networks at the same time. The findings introduce the idea that the configuration of the urban grid can influence the proportion of pedestrians (as a part of total trips in any transport mode) who choose to walk on single-journey trips. The discussion links with the current debate about walkability indexes and the need of empirical support for the chosen variables and also with transport planning. Because the relevance of the street network’s role is not so easy to grasp, inputs from configurational theory and the pedestrian potential underlying this fact are also discussed at the end of the paper.     

Mapping spatial accessibility of public transportation network in an urban area – A case study of Shanghai Hongqiao Transportation Hub

Accessibility is a key metric when assessing the efficiency of an urban public transportation network. This research develops a methodology for evaluating spatial accessibility of a system with multiple transportation modes in an urban area, Shanghai Hongqiao Transportation Hub (SHTH) and its surrounding area. The method measured total traveling time as an accessibility indicator, which summed the time people spent on walking, waiting, transfer and transportation in a journey from the SHTH to destinations. Spatial accessibility was classified into five levels from very high to very low. The evaluation was conducted at a cell-by-cell basis under an overall scenario and three specific scenarios. Evaluation results were presented in a series of maps. The overall accessibility scenario shows a concentric-ring trend decreasing from the SHTH to the fringe of the study area. Areas along the metro lines generally have a much higher accessibility than those along the bus lines with some exceptions where bus routes play a more important role. Metro stations identified as either time-saving or time-consuming points are mainly distributed around the urban center. Some suggestions are proposed for improving accessibility of public transportation network in the study area. The results from this study provide a scientific basis and useful information for supporting decision-making on urban planning, and assisting dwellers to travel in a time-efficient manner. The methodology offers a simple, flexible way to the spatial evaluation, metro station identification and network modification of accessibility of public transportation systems with multiple transportation modes.     

Does regional travel time unreliability influence mode choice?

Researchers and practitioners highlight the unreliability of travel as a potential weak link in the transportation system which may inhibit individuals’ accessibility and urban economic activity. With the trend towards increasing traffic congestion, the outlook suggests that travel conditions will become structurally less reliable over time, but that not all places will be equally affected. But is travel time unreliability a problem? This study uses global positioning systems travel survey data for Chicago to build a regional model of travel time unreliability. The results suggest that unreliability varies spatially during different time periods, but that the average overall network unreliability varies little across times in the day. Using the Chicago Metropolitan Agency for Planning (CMAP)’s 2007 Travel Tracker Survey, a household travel diary survey including both GPS and non-GPS components, we estimate a mode choice model for work trips to explore the influence of unreliability on travel behavior. The results suggest that unreliable auto travel conditions induce mode switching to transit and that the influence is strongest when service by train is already faster than by car. This further suggests that auto travel unreliability may have the strongest influence in metropolitan regions with highly-competitive transit systems. Nevertheless, the influence of travel unreliability is limited and is not the underlying driver of travel decision-making.     

Link travel time inference using entry/exit information of trips on a network

This paper studies link travel time estimation using entry/exit time stamps of trips on a steady-state transportation network. We propose two inference methods based on the likelihood principle, assuming each link associates with a random travel time. The first method considers independent and Gaussian distributed link travel times, using the additive property that trip time has a closed-form distribution as the summation of link travel times. We particularly analyze the mean estimates when the variances of trip time estimates are known with a high degree of precision and examine the uniqueness of solutions. Two cases are discussed in detail: one with known paths of all trips and the other with unknown paths of some trips. We apply the Gaussian mixture model and the Expectation–Maximization (EM) algorithm to deal with the latter. The second method splits trip time proportionally among links traversed to deal with more general link travel time distributions such as log-normal. This approach builds upon an expected log-likelihood function which naturally leads to an iterative procedure analogous to the EM algorithm for solutions. Simulation tests on a simple nine-link network and on the Sioux Falls network respectively indicate that the two methods both perform well. The second method (i.e., trip splitting approximation) generally runs faster but with larger errors of estimated standard deviations of link travel times.     

A new generalized travel cost based connectivity metric applied to Scandinavian airports

This article proposes a new, generalized travel cost based method to operationalize network accessibility provided by airports. The approach is novel as it integrates features of network topology with multiple quality aspects of scheduled air transport services into one metric. The method estimates generalized travel costs for the full set of feasible travel paths between an airport and all network destinations. Rooftop modeling accounts for schedule delay and isolates the most cost-efficient travel paths per O-D relation. Respecting the assumed arrival time preference of passengers and adjusting for destination importance, connectivity scores are derived. The method is then applied to explore changes in the global connectivity pattern of Scandinavian airports from 2004 to 2018. The results suggest distinct spatial differences throughout the network, but less pronounced in size than suggested by popularly applied connectivity measures. Findings also highlight the importance of the geographical location as a determinate of an airport’s connectivity.     

Traveler delay costs and value of time with trip chains, flexible activity scheduling and information

The delay costs of traffic disruptions and congestion and the value of travel time reliability are typically evaluated using single trip scheduling models, which treat the trip in isolation of previous and subsequent trips and activities. In practice, however, when activity scheduling to some extent is flexible, the impact of delay on one trip will depend on the actual and predicted travel time on itself as well as other trips, which is important to consider for long-lasting disturbances and when assessing the value of travel information. In this paper we extend the single trip approach into a two trips chain and activity scheduling model. Preferences are represented as marginal activity utility functions that take scheduling flexibility into account. We analytically derive trip timing optimality conditions, the value of travel time and schedule adjustments in response to travel time increases. We show how the single trip models are special cases of the present model and can be generalized to a setting with trip chains and flexible scheduling. We investigate numerically how the delay cost depends on the delay duration and its distribution on different trips during the day, the accuracy of delay prediction and travel information, and the scheduling flexibility of work hours. The extension of the model framework to more complex schedules is discussed.     

Does a circular high-speed rail network promote efficiency and spatial equity in transport accessibility? Evidence from Hainan Island,China

This paper investigates the efficiency and spatial equity impacts of a unique island-looping high-speed rail (HSR) network in Hainan province, China. An integrated network and raster-based model is applied to accurately measure the accessibility indicators. We perform analysis at four different geographical planning levels – island, corridor, spillover, and county level. The HSR with a non-polarized topology can increase the accessibility of the entire island and corridor, but only leads to a slight increase in the spillover areas without HSR stations. HSR construction also leads to spatial cohesion for the entire island and corridor. Although the circular HSR network consists of several HSR stations distributed relatively equally, the results show that counties contribute differently to the cohesion of the entire island due to the varied initial level of accessibility values. Moreover, the county-level analysis reveals that the internal changes of each county are also different with balancing, polarization, and neutral effects appearing. Therefore, the internal equity of counties needs to be combined with their external contributions to global equity. Our framework permits policymakers to make customized HSR transport policies at different planning levels, particularly for an isolated area.     

Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment

Automated driving technologies are currently penetrating the market, and the coming fully autonomous cars will have far-reaching, yet largely unknown, implications. A critical unknown is the impact on traveler behavior, which in turn impacts sustainability, the economy, and wellbeing. Most behavioral studies, to date, either focus on safety and human factors (driving simulators; test beds), assume travel behavior implications (microsimulators; network analysis), or ask about hypothetical scenarios that are unfamiliar to the subjects (stated preference studies). Here we present a different approach, which is to use a naturalistic experiment to project people into a world of self-driving cars. We mimic potential life with a privately-owned self-driving vehicle by providing 60 h of free chauffeur service for each participating household for use within a 7-day period. We seek to understand the changes in travel behavior as the subjects adjust their travel and activities during the chauffeur week when, as in a self-driving vehicle, they are explicitly relieved of the driving task. In this first pilot application, our sample consisted of 13 subjects from the San Francisco Bay area, drawn from three cohorts: millennials, families, and retirees. We tracked each subject’s travel for 3 weeks (the chauffeur week, 1 week before and 1 week after) and conducted surveys and interviews. During the chauffeur week, we observed sizable increases in vehicle-miles traveled and number of trips, with a more pronounced increase in trips made in the evening and for longer distances and a substantial proportion of “zero-occupancy” vehicle-miles traveled.     

Effects of land-use transport scenarios on travel patterns: a multi-state supernetwork application

Understanding travellers’ response is essential to address policy questions arising from spatial and transport planning sectors. This paper demonstrates the usefulness of the multi-state supernetwork approach to investigate the effects of land-use transport scenarios on individuals’ travel patterns. In particular, it illustrates that multi-state supernetworks are capable of representing activity-travel patterns at a high level of detail, including the choice of mode, route, parking and activity location. Multi-faceted activity-travel preferences can be accommodated in supernetworks. Using a micro-simulation approach, the adaptation of individuals’ travel patterns to policies can be readily captured. The illustration concerns hypothetical land-use and transport scenarios for the city of Rotterdam (The Netherlands), focusing on accessibility changes, modal substitution and shift in the use of transport and location facilities.     

A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks

Urban travel demand, consisting of thousands or millions of origin–destination trips, can be viewed as a large-scale weighted directed graph. The paper applies a complex network-motivated approach to understand and characterize urban travel demand patterns through analysis of statistical properties of origin–destination demand networks. We compare selected network characteristics of travel demand patterns in two cities, presenting a comparative network-theoretic analysis of Chicago and Melbourne. The proposed approach develops an interdisciplinary and quantitative framework to understand mobility characteristics in urban areas. The paper explores statistical properties of the complex weighted network of urban trips of the selected cities. We show that travel demand networks exhibit similar properties despite their differences in topography and urban structure. Results provide a quantitative characterization of the network structure of origin–destination demand in cities, suggesting that the underlying dynamical processes in travel demand networks are similar and evolved by the distribution of activities and interaction between places in cities.     

Bi-level GA and GIS for Multi-objective TSP Route Planning

Abstract

Route planning is usually carried out to achieve a single objective such as to minimize transport cost, distance traveled or travel time. This article explores an approach to multi-objective route planning using a genetic algorithm (GA) and geographical information system (GIS) approach. The method is applied to the case of a tourist sight-seeing itinerary, where a route is planned by a tour operator to cover a set of places of interest within a given area. The route planning takes into account four criteria including travel time, vehicle operating cost, safety and surrounding scenic view quality. The multi-objective route planning in this paper can be viewed as an extension of the traditional traveling salesman problem (TSP) since a tourist needs to pass through a number of sight points. The four criteria are quantified using the spatial analytic functions of GIS and a generalized cost for each link is calculated. As different criteria play different roles in the route selection process, and the best order of the multiple points needs to be determined, a bi-level GA has been devised. The upper level aims to determine the weights of each criterion, while the lower level attempts to determine the best order of the sights to be visited based on the new generalized cost that is derived from the weights at the upper level. Both levels collaborate during the iterations and the route with the minimal generalized cost is thus determined. The above sight-seeing route planning methodology has been examined in a region within the central area of Singapore covering 19 places of interest.     

Investigation of the use of smartphone applications for trip planning and travel outcomes

This paper explores the use of smartphone applications for trip planning and travel outcomes using data derived from a survey conducted in Halifax, Nova Scotia, in 2015. The study provides empirical evidence of relationships of smartphone use for trip planning (e.g. departure time, destination, mode choice, coordinating trips and performing tasks online) and resulting travel outcomes (e.g. vehicle kilometers traveled, social gathering, new place visits, and group trips) and associated factors. Several sets of factors such as socio-economic characteristics and travel characteristics are tested and interpreted. Results suggest that smartphone applications mostly influence younger individuals’ trip planning decisions. Transit pass owners are the frequent users of smartphone applications for trip planning. Findings suggest that transit pass owners commonly use smartphone applications for deciding departure times and mode choices. The study also identifies the limited impact of smartphone application use on reducing travel outcomes, such as vehicle kilometers traveled. The highest impact is in visiting new places (a 48.8% increase). The study essentially offers an original in-depth understanding of how smartphone applications are affecting everyday travel.     

Ramp meters on trial: Evidence from the Twin Cities metering holiday

Ramp meters in the Twin Cities have been the subject of a recent test of their effectiveness, involving turning them off for eight weeks. This paper analyzes the results with and without ramp metering for several representative freeways during the afternoon peak period. Seven performance measures: mobility, equity, productivity, consumers’ surplus, accessibility, travel time variation and travel demand responses are compared. It is found that ramp meters are particularly helpful for long trips relative to short trips. Ramp metering, while generally beneficial to freeway segments, may not improve trip travel times (including ramp delays). The reduction in travel time variation comprises another benefit from ramp meters. Non-work trips and work trips respond differently to ramp meters. The results are mixed, suggesting a more refined ramp control algorithm, which explicitly considers ramp delay, is in order.