Metro Fare Research Articles

DIAGNOSTIC EVALUATION OF URBAN METRO TRANSIT SYSTEM POST-COVID-19

Public transportation usage in Delhi has declined, with the Delhi Metro having a significant share. However, due to fare hikes and COVID-19 restrictions, the DM's share has been decreasing further. To improve ridership, a study is being conducted to evaluate the DM's performance and identify areas for improvement in passenger convenience and comfort. The Magenta line is investigated through an on-board survey to collect primary data. The survey covers commuter perceptions of safety & security, financial & economic factors, infrastructure & comfort and functional & operational features. The Relative Importance Index approach is used to analyse the data and evaluate DM performance. An ANN model is also presented to determine the factors influencing the choice to travel on the DM, with the “metro fare per trip” factor being a key consideration. Based on the analysis results, recommendations are made to improve the DM's performance. The study found that safety and security had the highest RII, followed by efficiency and viability, functional and operational features, infrastructure and comfort, and financial and economic factors. The subway fare had the lowest RII. The ANN model is adapted to understand the reasons behind low metro ridership.

A Study of Delhi Metro’s Magenta Line to Assess Commuter Satisfaction Post Covid-19

Abstract This study looks how satisfied people are with the Delhi metro, which is crucial for sustainable transportation. The study focuses on security, comfort, travel time components. The research shows how important the quality of service is in public transportation and how it affects what people think and if they would recommend it to others. In the research, 430 passengers surveyed and used statistical analysis to understand what factors influence people’s opinions. The study reveals that age, gender, comfort and security are important factors. The study also investigates the alternate PT modes and found that metro fare, seating/standing facilities are important aspects especially for different genders. It’s important for the DM to think about how people feel about the cost of using it, the seating, and the different preferences of men and women. Making changes like lowering fares and making the metro more comfortable could make it a better option for everyone in Delhi.

“Memory Makes Us Brave”: Hauntological Echoes of the Past in the Music of Chile’s 2019 Social Upheaval

Abstract: The 2019 social upheaval in Chile began with students jumping turn-stiles in protest over a modest increase in the metro fare, but it quickly expanded into a widespread denunciation of nearly every facet of the neo-liberal economic system installed under the 1973–1990 Augusto Pinochet dictatorship. “It’s not the thirty pesos,” protesters claimed, “it’s the thirty years,” referring to the three decades of neoliberal policies after the return to democracy in 1990. In the days and weeks after the protests began, a soundtrack emerged of both original music and songs repurposed from Chile’s past. Even the new songs created in the wake of the 2019 protests also frequently reference, sample, or allude to Chile’s musical icons of the Chilean New Song era of the 1960s and early 1970s or to dictatorship era music. Both the protests and their music are therefore rooted in a hauntological past. Jacques Derrida coined the term “hauntology” in Spectres of Marx (2006), where he examines the ways in which the spirit of Marxism, like all ghosts which have yet to be laid to rest, would return, repeatedly, disrupting the present and continuing to remind us of another possible future.” In Ghosts of My Life , British cultural theorist Mark Fisher applies Derrida’s concept of hauntology to English language cultural production, arguing that 21st-century cultural products reflect a “slow cancellation of the future.” “It doesn’t feel like the future,” Fisher writes; instead, “we remain trapped in the 20th century.” This article examines how the hauntological songs of the 2019 social upheaval seek to inspire and support an oppositional consciousness against the neoliberal system and how the resilience of that same system maintains Chile’s musical ghosts in a perpetual limbo .

Affordable and sustainable transportation: Key drivers and policy choices for a megacity in India

The city of Bengaluru is one of the latest entrants to the list of 33 mega cities in the world. The transportation infrastructure of the city is expanding to accommodate the rapidly increasing population. As such, there is a need to reevaluate public transport policies to achieve the Sustainable Development Goal (SDG) target 11.2. In this study, we conducted a socio-economic survey of 1350 households belonging to the low and low-middle income categories in Bengaluru city to understand their travel behaviour and transportation mode choices in the event of changing transport infrastructure dynamics of the city. While two-wheelers are the dominant mode among employed working males in the age group of 18–45 years, buses are preferred for long-distance travel. Metro ridership is low even where metro stations are accessible at the start of the journey because low- and middle-income groups are unable to afford metro services. Additionally, we used Random Forest model to assess the contribution of each explanatory variable in mode choice determination. The results shows that travel cost followed by travel time and travel distance are the most important explanators in determining the mode choice for our sample population. Based on these findings, the authors have created two scenarios to assess the impact of metro fare rationalisation on metro ridership. This study quantifies the co-benefits of the proposed policy changes in terms of economic benefits to the operators and the avoidance of air pollution and CO2 emissions.

The Art of Living Together: The Work of Caiozzama, Delight Lab, and LASTESIS during Chile’s 2019-2020 Protests

On 18 October 2019, a protest over an increase in metro fares in Santiago, Chile transformed into a nationwide uprising against inequality. As the protests evolved, it became clear that the discontent stemmed not only from the economic effects of the neoliberal model put into place during the Pinochet dictatorship (1973 to 1990), but also from the modes of relationality that it had engendered. The messages that protesters scrawled on the walls of the city insisted on the need for more empathy, respect, and dignity. Chilean artists responded by creating works that framed these individual grievances as collective experiences of a crisis in what in Spanish is called convivencia, or the art of living together. In this piece, I review the paste-up graffiti of Caiozzama, the visual mappings of Delight Lab, and the feminist performances of LASTESIS to highlight how these artists supported protesters’ call for dignity and a new mode of convivencia.

Trip-based Modal Shift Behaviour of Mode Users along the Proposed Extension Metro Corridor in Chennai (India)

Object of this study is to predict the ‘Probability of Shift’ to the proposed metro corridor from two-wheeler, car, bus and suburban rail in Chennai. To achieve this, a Stated Preference survey questionnaire was prepared and survey was conducted among two-wheeler users; car users; bus users and suburban rail users through face-to-face interview method. The collected SP data were coded, analysed and mode-wise/ trip-based binary logit models were developed using Statistical Software Tools (SST) software. From the developed models, it is observed that irrespective of mode & trip purposes, the choice of metro is fully driven by the proposed metro fare. From the predicted Probability of Shift, it is observed that car users are more willing to switch to metro as well as relatively price sensitive when comparing with other mode users.

Post-COVID-19 performance evaluation of urban metro transit system in Delhi and influence on access mode

The impact of the COVID-19 pandemic has been observed to affect the travel patterns, routes and traffic in public transportation systems across the world. It is important to evaluate the performance of the Delhi Metro (DM) post-COVID-19 pandemic for its successful operation. In this study, the BLUE line of DM with the longest route and highest number of metro stations has been examined for performance evaluation. The performance is evaluated based on travel time components (access, egress, transfer, waiting and main haul time) to calculate various performance indicators i.e., Level of Service (LOS), Service Time Ratio (STR), Passengers Waiting Index (PWI), Total Travel Ratio (TTR) and Interconnectivity Ratio (IR). The post-COVID-19 LOS evaluation indicates that the users are spending 72.6 % to 84.4 % of their main haul time on their access-egress trips. The STR shows that the users are spending 10.9 % to 12.6 % of their total travel time in waiting and transferring only during the main haul trip. The mean PWI, RI and TTR are noted as 1.008, 0.794 and 2.069 respectively. The IR is observed as 0.312 for the given route. The median and average main haul distances across all access modes are observed to be (12–21) Km. and (19.69 ± 11.19) Km. respectively. It is revealed that the observed mean value of LOS is (0.775 ± 0.575). It is further revealed that the metro fare per trip and the access-egress trip cost per day are significant factors for access mode choice in the case of walking and auto-rickshaw whereas LOS, RI and PWI are other significant operator’s performance indicators influencing the access mode choice. The study reveals that post-COVID-19 the performance indicators exhibit the unsatisfactory performance of DM and there is further scope to improve the UMTS performance.

Data-Driven Digital Advertising with Uncertain Demand Model in Metro Networks

Nowadays most metro advertising systems schedule advertising slots on digital advertising screens to achieve the maximum exposure to passengers by exploring passenger demand models. However, our empirical results show that these passenger demand models experience uncertainty at fine temporal granularity (e.g., per min). As a result, for fine-grained advertisements (shorter than one minute), a scheduling based on these demand models cannot achieve the maximum advertisement exposure. To address this issue, we propose an online advertising approach, called FineUDM, based on the uncertain passenger demand modeling for both entering passengers and exiting passengers. FineUDM combines coarse-grained statistical demand modeling and fine-grained real-time demand modeling by leveraging historical passenger demands, real-time card-swiping records, and passenger mobility patterns. Based on this uncertain demand model, it schedules advertising time online based on robust receding horizon control to maximize the advertisement exposure. We evaluate the proposed approach based on an one-month sample from our 530 GB real-world metro fare dataset with 16 million cards. The results show that our approach provides a 61.5 percent lower traffic prediction error and 20 percent improvement on advertising efficiency on average.

Activism in a time of pandemic: The impact of COVID-19 in Chilean citizen movement after the uprising of October 2019

Chile, unlike other countries in the region, is facing two major crises: one of a large social nature and the other in public health, which is in its form of the pandemic that is currently affecting the entire world. In October 2019, secondary-school and university students organized a massive evasion of the Santiago metro fare. The reason was to protest the 30 pesos increase in the cost of the ticket. This apparently small issue detonated the greatest protest movement of the last 30 years. By January 2019, the uprising had left 31 dead and 5,558 people who reported human rights violations, including 331 with ocular trauma or injury to their eyes and 21 suffered damage or loss of the eyeball. In March 2019, protests were eradicated from the streets and the development of the movement was slowed down by the powerful action of the Coronavirus. This article explores the impact that the COVID-19 crisis had on citizen movement, and the functionality of the health crisis to establish the de facto authoritarian hyper-controlled state in order to freeze the social crisis. Also, this work identifies the strategy that the Chilean citizen movement developed to survive during 2020, applying model of analysis of activism under pandemic as a starting point.

Modeling the Modal Shift towards a More Sustainable Transport by Stated Preference in Riyadh, Saudi Arabia

The need to gain a comprehensive understanding of road travelers’ choice of mode and their perceptions of using sustainable urban mobility modes have evolved to shape the form of future transport planning and policymaking. To combat the concern of growing traffic congestion in Riyadh City, the government of Saudi Arabia designed and introduced a sustainable public transport project named “Riyadh Metro”. This study explores the potential commuters’ perception towards the Metro services and the factors that limit their propensity to use Metro and understand the tradeoffs that the individuals make when they are faced with a combination of mode characteristics (e.g., travel time, price, walking time). The stated preferences experiment was conducted on a sample from the Riyadh neighborhood by structured interviews. A discrete choice model based on binary logistic regression has been developed. The coefficient of travel attribute: travel time, fuel cost, Metro fare, and walking time was found to be statistically significant with a different effect on mode choice. The elasticity of the coefficient showed that an increase in the fuel price by 10% would increase the metro ridership by 5.3% and reduce car dependency. Decreasing the walking time by 5 min to the metro station will increase the metro ridership by 22%. Furthermore, the study revealed that implementing a 1 SAR/hour parking charge will decrease car dependency by 14%. Increase Metro fare by 10% will decrease Metro ridership by 6.9%. The socioeconomic factors coefficient shows a marginal effect on the choice decision of passengers.

How Far Can You Travel by Metro for Five Yuan?

With 5 Yuan, you can buy a small piece of bread or two bottles of water. If you are thinking about travelling, public transportation will be the only option; and if you want to reach the destination quickly and comfortably, the metro will be your first choice. Then with 5 Yuan in hand, how far can you travel by metro? To answer this question, Shanghai Rail Transit Industry Information Center has collected the latest data on metro fares in 33 cities in China and drawn the chart, as shown in figure 1.

Verification and Optimization of Metro Fare Clearing Models Based on Travel Route Reconstruction

How to verify and optimize metro fare clearing models efficiently and accurately is a research focus in metro operations. Metro fare clearing models are mostly based on probability distributions. In such models, the normal distribution of travel time corresponding to the section probabilities is used to calculate the route choice probabilities of passengers on a multi-route metro network. By integrating the operating mileage proportions of each metro line operator and the corresponding route choice probabilities, the fare clearing proportions are calculated for all the operators of the metro network. To verify the accuracy of the fare clearing proportions, we propose a travel route reconstruction approach based on cell phone data acquisition technique. With wireless access point (AP) sensors installed at transfer stations, the unique medium access control (MAC) address of the smart phone with Wi-Fi function turned on is recorded and transmitted to a data analysis platform. After matching the MAC address information with time and location, the travel route of the smart phone user is reconstructed. Then, the parameters in the fare clearing model are verified and optimized according to the travel route choice probabilities. The proposed methodology is applied in Hangzhou metro network for experiment, and the metro fare clearing model is verified and modified by reconstructing the actual travel routs of the local passengers.

Assessment of urban transportation pricing policies with incorporation of unobserved heterogeneity

This paper aims to assess five urban transportation pricing policies (including petrol price, parking fee, taxi fare, bus fare, and metro fare). Using stated preference panel data, we estimate a mixed logit (ML) model and a latent class (LC) model, which account for individual unobserved heterogeneity. The estimated policy implications resulting from these models are compared to get a deeper understanding of the differences in policy recommendations when using different treatments of unobserved heterogeneity. In this regard, we focus on two criteria, which are the changes in mode share and the changes in expected consumer surplus in response to the changes in the level of pricing policies. Results by both ML and LC models reveal that in some comparisons, the ML and LC models yield similar results, as both indicate the policy of increasing petrol price is more effective than increasing parking fee on reducing car congestion. However, we can also find some differences in the behavioral outcomes of these models. Overall, the ML model estimated substantially greater choice elasticities and changes in mode share, in comparison to the LC model. Some of these differences may lead to different policy recommendations as the ML model suggests avoiding the policy of increasing bus fare due to its large negative impact on car share, while the LC model predicts a relatively small reduction in car share after increasing bus fare and therefore, can motivate policymakers toward this policy.This paper also provides new evidence on one of the key assumptions in discrete choice analysis, namely the assumption of an equal (generic) cost coefficient over transport modes is not satisfied when the travelers do not have a true perception about their travel costs (e.g. fuel cost and parking cost).

Prioritizing Metro Service Quality Attributes to Enhance Commuter Experience: TOPSIS Ranking and Importance Satisfaction Analysis Methods

A metro infrastructure, facility, and service quality investigation based on commuter perception was conducted in this study to explore and prioritize the key attributes influencing overall metro service quality in a typical Indian context. Based on the critical state-of-the-art review, 12 key attributes were identified and they were accommodated in a paper-based questionnaire to elicit commuter perception of importance and satisfaction by using a five-point Likert scale. Subsequently, TOPSIS, an extensively adopted multi-attribute decision-making technique, was carried out to rank the attributes with respect to perceived importance and satisfaction. Then an importance satisfaction analysis (ISA) was conducted to further classify the attributes in four quadrants based on their perceived degree of importance and satisfaction using an ISA matrix. Finally, the derived results from the TOPSIS and ISA analysis were combined and compared to obtain a prioritized set of attributes requiring intervention for better metro service quality in an Indian context. Results of this study clearly indicated the relative strengths and weaknesses of each metro service/infrastructure-specific attribute and presented the probable role of metro authorities for each of them. Attributes such as metro fare, connection to metro, and metro frequency were observed to be the most important, but were not performing satisfactorily, indicating that more emphasis is required on these attributes to improve the overall quality of travel by metro rail in an Indian context. Thus, this methodology would be instrumental in detecting a set of priority areas for improvement in metro rail services, which could contribute to retaining existing commuters and attracting new metro users.

In Chile, the Post-Neoliberal Future is Now

The mass revolt of October 2019 destroyed many myths in Chile. It began in Santiago with a protest against the rise in metro fares, but quickly turned into a broader rebuke of rampant inequality, s...

Estimating the long-run metro demand elasticities for Lisbon: A time-varying approach

This paper provides the first estimation of long-run demand elasticities for Lisbon’s metro, covering the lifetime of the metro’s operation from 1960 until 2017. The findings indicate that the metro patronage is relatively more responsive to changes in the fare than to changes in service level, with long-run elasticity values ranging between −0.45 to −0.84 for metro travel card and between 0.45 and 0.50 for service level. This implies that fare policies are likely to be more effective at influencing patronage than supply policies. We also find a substitution effect between the metro and private motorized transport, but not between the metro and the urban bus/tram system. There is also evidence of a strong relation between wage and metro demand for poorer individuals, which we interpret as an indication of greater mobility constrains faced by these individuals for whom an increase in income level only permits more mobility by public transport. Finally, we also implement a recursive time-varying method to investigate the presence of structural breaks resulting from the very large increase in metro prices and the strong reduction in service level during the period of economic crisis and public finance imbalances that followed the financial and economic crisis of 2008. During this period, metro demand elasticities changed, especially for the metro fare, suggesting it became more elastic.

The effects of metro fare increase on transport equity: New evidence from Beijing

Transit pricing is one of the major factors influencing transport-related equity. In particular, in developing countries with low car-dependency rates, public transit plays an important role in providing access for disadvantaged groups to desired destinations, such as jobs, education, and health care. Changes in public transit fares can significantly affect residents' travel expenditures and possibly transport-related social equity. However, cases from developed countries dominate the existing literature in the field, and the comparison of equity between flat fare and distance-based fare is scarce. This study aims to fill this gap by examining the case of Beijing. To relieve operators’ financial pressures, the Beijing municipal government replaced its flat metro fare (CNY 2) by a distance-based fare in 2014. Using retrospective survey data, this study analysed the effects of the metro fare increase on transport equity. An index of affordability was established to measure transit equity, and the multivariable models showed that the introduction of a distance-based fare would significantly increase the cost burden of vulnerable residents on metro use with such groups as low-income earners and young workers, who pay more than their counterparts. Because of the unaffordable housing price in Beijing and the different patterns of residence by income, this study also investigated the interaction effects of housing tenure and residential location. The compelling results suggest that residents who owned housing in the suburbs experienced less increase of the transit burden. These findings are interpreted as supporting the construction of affordable housing in suburban areas and integrated transit-oriented as tools to enhance social equity under the circumstance of property-led urban growth.

Modeling departure time choice of metro passengers with a smart corrected mixed logit model - A case study in Beijing

It is critical to improve the effectiveness of demand management in metro systems with passenger departure time choice exactly learned during peak hours. In this study, a practical framework is developed to model departure time choice of metro passengers during peak hours. First, various attributes that influence departure time choice of metro passengers are investigated and the technique for order preference by similarity to ideal solutions (TOPSIS) is used to identify these main attributes. Then, a mixed logit (ML) model of departure time choice that accounts for price endogeneity is developed. To calibrate the model, a stated preference (SP) survey based on D-efficient design is conducted in the Beijing metro system. It is proved that the corrected ML model outperforms the uncorrected ML model according to the collected 1152 sample data. An elasticity analysis of these main attributes is further conducted, which indicates that metro fare and departure time change influence passenger departure time choice more than crowdedness in Beijing metro. Knowledge of these preferences assists traffic managers in balancing passenger departure time to mitigate overcrowding during peak hours. Heterogeneity of passenger socioeconomic and trip characteristics is also concerned taking advantage of ML model. Finally, a ML-based fare discount strategy to ease the crowdedness in Batong Line of Beijing metro is presented and evaluated via an existing simulation tool.

Potential Influence of Metro on Bus: A Case Study

A modal shift occurs when one mode of transport has a comparative advantage in a similar market over another. The present work concerns with the development of modal shift model for urban travel in Chennai, India. The modal shift model was calibrated using binary logit technique and validated using hold-out sample method. The validated model was used to predict the probability of shift in selected corridor. The recent introduction of metro rail in Chennai has lead to an increasing competition among public transport modes. To study the influence of metro on bus transport, a Stated Preference (SP) survey was conducted among express bus travellers. Using the SP survey data, a modal shift model was calibrated to estimate the plausible shift from bus to metro. Results indicate that variables like fare-difference, age, and income play an important role in the shift behaviour. When metro fare increases with respect to express bus fare, bus passengers are less willing to use metro and vice-versa.

Does where you live affect how much you spend on transit? The link between urban form and household transit expenditures in Mexico City

Long and expensive transit trips burden millions of households in many low- and middle-income cities. Geography likely plays an important role. In Mexico City, suburban households earn 30% less than urban households, have 40% longer commutes, and spend nearly twice as much per transit trip. This paper examines the relationship between where households live in Mexico City and how much they spend on transit using a large metropolitan household travel survey matched to measures of the built environment. Transit expenditures vary systematically with neighborhood population density, land-use diversity, municipal job density, street network density, and distance to the metro and urban center. These relationships are complex and nonlinear but robust with the inclusion of household income, size, and structure. They are also relatively strong with job density, destination diversity, distance to the metro, and population density being as strongly correlated with transit expenditures as household income. In dollar values, the savings associated with more convenient household locations are substantial and in the same ballpark as total metro fare revenues and a back-of-the-envelope estimate of the total daily external costs of suburban congestion.