Route choice of bike share users: Leveraging GPS data to derive choice sets

To identify the determinants of bike share users' route choices, this research collects 132,397 hub-to-hub global positioning system (GPS) trajectories over a 12-month period between April 1, 2015 and March 31, 2016 from 750 bicycles provided by Hamilton Bike Share (HBS). A GIS-based map-matching algorithm is used to derive users' routes along the cycling network within Hamilton, Ontario and generate multiple attributes for each route, such as route distance, route directness, average distance between intersections, and the number of turns, intersections, and unique road segments. Concerning route choice analysis, the origin and destination pair should be the same for all routes within a choice set, thus HBS users' trips are grouped by origin-destination hub pairs. Since trips taken by different users between a hub pair can follow the same route, unique routes are extracted using a link signature extraction tool. Following this, a normalized Gini (G_n) coefficient is calculated for each hub pair to evaluate users' preferences among all the unique hub-to-hub route choices. A G_n closer to 0 indicates that routes between a hub pair are more evenly used, while a value closer to 1 implies a higher preference toward one dominant route. Three route choice models, a global model, a medium G_n model, and a high G_n model, are estimated using Path-Size Logit to determine how route choice is affected by the presence of dominant routes. These models suggest that HBS users are willing to detour for some attributes, such as bicycle facilities, but tend to avoid circuitous routes, turns, steep slopes, and roads with high traffic volume.     

Resolving splits in location/allocation modeling: a heuristic procedure for transit center decisions

A heuristic procedure is developed to assign buses to transit centers (garages) in such a way that all the buses on a particular route are assigned to a single transit center. This research builds on an optimal mixed integer programming location/allocation model that splits the bus assignments when capacity limitations were reached at a transit center. The heuristic procedure adopts a two-step process: namely, assignment of all buses of a route to a unique transit center, then switching of routes to alternative transit centers to enforce capacity limitations. The procedure is shown to still provide cost savings over current locations and allocations for the Vancouver Regional Transit System (VRTS), Canada's largest urban transit network.     

Route choice behavior in a radial structured urban network: Do people choose the orbital or the route through the city center?

We use a license plate survey to study route choice through the city center of a medium-sized Dutch city, in which car drivers can basically choose between the orbital and center ring. For a sample of 1397 trips, we fitted a multinomial logit regression model. According to this model, route choice is relatively little influenced by actual travel time. This corresponds with the fact that many drivers did not choose the shortest time route. Travel distance in combination with one “route type velocity” for all orbital routes, and one route type velocity for all center routes is the most decisive factor. The route type velocity indicates how fast and attractive routes of that type are (being perceived). The results support the hypothesis that orbital routes are more attractive as these routes avoid the busy city center. This effect is however partly offset by the fact that drivers also prefer routes in the direction of their destination. These direct routes are mainly center routes. The results show the importance of considering complete routes in relation to their location and not only as a set of links and nodes when modeling route choice.     

Mutual influence across routes using a common airport: The case of the domestic market in Japan

This paper empirically investigates the mutual influence of traffic volumes across routes serving the same airport. Regression analysis using the data on Japan's domestic air transport market reveals that an increase in passengers on a given route has a positive effect on the number of passengers on other routes that share an endpoint airport with the given route. This result implies that a change in policy for an airport is likely to influence routes that do not serve that airport as well as the routes that do.     

An analysis of drivers route choice behaviour using GPS data and optimal alternatives

This work aims to study drivers' route choices using a dataset of low frequency GPS coordinates to identify travels' trajectories. The sample consists of 89 drivers who performed 42 thousand paths in the province of Reggio Emilia, in Italy, during the seventeen considered months. Four attributes that may be important for the driver are identified and four optimal alternative paths are created based on the selected objectives to evaluate route choice behaviour. The comparison between the characteristics of the paths allows to conclude that drivers select routes that are overall longer than their optimal alternatives but that allow for higher speeds. Furthermore the statistical analysis of drivers' route choices in macroareas evidences that drivers have different behaviours depending on the geography of the territory. Specifically, there is higher heterogeneity of route choices in the plain areas compared to the mountains. In the second part of this work, clusters of repetitive travels are identified and a Geographical Route Directness Index is proposed to identify the areas of the province where the deviation from the shortest alternative path is higher. The analysis shows that, among groups of repetitive travels, the value of the index is higher along the ring road of the city of Reggio Emilia and there is a strong negative correlation between the frequency the driver selects the longer alternative that allow for higher speed, and the number of additional kilometres the same driver has to travel.     

A GIS-based toolkit for route choice analysis

This paper develops and applies the route choice analysis (RCA) toolkit. This GIS-based toolkit generates a suite of over 40 variables describing route characteristics such as distance, travel time, speed statistics, number of intersections, number of turns, number of stop signs/stop lights, and a measure of route circuity, to name a few. The input to the toolkit is one or more routes, which can be obtained from global positioning system (GPS) data or some other means (e.g., shortest path). While the toolkit is designed to support route choice modeling by generating variables that have been tested in previous modeling efforts, we demonstrate its utility by testing the hypothesis that workers choose routes to minimize either travel time or distance between home and work. A GPS-enhanced data set of 237 observed routes for home-to-work trips collected for auto drivers in Halifax, Nova Scotia, Canada is used in our analysis. We find that the null hypothesis is refuted - that is, a comparison of observed routes to their shortest-path alternatives based on time and distance via inferential statistics indicates that observed routes are significantly longer compared to their alternatives. This finding suggests that workers may choose routes based on other route attributes. The attributes generated by the RCA toolkit for observed, shortest time, and shortest distance routes are compared and significant differences are noted.     

Determinants of route choice behavior: A comparison of shop versus work trips using the Potential Path Area - Gateway (PPAG) algorithm and Path-Size Logit

This paper presents an in-depth comparison of route choice models for work and shop vehicle trips—with emphasis on the interactions between route attributes and individual characteristics—to better understand the route choice determinants that are assumed to vary by trip purpose. Insights into the route choice behavior involving two dominant vehicle trip purposes—work and shop trips—will help in the design of traffic facilities and implementation of measures to influence route choice in the desired direction.In this study, we show that the utility and scale parameters for separate models of work and shop trips differ by direct comparison using a sequential scaling estimation method and likelihood ratio tests, and highlight the differences in route choice behavior by considering the interaction of route attributes and individual characteristics using Path-Size Logit modeling. In the process, we used Potential Path Area - Gateway (PPAG) algorithm—that generates feasible route choice sets for route choice modeling from GPS trajectories of observed routes.The results show that, indeed, route choice behavior varies by trip, which suggests that drivers attach value to route choice determinants relative to trip purpose. The inclusion of interaction terms in model specifications further indicates that work route choice behavior tends to be restrictive compared to the nonrestrictive route choice for shop trips—a generalization consistent with the mandatory and discretionary nature of work and shop trips, respectively. Specifically, individual characteristics such as personal income, age, gender, tenure, household size, and access to public transit affect route choice behavior.     

Anatomy of a new dollar van route: Informal transport and planning in New York City

Despite nearly eight million rides per day on formally planned and legally sanctioned buses and subways, dollar vans provide service that shadow some of the busiest bus lines in Brooklyn and Queens. Dollar vans are an informal transport service that occupy an awkward liminal space between legal and illegal—some are licensed and some are not, but all dollar vans operate illegally. It is this legal confusion that renders them informal. It is because of this informality that dollar van operators and drivers can also adapt their routes and service as they deem necessary. This “generative” mode of planning introduces a second dimension of informality; however, I argue that dollar van operators follow a similar logic as formal transportation operators when planning service. I demonstrate this by examining the case of a dollar van operator in Brooklyn developing a new route. I juxtapose his method with that of bus planners from the Metropolitan Transportation Authority (MTA) to show how both groups of planners rely on prompts they encounter, be it anecdotal stories about West Indians in Flatbush moving away or an angry letter from a state legislator, rather than a systematic approach that is taught in classrooms. By examining the planning of a new dollar van route in Brooklyn, I trace the operator's planning process and compare his data against quantitative datasets to show that his generative planning process is supported by the quantitative data and deepens its meaning when combined with his local knowledge. Seen in this light, it is clear that the distance between informal and formal transit is artificial rather than inherent.     

Improving Bus Service Levels and social equity through bus frequency modelling

Bus lines play an essential role in providing urban public transport service. Demographic and socioeconomic characteristics determine the specific transport service needs of districts that, in most cases, are not served by the existing bus routes. Small changes in the frequency of a bus route can have a direct effect on the territorial distribution of a city's public transport service. Adjusting the frequencies of a bus fleet can help planners improve the service level and adapt the fleet's spatial distribution. A bus frequency optimization methodology is proposed to improve harmonization between service level and social equity in public transport. The method relies on a simple spreadsheet that integrates geographic data about bus routes and socioeconomic information about city districts. Simulation and optimization procedures are coordinated to appropriately adjust the routes to the geographic space. The proposed method is tested in a real case study that demonstrates its usefulness in analysing the service level and equity of a transport system and improving a city's public transport planning.     

Drivers of long-haul air transport route development

An analysis of long-haul routes identifies trends and patterns underlying their development. Five distinct perspectives: geography, regulation, manufacturers, passengers and airlines are taken to investigate the drivers of long-haul route development. From the insights gained it is inferred that the demand for long-haul aircraft is a complex function thereof, whereby long-haul routes are operated between cities with strong business and social connections as influenced by the dynamics of change and underlying geography.     

Assigning delivery routes to drivers under variable customer demands

This study covers situations in which random day-to-day customer demands complicate decisions made by managers of vehicle routing/dispatch operations. The paper proposes and analyzes a rule to guide the decision of interest: daily assignment of delivery routes to drivers. The rule targets customer service goals by trying to maximize the likelihood that each customer will continue to be served by the driver who is most familiar with that customer. Statistical analysis of the rule yields several managerial implications about pursuing maximum customer-driver familiarity. Among these is the potentially problematic wide disparity in a customer’s level of familiarity with different drivers.     

Operationalization of path walkability for sustainable transportation

Most walking travel behavior research thus far has tested area-based neighborhood walkability, which is measured with meso-level urban form attributes. In need of micro-level walkability analyses that focus on individual travelers and their routes, we propose a route-oriented linear walkability concept named “path walkability.” It is defined and measured by 42 path walkability indicators that can collectively represent an individual traveler's micro-level walkability. A graphic measurement instrument for an objective and efficient on-field walkability measurement is developed. This study also sets the protocol for quantitatively integrating the walkability data measured at the segment level into path walkability indicators that are comparable at the route level. To test the applicability of the proposed path walkability, a pilot case study is conducted within a station area. A user survey is administered to collect transit users' access mode choices and walking routes to the station. The survey results help identify two groups of street segments: one used by regular walkers and the other selected by habitual auto users/occasional walkers. The routes chosen by the two groups are quantitatively and graphically compared for walkability. The analyses show a physically measurable and quantitatively comparable difference between the routes' walkability and suggest criteria for walking-conducive transit walkability for station users. Specific design recommendations for improving street-level micro-walkability for future transit-oriented developments (TODs) are added along with a future research agenda.     

Informal motorbike taxi drivers and mobility injustice on Hanoi's streets. Negotiating the curve of a new narrative

The central government of the Socialist Republic of Vietnam and Hanoi's municipal authorities are enthusiastically embracing a series of plans and policies for the capital city to create a sustainable mega-city. This state imaginary privileges ‘modern’ mobilities, championing highways, a bus rapid transport system, and an elevated metro, while so called ‘traditional’ means of moving around the city such as motorbikes, bicycles, or cyclos are being strongly discouraged and increasingly marginalised. For example, Hanoi officials are implementing a step-wise ban on motorbikes from downtown streets by 2030, while the majority of the urban population travels by motorbike, with about five million motorbikes plying the city's streets. While such an approach not only creates mobility injustice for lower socio-economic residents of the city as a whole, it threatens to undermine the livelihoods of thousands of informal motorbike taxi drivers (locally known as xe ôm). In this article I engage with the emerging mobility injustice literature to explore how state discourses regarding urban modernisation are impacting the possibilities for Hanoi's xe ôm drivers to maintain access to city streets and viable livelihoods. These drivers must negotiate emerging and often conflicting state policies, their enforcement, as well as new app-based competitors, all of which challenge the equitable distribution of motility and produce important frictions. Nonetheless, xe ôm drivers draw on their agency and creativity during their daily routines to push back, while also creating new narratives regarding their vital role in maintaining neighbourhood security. We thus see how marginalised individuals are counteracting policies they consider unjust, even when this urban agenda is embedded in a politically socialist context.     

A GPS data-based analysis of built environment influences on bicyclist route preferences

This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named “CycleTracks.” The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.     

Managing severe airspace flow programs: The Airlines’ side of the problem

This paper presents a heuristic-based approach for minimizing airlines’ schedule disruptions and operation costs associated with severe airspace flow programs. It considers primary decisions made by flight dispatchers such as flight slot substitution and rerouting outside the boundaries of the flow-constrained area. A two-stage heuristic is developed. In the first, a linear approximation of the problem is used to screen inefficient routing and slot substitution alternatives. The second stage examines possible solution improvements through trading flight assignments for every pair of conflicting routes. A genetic algorithm is developed and used to benchmark the performance of the two-stage heuristic. In the algorithm, flight route and slot allocation schemes are modeled as chromosomes. The fitness of these chromosomes measures the magnitude of schedule disruption and overall operating cost. A set of experiments that compare the performance of the two heuristics considering airspace flow programs with different levels of severity is presented.     

On constituting cyclists as ‘hazards’

‘Hazard perception’ has become an integral part of novice driver education and training. Cyclists are often identified as one of many ‘hazards’ to look out for. We speculate that constituting cyclists as ‘hazards’, something that presents a danger or threat, may foster negative attitudes toward cyclists. Rather than accepting cyclists as ‘hazards’, our study examined the conditions that have made it possible to identify cyclists as ‘hazards’ in novice driver preparation. Informed by Michel Foucault's work on discursive practices, the analysis focused on the ‘road safety’ literature (1900–2017), the changing context in which road safety knowledge has been produced and the implications for the production of road space. This literature is important given the authority of scientific knowledge in western societies and its role in managing and governing populations. We found a shift in the middle of the twentieth century from drivers being identified as ‘hazards’ to drivers being identified as perceivers of ‘hazards’. At this time, researchers began studying drivers for their ability to recognise hazards: cyclists were routinely listed among the ‘hazards’ drivers should perceive. Out of 200 articles published on drivers' ‘hazard perception’ since the 1960s, one third categorised cyclists as ‘hazards’. Such research has informed the development and implementation of ‘hazard perception’ tests and, following Foucault, it participates in producing road space and shaping how drivers can think about themselves and other road users. While ‘scientific’ studies constitute cyclists as potential threats or sources of harm they lend authority to negative views of cyclists. We suggest ‘traffic participation’ as a more inclusive approach to driver education and training.     

Comparing strategies for addressing delivery shortages in stochastic demand settings

In logistics networks involving one supply point (depot) and several geographically dispersed demand points (e.g., retail stores), delivery shortages will result if the design of delivery routes ignores random period-to-period fluctuations in customer demands. Delivery shortages may be costly enough for the depot to seek strategies to prevent them. A requirement for rational comparison of strategies is quantifying their effects on total supply chain costs. Accurate distance prediction models are developed to help satisfy this prerequisite for the transportation cost element. These models are integrated into a comparison of strategies on the basis of how these strategies affect inventory and transportation. The focus of findings from the comparison involves identifying the information cost thresholds for accepting/rejecting a demand-responsive strategy. The study's implications for choosing a strategy are presented. ©     

Robust accessibility: Measuring accessibility based on travelers' heterogeneous strategies for managing travel time uncertainty

Uncertainties in travel times due to traffic congestion and delay are risks for drivers and public transit users. To avoid undesired consequences such as losing jobs or missing medical appointments, people can manage the risks of missing on-time arrivals to destinations using different strategies, including leaving earlier to create a safety margin and choosing routes that have more reliable rather than fastest travel times. This research develops a general analytical framework for measuring accessibility considering automobile or public transit travelers' heterogeneous strategies for dealing with travel time uncertainty. To represent different safety margin plans, we use effective travel time (expected time + safety margin), given specified on-time arrival probabilities. Heterogeneity in routing strategy is addressed using different Pareto-optimal routes with two main criteria: faster travel time vs. higher reliability. Based on various safety margin and routing strategy combinations, we examine how accessibility changes under varying safety margin plans and routing strategies. Also, we define and measure robust accessibility: geographic regions that are accessible regardless of the safety margin planning and routing strategy. Robust accessibility can provide a conservative and reasonable view of accessibility under travel time uncertainty. To demonstrate the applicability of the methods, we carry out an empirical study on measuring the impacts of new transit service on healthcare accessibility in a deprived neighborhood in Columbus, Ohio, USA.     

Effect of concentration in airline market on Spanish airport technical efficiency

This paper tries to measure the effect of airline market concentration on airport technical efficiency. With this aim, a Stochastic Frontier Analysis (SFA) is applied, estimating with a one-step procedure technical efficiency and the effect of airlines' market power on that efficiency. Results suggest that when airports are lowly concentrated increasing concentration reduces such inefficiencies. However, this effect practically disappears when airports are highly concentrated. Additionally, the government's policies to improve airports' performance seems to have a positive effect in the short run.     

Performance evaluation of China's air routes based on network data envelopment analysis approach

Air routes are among the most important elements of civil aviation transport. Airlines' operations are mainly dependent on the structure and layout of air routes. This paper first divides the production process of air routes into two stages, allocation and transport, based on air route operational characteristics. Then, two network data envelopment analysis (DEA) models are proposed to analyze the efficiency of the system, allocation, passenger transport, and freight transport of 477 air routes. The research result demonstrates that the different constraints on intermediate measure in the network DEA models do affect the air routes’ efficiency significantly; Most air routes have high allocation efficiency and passenger transport efficiency, while they have low freight transport efficiency. Furthermore, the efficiencies of 82 airports are also analyzed after aggregating the efficiencies of the air routes.