Public Transit Lines Research Articles

Mobility and transit segregation in urban spaces

Segregation is a highly nuanced concept that researchers have worked to define and measure over the past several decades. Conventional approaches tend to estimate segregation based on residential patterns. However, the residential dimension does not fully comprise individuals’ interactions with their environment and, consequently, can misrepresent individuals’ lived experiences. To address this gap, we analyse how segregation extends to other dimensions of the urban life. We accomplish this by using the Index of Concentration at the Extremes (ICE) to measure socioeconomic segregation at amenities and on public transit lines. Moreover, we consider the pivotal role that transport plays in democratising access to opportunities. Using transport networks, amenity visitations, and census data, we leverage agent-based models to approximate socioeconomic composition at amenities and on transit lines. Consequently, we can estimate socioeconomic segregation within the United States, for various aspects of urban life. We find that neighbourhoods that are segregated in the residential domain tend to exhibit similar levels of segregation in amenity visitation patterns and transit usage, albeit to a lesser extent. Moreover, we discover that low-income neighbourhoods experience a greater decrease from residential to amenity segregation, than their high-income segregated counterparts, highlighting how mobility can be used as a tool for overcoming residential inequalities, given the proper infrastructure. We identify inequalities embedded into transit service, which impose constraints on residents from segregated areas, limiting the neighbourhoods that they can access within an hour to areas that are similarly disadvantaged. By exploring socioeconomic segregation from a transit perspective, we underscore the importance of conceptualising experiential segregation, while also highlighting how transport systems can contribute to a cycle of disadvantage.

Diseconomies of scale and subsidies in urban public transportation

Subsidization of urban public transportation systems is often motivated by economies of scale and second-best considerations such as an underpriced road alternative. We model a public transit line subject to frictions between users (in-vehicle crowding), users and vehicles (boarding and alighting delays), and vehicles (congestion). We derive the profit- and welfare-maximizing provisions of supply. We show that if demand exceeds a first threshold, the system enters a congested regime and service frequency decreases. Beyond a second threshold, the strong deterioration of service quality causes the transit line to operate under diseconomies of scale, calling for a Pigouvian tax instead of a subsidy. This finding, which goes against Mohring’s classical rule (1972), holds with an untolled road alternative, provided that the network structure remains constant. We estimate the model for the London Piccadilly line and find evidence of substantial diseconomies of scale during the morning peak, adding up to −1.49 £/trip for the observed provision of service quality (-0.61 £/trip at optimum). These results question current subsidy policies for the busiest transit lines.

Travel demand management: The solution to public transit congestion? An ex-ante evaluation of staggered work hours schemes for the Paris region

This paper investigates the congestion relief potential of staggered work hours (SWH) schemes for public transit. An ex-ante evaluation framework is developed, which combines a hybrid assignment model with a travel demand management module to simulate the impact of SWH schemes on travel demand and public transit congestion. The key performance indicators capture not only congestion relief benefits, but also rescheduling costs for users. The methodology is applied to the RER A heavy rail line in Paris, the busiest public transit line in Europe. We find that SWH schemes generate congestion relief benefits, as intended, even matching up to telework policies. Yet, such benefits remain moderate, adding up to 20% of total crowding costs for the morning peak period at most. Moreover, substantial rescheduling costs are involved: decreasing the total time standing by 1 h implies shifting fifteen trips by the same amount of time. Regarding policy design, our results suggest that shifting few users by a large amount of time is usually more efficient than shifting many users by a smaller amount of time; the latter may even prove counterproductive by merely transferring the peak to some other time in the morning. We also find for the RER A that focusing the SWH scheme on a single station - the biggest trip attractor - yields benefits similar to applying the scheme over the whole line (for a similar level of effort in terms of total timeshift). The developed framework is intended to provide guidance as how to improve the design of future SWH schemes, in particular in times of social distancing and need for reduced crowding.

Study of traffic volumes

"The area of transportation planning deals with transportation facilities (usually streets, roads, walkways, bike lanes, and public transit lines)." It is vital to assess the present state of traffic volume and anticipate the future state of traffic volume in this field traffic volume survey. The purpose of traffic volume studies is to determine the number, movement, and categories of highway vehicles in a given region. An attempt was made to grasp traffic patterns throughout various time periods using data collection. The characteristics of the traffic flow at that crossroads also have an impact on traffic control. As a consequence, the study's findings are valuable in controlling traffic at the intersection and giving some corrective measures to improve traffic safety in the region. Based on the findings, corrective actions such as road widening or enhanced public transit may be recommended.

Improved Breadth First Search For Public Transit Line Search Optimization

People in general find it difficult to determine the transportation route, because to get to one destination there are many alternative paths that must be passed. This study aims to model the search for alternative bus route routes that are faster to produce routes that must be passed. The method used in this study is Improved Breadth first search by modifying BFS so that its performance is improved in producing route search completion. The improved BFS method is basically the same as BFS doing a level-by-level search stop if a false finish point is found. As the experiment above with a starting point of 175 and an end point of 54 the BFS algorithm takes 27 seconds 564 milliseconds, while the Improve BFS algorithm takes 171 milliseconds. The results showed that improved BFS can improve the performance of the BFS method. Research can be a model to be applied to other optimal route finding cases.

Coordinating feeder and collector public transit lines for efficient MaaS services

Coordinating the schedules of feeder and collector public transit lines can reduce the passenger travel times. With advances in smart mobility, mobility-as-a-service (MaaS) schemes allow passengers to book a combined ticket for all their trip legs. This detailed information about the origins and destinations of door-to-door trips offers the opportunity to coordinate the schedules of public transport lines to reduce the passenger travel times. In this study, we model the coordination problem of feeder and collector lines by explicitly considering the regularity of the feeder lines and the transfer times of passengers. The coordination problem is modeled as a nonlinear non-convex problem and reformulated to an easy-to-solve convex optimization problem. Because of the travel times uncertainty, we also introduce a stochastic optimization formulation based on the sample average approximation approach. We test the performance of our approach in a case study with feeder and collector lines in Singapore showing an improvement potential of 5%–10% in passenger travel times. • A novel, easy-to-solve model for the coordination of feeder and collector transit lines. • Explicit consideration of door-to-door travel times for efficient MaaS services. • Improvement potential of 5%–10% even under uncertain demand conditions.

Insectivore art in transit

Art reflects nature in a monumental way on the new section of a LYNX public transit line in Charlotte, North Carolina.

Morning commuting pattern and crowding pricing in a many-to-one public transit system with heterogeneous users

This paper examines the morning commuting flow patterns in a many-to-one public transit line. Multi-class commuters with different degrees of sensitivity towards crowding are considered. At user equilibrium, trains arriving at the destination at approximately the work start time are found to be either more or less congested at the intermediate stations, depending on the spatial distribution of commuter class at each station. In addition, the system optimal crowding fare is found to be train-dependent and may fluctuate over time at each station. Finally, the theoretical properties of morning commuting flow patterns and crowding fare are illustrated through numerical examples.

First-Mile-Last-Mile Collector-Distributor System using Shared Autonomous Mobility

High costs of owning fully-automated or autonomous vehicles (AVs) will fuel the demand for shared mobility, with zero driver costs. Although sharing sounds good for the transport system, congestion can easily rise without adequate policy measures. Many or all public transit lines will continue to exist, and carefully-designed policies can be implemented to make good use of fixed public assets, like commuter- and light-rail lines. In this study, a shared AV (SAV) fleet is analyzed as a potential solution to the first-mile-last-mile (FMLM) problem for access to and from public transit. Essentially, SAVs are analyzed as collector-distributor systems for these mass-movers and compared with a door-to-door (D2D) service. Results from an agent-based simulation of Austin, Texas, show that SAVs have the potential to help solve FMLM transit problems when fare benefits are provided to transit users. Restricting SAV use for FMLM trips increases transit coverage, lowers average access and egress walking distance, and shifts demand away from park-and-ride and long walk trips. When SAVs are available for both D2D use and FMLM trips, high SAV fares help maintain transit demand, without which the transit demand may decrease significantly, affecting the transit supply and the overall system reliability. Policy makers and planners should be wary of this shift away from transit and may be able to increase transit usage using policies tested in this study.

Trial-and-error operation schemes for bimodal transport systems

We concern the modal choice of commuters in a transport system comprising a highway, which is only used by autos, in parallel to a transit line, which is only used by buses. In the transport system, the in-vehicle congestion of passengers in bus carriages is treated as a negative externality cost of affecting the modal choice of commuters and commuters choose their travel modes according to the perceived travel costs of transport modes. We propose two trial-and-error operation schemes for the transport system without resorting to both the function of in-vehicle congestion costs and the distribution of perceived travel cost errors. In the first operation scheme, the manager (or the government) determines the transit fare charged from (or financial subsidy to) bus users from period to period so as to minimize the system time cost of the transport system. The second operation scheme is established from the viewpoint of a private firm that operates the public transit line. The operator determines the transit fare and bus run frequency from period to period in order to maximize its operating profit. Moreover, we demonstrate the effectiveness of the two operation schemes for optimizing the system time cost and the operating profit by both theoretical analyses and numerical examples.

A Geospatial Analysis of Freestanding and Hospital Emergency Department Accessibility via Public Transit.

IntroductionEmergency departments (ED) are an important source of care for underserved populations and represent a significant part of the social safety net. In order to explore the effect of freestanding emergency departments (FSED) on access to care for urban underserved populations, we performed a geospatial analysis comparing the proximity of FSEDs and hospital EDs to public transit lines in three United States (U.S.) metropolitan areas: Houston, Denver, and Cleveland.MethodsWe used publicly available U.S. Census data, public transportation maps obtained from regional transit authorities, and geocoded FSED and hospital ED locations. Euclidean distance from each FSED and hospital ED to the nearest public transit line was calculated in ArcGIS. We calculated the odds ratio (OR) of an FSED, relative to a hospital ED, being located within 0.5 miles (mi) of a public transit line using logistic regression, adjusting for population density and median household income and with error clustered at the metropolitan statistical area (MSA) level.ResultsThe median distance from FSEDs to public transit lines was significantly greater than from hospital EDs across all three markets. In Houston, Denver, and Cleveland, the median distance between FSEDs and public transit lines was greater than from hospital EDs by 1.0 mi, 0.2 mi, and 1.6 mi, respectively. The OR of a public transit line being located within 0.5 mi of an FSED, as compared with a hospital ED, across all three MSAs was 0.21 (95% confidence interval [CI], 0.13–0.34) unadjusted and 0.20 (95% CI, 0.11–0.40) adjusted for population density and median household income.ConclusionIn comparison with hospital EDs, FSEDs are located farther from public transit lines and are less likely to be within walking distance of public transportation. These findings suggest that FSEDs are unlikely to directly increase access to care for patients without private means of transportation. Further research is necessary to explore both the direct and indirect impact of FSEDs on access to care, potentially through effects on hospital ED crowding and overall healthcare expenditures, as well as the ultimate role and responsibility of FSEDs in improving access to care for underserved populations.

Employer-paid parking, mode choice, and suburbanization

This paper constructs a theoretical model that facilitates analysis of the effects of employer-paid parking on mode choice, road investment and suburbanization. The model simplifies urban space by dividing it into two zones (islands), center and suburbs, which are connected by a congested road and a public-transit line. Each road commuter requires an allotment of CBD land for parking, and because the central zone’s area is fixed, parking land reduces the amount available for central residences and CBD production. The model characterizes optimal resource allocation from the perspective of a social planner. The planning solution can be decentralized, which requires employee- rather than employer-paid parking, congestion tolls, and a tax (subsidy) to offset the road capacity deficit (surplus). The analysis then considers the effect of switching to employer-paid parking, with the burden of parking costs shifting from road users to employers, thus reducing the wage for all workers. This switch inefficiently increases road usage and capacity investment, while spurring an inefficient increase in suburbanization.

Setting services in public transit lines in short time periods under time-varying demand

Abstract: This paper focuses on a mathematical programming based model for setting the schedule of a given number of services on a public transportation network. The structure of the model is that of a time-expanded or diachronic network, where origin to destination flows vary dynamically over a short time horizon (several hours) and are assumed to be known deterministically. The model basically aims to minimize the total travel time of passengers during the time horizon by properly setting the lag times between services on the lines and thereby accommodating conveniently the schedules of the services on different lines in order to enhance transfers. Two different types of diachronic networks are considered, in which three basic algorithmic alternatives have been tested: a heuristic method based on the classical projected gradient, Benders decomposition, and a combination of both. Among other applications, the model can potentially be applied in operational aspects for disruption recovery in Rail-Rapid Transit and Suburban Railway systems by using bus shuttles or auxiliary bus lines. The computational viability of the model, in terms of adequate response time, is shown using test networks of auxiliary bus lines. Its computational performance in readjusting schedules for larger suburban rail systems is also evaluated.

Employer-Paid Parking, Mode Choice, and Suburbanization

This paper constructs a theoretical model that facilitates analysis of the effects of employer-paid parking on mode choice, road investment and suburbanization. The model simplifies urban space by dividing it into two zones (islands), center and suburbs, which are connected by a congested road and a public-transit line. Each road commuter requires an allotment of CBD land for parking, and because the central zone’s area is fixed, parking land reduces the amount available for central residences and CBD production. The model characterizes optimal resource allocation from the perspective of a social planner. The planning solution can be decentralized, which requires employee- rather than employer-paid parking, congestion tolls, and a tax (subsidy) to offset the road capacity deficit (surplus). The analysis then considers the effect of switching to employer-paid parking, with the burden of parking costs shifting from road users to employers, thus reducing the wage for all workers. This switch inefficiently increases road usage and capacity investment, while spurring an inefficient increase in suburbanization.

The OD matrix estimation model of passenger flow based on the POI around the bus station

In this paper, an optimised model that is based on the existing flow of bus passengers OD estimation model is established sufficiently. First of all, by analysing the types and quantities related to the point of interest around the bus station, the intensity of land utilisation surrounding the bus station is identified, and then combining this factor with the principle that the probability of the number of travel stations obeys the characteristics of Poisson distribution, a new improved flow of bus passengers OD estimation model is set up eventually. At last, comparing the estimation results of OD from the former and the improved model through the example test, the result shows that the improved flow of bus passengers OD estimation model is more accurate than before, so that this new model can provide more reliable and practical data support for optimisation of public transit line network.

Development of Urban Public Transit Network Structure Integrating Multi-Class Public Transit Lines and Transfer Hubs

Development of Urban Public Transit Network Structure Integrating Multi-Class Public Transit Lines and Transfer Hubs

Layout Optimization Algorithm and Application for Urban Public Transit Line

Layout Optimization Algorithm and Application for Urban Public Transit Line

Locating optimal timetables and vehicle schedules in a transit line

This paper deals with the Transit Network Timetabling and Scheduling Problem (TNTSP) in a public transit line. The TNTSP aims at determining optimal timetables for each line in a transit network by establishing departure and arrival times of each vehicle at each station. We assume that customers know departure times of line runs offered by the system. However, each user, traveling after or before than their desired travel time, will give rise to an inconvenience cost, or a penalty cost if that user cannot be served according to the scheduled timetable. The provided formulation allocates each user to the best possible timetable considering capacity constraints. The problem is formulated using a p-median based approach and solved using a clustering technique. Computational results that show useful applications of this methodology are also included.

Application of Data Analysis of Public Transit Passenger Flow in Line Classification

Applications of data analysis technology in analysis of public transit passenger flow and studying the classification of public transit lines using clustering analysis method are introduced in this paper. Public transit lines in Changsha, as a case, is studied, which if of references for optimizing the operation management of public transit.

Algorithms for central-median paths with bounded length on trees

The location of path-shaped facilities on trees has been receiving a growing attention in the specialized literature in the recent years. Examples of such facilities include railroad lines, highways and public transit lines. Most of the papers deal with the problem of locating a path on a tree by minimizing either the maximum distance from the vertices of the tree to the facility or of minimizing the sum of the distances from all the vertices of the tree to the path. However, neither of the two above criteria alone capture all essential elements of a location problem. The sum of the distances criterion alone may result in solutions which are unacceptable from the point of view of the service level for the clients who are located far away from the facilities. On the other hand, the criterion of the minimization of the maximum distance, if used alone, may lead to very costly service systems. In the literature, there is just one paper that considers the problem of finding an optimal location of a path on a tree using combinations of the two above criteria, and efficient algorithms are provided. In particular, the cases where one criterion is optimized subject to a restriction on the value of the other are considered and linear time algorithms are presented. However, these problems do not consider any bound on the length or cost of the facility. In this paper we consider the two following problems: find a path which minimizes the sum of the distances such that the maximum distance from the vertices of the tree to the path is bounded by a fixed constant and such that the length of the path is not greater than a fixed value; find a path which minimizes the maximum distance with the sum of the distances being not greater than a fixed value and with bounded length. From an application point of view the constraint on the length of the path may refer to a budget constraint for establishing the facility. The restriction on the length of the path complicates the two problems but for both of them we give O( n log 2 n) divide-and-conquer algorithms.