Tag Archives: transit

Integrated bus-bike system

After much delay, the last paper Sida and I wrote together came out last week in Transportation Research Part C.   Growing out of the last chapter of Sida’s PhD dissertation, the first draft of the paper was completed before he went back to China in the summer of 2020, at the height of COVID19 pandemic.   In part, the long delay was due to Sida’s transition to his new job at Beijing Jiaotong University.   I am glad he pressed on despite the early setbacks and eventually published the paper  in a descent journal.  Here is the abstract for those who wonder what is an integrated bus-bike system.


Abstract: This paper examines the design of a transit system that integrates a fixed-route bus service and a bike-sharing service. Bike availability – the average probability that a traveller can find a bike at a dock – is modelled as an analytical function of bike utilization rate, which depends on travel demand, bike usage and bike fleet size. The proposed system also recognizes the greater flexibility provided by biking. Specifically, a traveller can choose between the closest bus stop and a more distant stop for access, egress or both. Whether the closest stop is a better choice depends on the relative position of the traveller’s origin and destination, as well as system design parameters. This interdependence complicates the estimation of average system cost, which is conditional on route choice. Using a stylized analysis approach, we construct the optimal design problem as a mixed integer program with a small number of decision variables. Results from our numerical experiments show the integrated bus-bike system promises a modest but consistent improvement over several benchmark systems, especially in poorer cities with lower demand density. We find a large share of travellers, more than 20% in nearly all cases tested, opt not to use the nearest bus stop in an optimally designed system. The system also tends to maintain a high level of bike availability: the probability of finding a bike rarely drops below 90% except in very poor cities.

The sustainability appeal of URT

Few would deny that public transit has an important role to play in any sensible solutions to the transportation’s sustainability problem. Yet, the consensus often dissolves at the question of how. A case in point concerns urban rail transit (URT), which has expanded rapidly in recent decades.   The ongoing debate about URT has been fueled by inconclusive, sometimes contradictory, empirical evidence reported in the literature.  Has URT consistently reduced driving and/or auto ownership to affirm its appeal to sustainability? We set out to address this question head-on in this study.

You may read the abstract below, and download a preprint here.


Abstract: Urban rail transit (URT) has expanded rapidly since the dawn of the century. While the high cost of building and operating URT systems is increasingly justified by their presumed contribution to sustainability — by stimulating transit-oriented development, promoting the use of public transportation, and alleviating traffic congestion — the validity of these claims remains the subject of heated debates. Here we examine the impact of URT on auto ownership, traffic congestion, and bus usage and service, by applying fixed-effects panel regression to time series data sets compiled for major urban areas in China and the US. We find that URT development is strongly and negatively correlated with auto ownership in both countries. This URT effect has an absolute size (as measured by elasticity) in China three times that in the US, but is much larger in the US than in China, relative to other factors such as income and unemployment rate. Importantly, the benefit transpires only after a URT system reaches the tipping point that unleashes the network effect.  Where this condition is met, we estimate about 14,012 and 31,844 metric tons of greenhouse gas emissions can be eliminated each year in China and the US, respectively, for each additional million URT vehicle kilometers traveled. We also uncover convincing evidence of cannibalization by URT of bus market share in both countries. However, rather than undermining bus services, developing URT strongly stimulates their growth and adaptation. Finally, no conclusive evidence is found that confirms a significant association between URT and traffic congestion. While traffic conditions may respond positively to URT development in some cases, the relief is likely short-lived.

Ethics-Aware Transit Design

In this paper we proposed a corridor transit design model that places accessibility and equity at the center of the trade-off. By guiding transit design with ethical theories, it promises to improve vertical equity. We reviewed and examined four different ethical principle but were focused on the utilitarian principle (the status quo) and John Rawls’ difference principle (a form of egalitarianism). The main findings from our analysis of the design models are summarized as follows.

  • When the transit service is homogeneous in space, the utilitarian design model and the egalitarian design model are mathematically equivalent. Thus, they always produce identical designs for all forms of the opportunity distribution.
  • With supply heterogeneity, the egalitarian design has a prominent equity-enhancing effect, whereas the utilitarian design tends to exacerbate inequity, especially in presence of large innate inequality.
  • Correcting innate inequality by applying the egalitarian principle often entails interventions that appear more “discriminatory” than the status quo. Whether such distributive measures are justified, the appearance of unfairness can be met with skepticism, if not outright opposition, from the general public.
  •  Our ability to promote equity is restricted not only by the resources available but also by the structure of the problem at hand. The difference principle is useful because it defines the upper limit of equity that we may strive to reach but should not exceed.

It is worth recalling the egalitarian design based on the difference principle tends to reduce the total accessibility of all residents, compared to the incumbent design regime of utilitarianism. When innate inequality is large, the loss of accessibility can be substantial, up to 40\% according to our experiments. This, of course, is hardly a surprise, given the primary concern of the difference principle is the distributive justice, not the total utility. One thing is clear though: the benefits to the most disadvantaged could come at a hefty price to society writ large. Steven Dubner, the host of the popular podcast Freakonomics, likes to quip,

Economists know the price of everything but the value of nothing.

No doubt the same can be said about many if not most engineers. In some sense, our study constitutes an attempt to price social values in engineering practice. To be sure, these values are priceless to many an advocate, who would be quick to point out that the obsession with pricing everything is precisely what got us here in the first place. However, understanding the consequence of imposing certain values in engineering systems is still a crucial task, if only because we always need to secure public support or determine affordability.

The work is partially funded by Northwestern University’s Catalyst fund and NSF’s Smart and Connected Community (S&CC) Planning
Grant.  A prerprint of the paper may be downloaded here.

Paired-Line Hybrid Transit

Paired-Line Hybrid Transit was the first in a series of “hybrid-transit” studies conducted by my group using a stylized design model.  This line of work, funded by an National Science Foundation between   2013 and 2016, was initiated by Peng Chen in his PhD thesis.  The main idea is to pair a demand-adaptive service with a fixed-route service so that the transit system can leverage the advantages of both while avoiding their drawbacks.  The paper was published in Transportation Research Part B in 2017.

For preprint, check  Hybrid Transit System Design_Journal_2.0


Abstract: This paper proposes and analyzes a new transit system that integrates the traditional fixed-route service with a demand-adaptive service. The demand-adaptive service connects passengers from their origin/destination to the fixed-route service in order to improve accessability. The proposed hybrid design is unique in that it operates the demand-adaptive service with a stable headway to cover all stops along a paired fixed-route line. Pairing demand-adaptive vehicles with a fixed-route line simplifies the complexity of on-demand routing, because the vehicles can follow a more predictable path and can be dispatched on intervals coordinated with the fixed-route line. The design of the two services are closely
coupled to minimize the total system cost, which incudes both the transit agency’s operating cost and the user cost. The optimal design model is formulated as a mixed integer program and solved using
a commercially available metaheuristic. Numerical experiments are conducted to compare the demand adaptive paired-line hybrid transit (DAPL-HT) system with two related transit systems that may be considered its special cases: a fixed-route system and a flexible-route system. We show that the DAPL-HT system outperforms the other two systems under a wide range of demand levels and in various scenarios of input parameters. A discrete-event simulation model is also developed and applied to confirm the correctness of the analytical results.

Hyperbush

Hyperbush Algorithm for Strategy-based Equilibrium Traffic Assignment Problems

This recent paper extends the concept of bush to hyperbush and uses it devise a new class of algorithms for strategy-based traffic equilibrium assignment problem, of which frequency-based transit assignment is an archetype.  One of the longest papers that I’ve ever written (nearly 50 pages), the paper just appeared online in Transportation Science.    Here is a preprint  Hyperbush.


Strategy-based equilibrium traffic assignment (SETA) problems define travel choice broadly as a strategy rather than a simple path. Travelers navigating through a network based on a strategy end up following a hyperpath. SETA is well suited to represent a rich set of travel choices that take place en-route at nodes, such as transit passengers’ transfer decision, truckers’ bidding decision and taxi drivers’ re-position decision. This paper recognizes and highlights the commonalities among classical and emerging SETA problems and proposes to unify them within a same modeling framework, built on the concept of hypergragh. A generic hyperbush algorithm (HBA) is developed by decomposing a hypergraph into destination-based hyperbushes. By constructing hyperbushes and limiting traffic assignment to them, HBA promises to obtain more precise solutions to larger instances of SETA problems at a lower computational cost, both in terms of CPU time and memory consumption. To demonstrate its generality and efficiency, we tailor HBA to solve two SETA problems. The results confirm HBA consistently outperforms the benchmark algorithms in the literature, including two state-of-the-art {hyperpath-based} algorithms. To obtain high-quality equilibrium solutions for SETA instances of practical size, HBA runs up to five times faster than the best competitor with a fraction of its memory consumption.

Transit Design in Response to a Global Pandemic

Optimizing Operational Strategies for Mass Transit Systems in Response to a Global Pandemic

This is one of my COVID inspired research projects that was started in 2020.  The idea is that, in order to operate safety during a pandemic, transit agencies might have to adjust their operational strategies, in terms of service frequency and capacity.  The underlying tradeoff we are trying to explore here is that between the benefit of frequently testing drivers (as it reduces the transmission risk) and the cost of lowering the number of passengers allowed in buses, subject to the need to maintain certain safety standard, measured by infection risks. A novelty of the work is a physical model aiming to estimate infection risks based on vehicle size/type, service capacity and a few external risk factors.

The paper is currently under revision at Journal of Transportation Research Part A.   Please download a preprint here.


Abstract              This study analyzes the risk involved in riding various transit modes during and after a global pandemic. The goal is to identify which factors are related to this risk, how such a relationship can be represented in a manner amenable to analysis, and what a transit operator can do to mitigate the risk while running its service as efficiently as possible. The resulted infection risk model is sensitive to such factors as prevalence of infection, baseline transmission probability, social distance, and expected number of human contacts. Built on this model, we formulate, analyze and test three versions of a transit operator’s design problem. In the first, the operator seeks to jointly optimize vehicle capacity and staff testing frequency while keeping the original service schedule and satisfying the infection risk requirement. The second model assumes the operator is obligated to meet the returning demand after the peak of the pandemic. The third allows the operator to run more than one transit line and to allocate limited resources between the lines, subject to the penalty of unserved passengers. We find: (i) The optimal profit, as well as the testing frequency and the vehicle capacity, decreases when passengers expect to come in close contact with more fellow riders in a trip; (ii) Using a larger bus and/or reducing the testing cost enables the operator to both test drivers more frequently and allow more passengers in each bus; (iii) If passengers weigh the risk of riding bus relative to taxi, a higher prevalence of infection has a negative effect on transit operation, whereas a higher basic transmission probability has a positive effect; (iv) The benefit of improving service capacity and/or testing more frequently is limited given the safety requirement imposed. When the demand rises beyond the range of the capacity needed to maintain sufficient social distancing, the operator has no choice but to increase the service frequency; and (v) In the multi-line case, the lines that have a larger pre-pandemic demand, a higher penalty for each unserved passenger, or a greater exposure risk should be prioritized.