Multimodal Transit Research Articles

Distribution Optimization Model for Passenger Departure via Multimodal Transit

International airports in China have become a complex hub between airport and multimodal transit stations. Dissimilar passenger departure demands in different transit mode cause wide gaps among departure times from airport to these modes. In this context, hub managers need to balance the distribution of air passengers to transit modes in order to reduce departure delays and alleviate the congestion in transit stations, even though they cannot change the operating plan of airport or transit stations. However, few research efforts have addressed this distribution. Therefore, we developed a distribution optimization model for passenger departure that minimizes the average departure time and is solved by Genetic Algorithm. To describe differences in passenger choices, without taking into consideration the metropolitan transportation network outside the airport, we introduced the concept of rigid and elastic departures. To reflect the tendency of elastic passengers to choose different transit modes, we assume that the passengers change to other modes in different proportions. A case revealed that the presence of rigid passengers allows managers to partly balance the distribution of passengers and improve the average departure time. When the volume of passengers approaches the peak volume, the optimized distribution significantly improves the departure time.

Cascading Failures in Weighted Complex Networks of Transit Systems Based on Coupled Map Lattices

Study on the vulnerability and robustness of urban public transit networks (PTNs) has great implications for PTNs planning and emergency management, particularly considering passengers’ dynamic behaviors. We made a complex weighted network analysis based on passenger flow for Beijing’s bus stop network and multimodal transit network coupled with bus and urban rail systems. The analysis shows that there are small-world or scale-free properties in these two networks, which make them display different robustness under link or node failures. With consideration of the dynamic flow redistribution, we propose a model based on coupled map lattices to analyze the cascading failures of these two weighted networks. We find that the dynamic flow redistribution can significantly improve the tolerance of small-world or scale-free PTN against random faults. Because of the coupling of bus and rail systems, the multimodal network with scale-free topology and flow distribution structures displays an increasing tolerance even against intentional attack; however, its cascade is also much more intense once the failure is triggered. We find some thresholds of topological and flow coupling strength in the spreading process, which can be exploited to develop strategies to control cascade failures.

Multimodal Transit Connectivity for Flexibility in Extreme Events

Transportation services and their networks are vital in providing users with flexibility under both normal and extreme conditions. The availability of alternatives is essential in emergencies to provide critical support services for evacuation and supplies, yet disasters often impair transportation's ability to provide these services. In the populous and dense New York and New Jersey area, weather disasters often set records, have occurred historically, and are expected to recur. Vulnerabilities particularly affect disadvantaged populations. Multimodal connectivity for rail and bus transit is evaluated for New York City and several northeastern New Jersey cities for passenger flexibility and risk reduction in emergencies. The U.S. Department of Transportation's Intermodal Passenger Connectivity Database is evaluated as a general multimodal connectivity context. For rail transit stations, bus counts are computed for each station for buses stopping within a 0.1-mi radius; this requirement reflects the needs of less mobile users. Geographic information systems are used for database construction for statistical analysis with publicly available transit and census databases. The New York City statistical analyses of census tracts within which stations are located show variable bus connectivity for different stations and suggest availability by poverty level. A subanalysis for New York City's terminus stations shows greater bus connectivity and different transit activity characteristics. Results provide ways of operationalizing connectivity for transit resilience as critical infrastructure. Methods can be extended to other areas. Recommendations for flexibility in terms of passenger multimodality are provided.

Integrated Frequency Allocation and User Assignment in Multimodal Transit Networks

This paper presents an integrated solution method to the frequency-setting problem using optimization and assignment simulation. With a bilevel solution framework, an optimization problem is run at the upper level under the assumption that the total transit demand is fixed. The objective is to maximize wait time savings under the budget, fleet size, vehicle load, and policy headway constraints. At the lower level, an assignment and simulation algorithm is run; the algorithm models the demand response to the new frequency setting and transmits updated ridership and flow values to the upper level. The procedure is repeated until the improvement in the wait time savings converges. The platform is tested on the Chicago Transit Authority network in Illinois for the morning peak. The wait time savings in this experiment are converging and are found to be comparable with the results of a stand-alone frequency-setting algorithm that finds optimal solutions. Results are comparable with the optimal results of a stand-alone platform introduced in another study that modeled the demand response locally by using elasticities as opposed to networkwide modeling using assignment. The integrated platform can be used for medium-term strategic and long-term planning decisions.

InKoPoMoVer – Cooperative Positioning for Real-time User Assistance and Guidance at Multi-modal Public Transit Junctions

AbstractThe study ‘Cooperative Positioning for Real-time User Assistance and Guidance at Multi-modal Public Transit Junctions’ (InKoPoMoVer) aims at a better understanding of passenger movement at multi-modal transit situations for providing improved passenger assistance and guidance. By using a novel Differential Wi-Fi (DWi-Fi) approach through intelligent Cooperative Positioning (CP), algorithms can be generated, which considerably increase the accuracy of person tracking, allowing for the derivation of movement patterns. Due to user support smoothly transit at the stations is enabled, thus the gap in current multimodal transport information systems where routing is not performed at the junction itself is closed. Addressing ethical and usability aspects will ensure user-friendly results. In this article, the concept of transit assistance is introduced followed by a comprehensive discussion of the suitable CP localization techniques and sensors as well as the implementation strategy.

Efficiency Comparison of Bus Operators in Delhi

There is an apparent inefficiency in the workings of the primary bus operators in New Delhi. The paper focuses on labor inefficiency and compares the compensation schemes offered to the conductors of the two major bus operators in Delhi- Delhi Transport Corporation (DTC) and Delhi Integrated Multi-Modal Transit System (DIMTS). Such a study which compares the labour efficiency, and incentive schemes offered by these two primary bus services has not been done before. The results from the interview of bus conductors of DTC and DIMTS are used to establish the presence of moral hazard. The wide literature on the principal-agent problem is then examined, to find a wage scheme for DTC employees, which provides adequate incentives to them to perform efficiently. Hart and Holmstrom’s (1987) non-linear wage model is suggested in this case study to eliminate the problem of moral hazard. It is also found that the wage scheme offered by DIMTS is more efficient than that of DTC.

Finding Least Cost Hyperpaths in Multimodal Transit Networks

This paper presents a least cost hyperpath algorithm that captures the complexities that arise in a transit network because of the number of transfers, the standing and overcrowding penalties, the availability of walking and biking in addition to the transit modes, and the mode-specific limitations such as availability of bike parking. The problem was formulated as a mathematical program, and then a hybrid label setting–correcting algorithm was proposed as a solution. The multi-modal time- and approach-dependent algorithm does not require spatial or temporal expansion of the network; this feature results in good computational performance for large-scale applications. Scenario runs performed on the large-scale Chicago Transit Authority network, in Illinois, validate the accuracy and performance of the algorithm.

Examining the Influence of Internal Service Characteristics on Social Benefits of Multimodal Transit

Recent research has demonstrated that certain transit planning decisions about internal performance factors appeared to serve as successful strategies for improving transit ridership and productivity. However, the research has not assessed overall social benefits or the operating and capital costs of implementing such strategies. The influence of several transit performance factors, internal and external, on the annual net benefits generated by 13 U.S. bus and light rail transit systems was investigated with data from 2001 to 2011. The evaluation started with a benefit–cost analysis, which estimated net benefits (equal to agency revenues plus indirect social benefits minus operating and capital costs). Then, the statistical relationship between specific performance factors and the average net benefits generated by the systems studied was evaluated with a panel regression model. Results indicated that high frequency and service density positively influenced net benefits, but network decentralization (i.e., volume of service headed out of the central business district) played an insignificant role. Surprisingly, only one of several external factors, reflecting congestion volume, appeared to be correlated significantly with the benefits. These results provide new insight into the outcomes of planning decisions on the basis of internal factors and imply that the costs of certain transit service enhancements may be outweighed by increased revenues and indirect benefits. The results also indicate that bus and light rail systems can improve their economic feasibility by adjusting specific types of internal service characteristics.

All-Door Boarding in San Francisco, California

For generations, the transit industry has had to balance the desire for faster boarding with the need to collect fares. On July 1, 2012, the San Francisco Municipal Transportation Agency (SFMTA) in California addressed this challenge by becoming North America's first multimodal transit operator to implement all-door boarding systemwide. Customers with valid fare media may enter through any door of any vehicle at any time. Unlike other transit providers that used proof of payment, SFMTA still allowed customers to pay cash on board vehicles at surface stops, thus avoiding the expenses associated with wayside ticket vending machines. San Francisco's operating environment provided ideal conditions to demonstrate the potential benefits of all-door boarding. Serving the nation's second-densest major city with crowded transit vehicles largely operating in mixed traffic, SFMTA must make efficient use of every minute in revenue service and cannot afford excessive time at stops. Two years after the policy's implementation, a comprehensive and multi-factor analysis revealed incremental improvements in dwell times and fare compliance. Overall bus speeds increased slightly despite ridership growth and a population and employment boom.

A tool for measuring and visualizing connectivity of transit stop, route and transfer center in a multimodal transportation network

Agencies at the federal, state and local level are aiming to enhance the public transportation system (PTS) as one alternative to alleviate congestion and to cater to the needs of captive riders. To effectively act as a viable alternative transportation mode, the system must be highly efficient. One way to measure efficiency of the PTS is connectivity. In a multimodal transportation system, transit is a key component. Transit connectivity is relatively complex to calculate, as one has to consider fares, schedule, capacity, frequency and other features of the system at large. Thus, assessing transit connectivity requires a systematic approach using many diverse parameters involved in real-world service provision. In this paper, we use a graph theoretic approach to evaluate transit connectivity at various levels of service and for various components of transit, such as nodes, lines, and transfer centers in a multimodal transportation system. Further, we provide a platform for computing connectivity over large-scale applications, using visualization to communicate results in the context of their geography and to facilitate public transit decision-making. The proposed framework is then applied to a comprehensive transit network in the Washington-Baltimore region. Underpinning the visualization, we introduce a novel spatial data architecture and Web-based interface designed with free and open source libraries and crowd-sourced contextual data, accessible on various platforms such as mobile phones, tablets and personal computers. The proposed methodology is a useful tool for both riders and decision-makers in assessing transit connectivity in a multimodal transit network in a number of ways such as the identification of under-served transit areas, prioritization and allocation of funds to locations for improving transit service.

Modelling impacts of adverse weather conditions on activity–travel pattern scheduling in multi-modal transit networks

In general, adverse weather has significant influence on individuals’ activity/travel choice behaviour and such influence is obviously greater in cities which suffer frequent rainy periods. Thus, the impacts of weather conditions should be taken into account in long-term transit service planning. In this paper, an activity-based network equilibrium model for scheduling daily activity–travel patterns (DATPs) in multi-modal transit networks under adverse weather conditions (with different rainfall intensities) is developed. The interdependency of individuals’ activity/travel choices and weather conditions are comprehensively investigated. In the proposed model, the DATP choice problem under adverse weather conditions is transformed into an equivalent static transit assignment problem by constructing a novel super-network platform. A rule-based algorithm is proposed to automatically generate the super-network taking into account the rain effects implicitly. The effects of adverse weather on different transit modes and different activities are explicitly modelled. An efficient solution algorithm without prior enumeration of DATPs is proposed for solving the DATP scheduling problem in multi-modal transit networks. Numerical examples are presented to illustrate application of the proposed model and the solution algorithm.

Using connectivity for measuring equity in transit provision

This study proposes the assessment of equity in transit provision by using transit connectivity as a comprehensive impedance measure. Transit connectivity considers in-vehicle time, access/egress times, waiting time, service reliability, frequency, and ‘seamless’ transfers along multi-modal paths. In addition, transit connectivity weighs the impedance components according to their relative importance to travelers. The assessment of equity was performed for the multi-modal transit system in the Greater Copenhagen Area, renowned for its transit-oriented finger-plan. The assessment method used a GIS representation of the network (i.e., service lines, timetables, metro stations, train stations, and bus stops), and transit assignment results (i.e., level-of-service times, passenger flows). The assessment method proved effective in calculating location-based and potential-accessibility measures and Gini coefficients of inequality in the Greater Copenhagen Area. Results show that the transit-oriented development contributes to spatial equity with high connectivity in densely populated zones, vertical equity with comparable connectivity in high income and low income zones, inter-generational equity with good connectivity provision for students to higher-education and job opportunities. Also, results show that the north-west ‘finger’ is less equitable with lower connectivity for low population density and lower connectivity to higher-education opportunities regardless of the high number of students.

A Hierarchical Approach to Optimizing Bus Stop Distribution in Large and Fast Developing Cities

Public transit plays a key role in shaping the transportation structure of large and fast growing cities. To cope with high population and employment density, such cities usually resort to multi-modal transit services, such as rail, BRT and bus. These modes are strategically connected to form an effective transit network. Among the transit modes, bus stops need to be properly deployed to maintain an acceptable walking accessibility. This paper presents a hierarchical process for optimizing bus stop locations in the context of fast growing multi-modal transit services. Three types of bus stops are identified hierarchically, which includes connection stops, key stops and ordinary stops. Connection stops are generated manually to connect with other transit facilities. Key stops and ordinary stops are optimized with coverage models that are respectively weighted by network centrality measure and potential demand. A case study in a Chinese city suggests the hierarchical approach may generate more effective stop distribution.

Modeling and monitoring of multimode transition process based on reconstruction

In this paper, a new nonlinear reconstruction algorithm is proposed for handling the multimode problem in the industrial processes. The contributions are as follows: (1) in different batch cycles, the transition patterns may follow different trajectories and reveal different characteristics. After the operation patterns change, the two neighboring modes still share some common correlations; (2) nonlinear reconstruction model is built based on traditional characteristics; and (3) a new fault direction matrix is designed to modify the reconstruction equation. The corresponding confidence regions are constructed according to their models respectively. The effectiveness of the proposed method has been demonstrated via simulated examples.

Estimation of Origin-Destination Demand Matrix for the Urban Multimodal Traffic Network

In this paper we consider a procedure for the estimation of origin-destination (O-D) matrices for a multimodal transit network. The structure of urban multimodal transport system is fully analyzed and then a bi-level programming model is established for O-D demand matrices estimation, where the upper-level problem seeks to minimize the sum of error measurements in traffic counts and O-D matrices, while the lower-level problem is to assign a target O-D matrix onto the network according to the user equilibrium principle. And a heuristic algorithm is proposed, finally a numeral example is given which indicates that the solution approach can be applied in practice.

Response of the Hodgkin-Huxley Neuron to a Periodic Sequence of Biphasic Pulses

Electric stimulation of various parts of the nervous system is a widely used therapeutic method and a principle of operation of prosthetic devices. Its usefulness has been proven in areas such as treatment of neurological disorders and cochlear prostheses. However the dynamic mechanisms underlying these applications are not well understood. In order to shed some light on this problem we study the response of the Hodgkin Huxley neuron subject to periodic train of biphasic rectangular current pulses. One of the simpler ways to understand the behavior of such a nonlinear system is the analysis of the global bifurcation diagram in the period amplitude plane. For short pulses the topology of this diagram is approximately invariant with respect to the pulse polarity and shape details. The lowest excitation threshold for charge-balanced input was obtained for cathodicrst pulses with an inter-phase gap approximately equal to 5 ms. The ring rate of the Hodgkin Huxley neuron stimulated at the frequency of its natural resonance is a square root function of the pulse amplitude. At nonresonant frequencies the quiescent state and the ring state coexist and transition to ring is a discontinuous one. We found a multimodal transition in the regime of irregular ring between the 2:1 and 3:1 locked-in states. This transition separates the regime of odd-only multiples of the stimulus period from the regime where modes of both parities participate in the response. A strong antiresonant e ect was found between the states 3:1 and 4:1, where the modes (2 + 3n) : 1, where n = 0, 1, 2, . . ., were entirely absent. The antiresonant e ects at high stimulation frequency, such as multimodal transition, may provide an explanation for the therapeutic mechanism of deep brain stimulation.

A hierarchical process for optimizing bus stop distribution

Transit stop spacing is an important indicator in deploying public transit services. This paper presents a hierarchical process for optimizing distribution of bus stops in the context of multi-modal transit development in large cities. Firstly, connection stops are generated manually to connect with other transit facilities. Secondly, key stops are identified based on a coverage model that minimizing total distance, using node centrality value as weight. Thirdly, ordinary bus stops are optimized with coverage model that maximizing potential transit demand. The analytical process is based on a combination of raster and vector data models in Geographical information system, which allows for flexible computing and effective evaluation.

Toward Transit Metropolis: Status Quo Analysis for Chinese Major Cities

In order to promote low-carbon transport, “The 12th five-year Transport Development Planning” released by the Ministry of Transport (MoT) of P. R. China in 2011, indicates that MoT will provide significant funds to support 30 cities to build “The Transit Metropolis” before 2015. In order to support the “Transit Metropolis” project, the authors led great efforts on collecting statistic and economy data, geography and population data, transportation infrastructure and operation data, transit passenger degree of satisfaction data, etc. Based on all the ground information, this paper assessed the status of urban public transit in China, and analyzed the factors that affect the public transit development. It is found that the relationship between the transit mode share and the GDP per capita follows a “flash” shape and can be divided into three phases. With the growth of GDP, the trend of the transit mode share typically goes “up-down-up” due to the different stages of economy level, car ownership and investment on transit system. Based on the analysis and discussion, some suggestions are provided to develop a hierarchical multi-modal transit system with smooth transfers and good coverage to mitigate traffic congestion and improve the sustainability of urban transportation system in China.

A measure of equity for public transit connectivity

An equitable transit system can cater to the needs of captive riders and maximize transit service coverage. Historically transit equity has not considered in planning or has been an afterthought in the process; leading to the underutilization of transit and encouraging travelers to be auto dependent. In this paper, the authors propose a methodology to estimate transit equity using a number of attributes such as frequency, speed, capacity, and built environment in a multi-modal transit network. We propose a methodology to measure transit equity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns.The objective of using equity is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; conforming with federal regulations; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes and assessing the effectiveness and efficiency for node/stop prioritization while choosing transit as a mode of travel. The methodology uses a stylized connectivity measure with a Gini index for equity estimation at different levels such as stop, line, zone and area. An example problem is presented to demonstrate the proposed methodology. The approach is then applied to the Washington–Baltimore region in the United States. The results show the existing transit service coverage at different locations. The proposed approach can be utilized as a tool for transit service planning.

Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models

A growing base of research adopts direct demand models to reveal associations between transit ridership and influence factors in recent years. This study is designed to investigate the factors affecting rail transit ridership at both station level and station-to-station level by adopting multiple regression model and multiplicative model respectively, specifically using an implemented Metro system in Nanjing, China, where Metro implementation is on the rise. Independent variables include factors measuring land-use mix, intermodal connection, station context, and travel impedance. Multiple regression model proves 11 variables are significantly associated with Metro ridership at station level: population, employment, business/office floor area, CBD dummy variable, number of major educational sites, entertainment venues and shopping centers, road length, feeder bus lines, bicycle park-and-ride (P&R) spaces, and transfer dummy variable. Results from multiplicative model indicate that factors influencing Metro station ridership may also influence Metro station-to-station ridership, varied by both trip ends (origin/destination) and time of day. In comparison with previous case studies, CBD dummy variable and bicycle P&R are statistically significant to explain Metro ridership in Nanjing. In addition, Metro travel impedance variables have significant influence on station-to-station ridership, representing the basic time-decay relationship in travel distribution. Potential implications of the model results include estimating Metro ridership at station level and station-to-station level by considering the significant variables, recognizing the necessity to establish a cooperative multi-modal transit system, and identifying opportunities for transit-oriented development.