Taxi Industry Research Articles

Improving YOLOv8 with parallel frequency channel attention for taxi passengers

AbstractDetecting taxi passengers is crucial for assessing taxi driver behavior, which plays a significant role in regulating the taxi industry. Despite the advancements in deep learning, object detection algorithms have not been extensively applied to this domain. In this article, an innovative taxi passenger detection algorithm is introduced based on YOLOv8, a lightweight and highly accurate method designed to automatically monitor driver behavior and regulate the taxi industry. To address the challenge of deploying complex object detection models on mobile devices, the ghost module is incorporated in place of standard convolutions within the C2f module, thereby making the model more lightweight. Furthermore, the model's performance is enhanced by integrating an improved version of Frequency Channel Attention (FCA), termed Parallel Frequency Channel Attention (PFCA), which boosts detection accuracy with minimal additional parameters and computational overhead. Experimental results on a specific taxi passenger dataset demonstrate that the proposed method significantly outperforms the baseline YOLOv8n model. Specifically, the model reduces the number of parameters and floating point operations by 12.96% and 8.18%, respectively, while achieving increases in mAP50 and mAP50‐95 by 0.27 and 0.73 percentage points, respectively.

Investigating work-related distraction’s impact on male taxi driver safety: A hazard-based duration model

With the increasing use of phone-based ride-hailing apps, concerns have arisen regarding road safety and driver distraction. Despite the recognized safety risks of driver distraction, limited research has explored how distractions from various ride-hailing systems affect drivers in the taxi industry. To close this gap, the current research utilized a driving simulator experiment involving 51 male taxi drivers in two road environments (urban street and motorway) and three distracted driving conditions (no distraction, auditory distraction via radio dispatching system, and visual-manual distraction via mobile application). A car-following scenario with sudden brake events was incorporated into the experiments because this is a typical safety–critical situation where attention will determine the outcome. The collected performance indicators include brake reaction time, time headway, and car-following distance. The grouped random parameters Weibull accelerated failure time model was applied to model the duration data under different road conditions. The brake reaction time and time headway are dependent variables, while the car-following distance is a covariate in the models. The results indicate that although taxi drivers show longer brake reaction time when distracted by mobile app and radio system, this does not necessarily equate with greater risk or reduced safety since they compensate for the risk of rear-end crashes by maintaining a longer time headway. In general, taxi drivers’ brake reaction time and time headway are more profoundly affected by mobile apps when distracted in both urban and motorway scenarios. This highlights the elevated risks associated with such technologies. In addition, significant interaction effects revealed the observed heterogeneity, which suggests that drivers’ personal characteristics influence the relationship between distraction type and driving performance. This research provides valuable insights for designing safer ride-hailing operations and systems.

The Sea and Underwater Transport in Imraan Coovadia’s The Institute for Taxi Poetry

ABSTRACT This article discusses the link between public transport and literary practices by analyzing Imraan Coovadia’s 2012 novel, The Institute for Taxi Poetry. In this novel, Coovadia comments on South Africa’s palimpsestic history from the precolonial to the postcolonial. One way in which Coovadia does this is through the motif of the taxi. The taxi refers to a mini-bus taxi which in South Africa is a form of public transport primarily used by people from working-class backgrounds. Another way concerns the proposal of a fictional genre that plays a prominent role in this novel: taxi poetry. The article explores the ways in which the novel uses the taxi and submarine vessels to open up the geography of the sea as a transport surface whose impact on the histories of the dispossessed is visible from both below and above the waterline. Through engagement with the humanities turn in mobility studies and with scholarship in the oceanic humanities from the Global South, the article argues that the national and terrestrial readings of public transport in African literature(s) undervalue the sea, a prominent transport arena in Coovadia’s novel, as both a space of transit as well as a public space with shared transnational histories. The article engages the novel’s imagined literary sub-genre to evaluate how the text’s subterranean extensions of the South African taxi industry, and public transport generally, unearth the layered narrative of South Africa as nation.

Deadly Journeys: Thabo Jijana’s Nobody’s Business, the Minibus Taxi Industry, and the Racial Politics of Mobility in Post-Apartheid South Africa

ABSTRACT This article examines the politics of mobility in post-1994 South Africa by paying attention to minibus taxis, which have received little consideration from literary scholars although they are ubiquitous in contemporary South African literature. Attending to the minibus taxis that pervade post-apartheid Black writing, I contend, sheds light onto the ongoing racialization of mobility in the country. Offering a socially situated reading of Thabo Jijana’s Nobody’s Business: A Taxi Owner, a Murder, and a Secret (2014), I show that the abysmal state of public transport in present-day South Africa is emblematic of larger realities of immobility which continue to structure the lives of most Black South Africans. Motivated by the death of his father, a taxi owner who was murdered at the job, Jijana’s searing investigative memoir provides a powerful lens into the underbelly of the minibus taxi industry and the violence that drives it. As it reveals the precarity that continues to characterize not just public transport, but every-day life for the Black majority, Nobody’s Business suggests that the politics of mobility in post-apartheid South Africa cannot be understood outside the racism and anti-Blackness that define the democratic dispensation.

Exploring driving anger-caused impairment of takeover performance among professional taxi drivers during partially automated driving

Partially automated systems are expected to reduce road crashes related to human error, even amongst professional drivers. Consequently, the applications of these systems into the taxi industry would potentially improve transportation safety. However, taxi drivers are prone to experiencing driving anger, which may subsequently affect their takeover performance. In this research, we explored how driving anger emotion affects taxi drivers’ driving performance in various takeover scenarios, namely Mandatory Automation-Initiated transition (MAIT), Mandatory Driver-Initiated transition (MDIT), and Optional Driver-Initiated transition (ODIT). Forty-seven taxi drivers participated in this 2·3 mixed design simulator experiment (between-subjects: anger vs. calmness; within-subjects: MAIT vs. MDIT vs. ODIT). Compared to calmness, driving anger emotion led to a narrower field of attention (e.g., smaller standard deviations of horizontal fixation points position) and worse hazard perception (e.g., longer saccade latency, smaller amplitude of skin conductance responses), which resulted in longer takeover time and inferior vehicle control stability (e.g., higher standard deviations of lateral position) in MAIT and MDIT scenarios. Angry taxi drivers were more likely to deactivate vehicle automation and take over the vehicle in a more aggressive manner (e.g., higher maximal resulting acceleration, refusing to yield to other road users) in ODIT scenarios. The findings will contribute to addressing the safety concerns related to driving anger among professional taxi drivers and promote the widespread acceptance and integration of partially automated systems within the taxi industry.

The Impact of Rice Sharing Service on Traditional Taxy Market: Meta-analysis

This study aims to analyze the impact of rice sharing services on the traditional taxi market through a meta-analysis. Rice-sharing services have grown rapidly in recent years, offering cheaper and more convenient transportation alternatives for consumers. The study pooled and analyzed the results of 10 studies examining the impact of rice-sharing services on the traditional taxi market. The results of the meta-analysis showed that rice sharing services had a significant negative impact on the income and number of traditional taxi passengers with an effect size value of 0.712. This effect is stronger in developing countries and in large cities. Subgroup analysis showed that the impact of rice-sharing services was greater on economy-class taxis and taxis operating on popular routes. Nan Berbagi Rice has disrupted the traditional taxi market and led to a decline in revenue and the number of traditional taxi riders. The findings have important implications for the taxi industry and policymakers looking to formulate regulations for rice-sharing services.

Exploring competitiveness of taxis to ride-hailing services from a multidimensional spatio-temporal perspective: A case study in Beijing, China

As the sharing economy expands in China, the emergence of ride-hailing services has diminished the market share of the taxi industry. As a regulated and publicly convenient service with a dedicated customer base, traditional taxi industry needs to improve its own competitiveness and maintain its market share. However, the specific circumstances under which taxis can gain a competitive edge over ride-hailing services are not well-understood. Aiming to uncover the competitive potential of taxis in the ride-source market, this study proposes a methodology to explore the Competition and Cooperation Relationship (CCR) between taxis and ride-hailing services on a multidimensional spatio-temporal scale. By taking Beijing, China as a case study, we first compare different impacts of Points of Interest (POI) on the traffic volume of taxis/ride-hailing services through Geographically and Temporally Weighted Regression (GTWR) models, and explore the corresponding times and locations where taxis/ride-hailing services are more likely to attract passengers. Based on the findings that there are strong correlations between traffic volume and spatio-temporal conditions, we establish the Competition-Cooperation Index (CCI) as a quantitative measure to characterize the CCR and then analyze the spatio-temporal distribution of CCI to identify the times and locations where taxis hold advantages in cooperative or competitive relationship relative to ride-hailing services. Furthermore, we investigate the underlying reasons for these patterns, discovering that CCI has a close connection with land use. The results of our analysis show that taxis exhibit competitive advantages over ride-hailing services under some specific circumstances and can further enhance their competitiveness by proposed targeted measures. The findings of this study provide valuable insights for both industries in formulating growth strategies and for governmental agencies in setting policies.

A comparative analysis of risk factors in taxi-related crashes using XGBoost and SHAP

Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted a comparative analysis of risk factors in crashes between traditional taxi drivers and ride-hailing taxi drivers in China, including their demographic characteristics, working conditions, and risky driving behaviors. The data was collected from 2,039 traditional taxi drivers and 2,182 ride-hailing taxi drivers via self-reported questionnaires. Four XGBoost models were established, taking into account different types of taxi drivers and crash types. All models showed acceptable performance, and SHAP explainer was used to analyze the model results. The results showed that for both taxi drivers, risk factors related to risky driving behaviors are more important in predicting property damage (PD) crashes, while risk factors related to working conditions are more important in predicting person injury (PI) crashes. However, the relative importance of each risk factor varied depending on the type of crashes and the type of taxi drivers involved. Furthermore, the results also validated certain interactions among the risk factors, indicating that the combination of certain factors generated a greater impact on crashes compared to individual factors alone. These findings can provide valuable insights for formulating appropriate measures to enhance road safety for taxi driver.

Taxis v. Uber in Paris: technology, capital, and the sharing economy

ABSTRACT Uber came to Paris late in 2011, bringing with them a widely accepted narrative of their necessary ‘disruption’ of a stagnant taxi industry. They presented themselves as part of the ‘Sharing Economy,’ with ‘driver/partners’ rather than employees, taking a share of the profits of each trip but acknowledging no obligations beyond the use of their app. Uber broke French law, evaded taxes, and engaged in unfair competitive practices. Uber is one example of the gig economy, based on the digital platform, which has transformed the working lives of people throughout the globe, imposing on them – as many labor historians have noted – a form of work akin to the sweated piecework labor of the nineteenth century. The government of Socialist President François Hollande (2012–2017) managed to preserve a lane for taxis. His term, however, was bracketed by the conservative and deregulatory presidencies of Nicolas Sarkozy (2007–2012) and of Emmanuel Macron (2017–), who created a legal space for Uber and other platforms. Taxis survived. As this article will show, however, working conditions and the French social model have been undermined.

Transport-related social exclusion and mobility in developing countries: the South African case

IntroductionTransport-related social exclusion has been studied in many countries, and from many different perspectives. In Africa, however, there is little recent research into the phenomenon, even though African cities tend to have poor transport services, urban sprawl is extensive usually resulting in long travel times and high travel costs, and certain areas experience high levels of crime. By implication, there are several factors that impact the ability of people to access economic and societal opportunities, however these are not well documented. Building on previous work from several authors, this research sought to describe transport-related social exclusion in a large metropolitan area in an emerging economy.MethodsUsing a qualitative methodology, 60 interviews were conducted with City of Johannesburg residents. The data was analyzed using manual thematic and classic content analysis.ResultsThe study found that residents often did not have access to services due to availability, but also that economic, geographic and fear-based exclusion were particularly prevalent in the sample, although there were several other psychological exclusion dimensions, as well as information exclusion.DiscussionThis study is the first recent study in South Africa to consider a wide range of commuters from varying demographic strata, thus providing a novel perspective on TRSE in a major urban area in the country. The study recommends that policy actions be considered, taking into account the minibus taxi industry, which is often overlooked in government policy. TRSE should also be an inherent element in urban (and other) transport planning, as well as take into account the broader societal realities faced by citizens. Future research directions include conducting broader quantitative studies across a variety of urban areas in South Africa, and beyond, to determine specific TRSE dimensions in various urban areas. Policy analysis is also recommended, to determine TRSE policy gaps and align interventions with specific commuter needs.

Navigating the roads of corporate strategy: An in-depth analysis of mobile taxi industry from the customers’ lens

This study aims to identify passenger preferences for mobile app based taxi services in Dehradun, India, to ensure sustainable business growth. The Indian taxi industry is expected to reach USD38.90 billion by 2028, growing at a compound annual growth rate (CAGR) of 13.55% from its projected value of USD20.61 billion in 2023 (Mordor Intelligence, 2023). A structured questionnaire with 28 attributes was employed in a cross-sectional survey of 384 purposively selected respondents who have used Uber and Ola at least three times. Importance–performance analysis (IPA) was utilized for data analysis. IPA identifies improvement opportunities, guides strategic planning, and assesses a firm’s competitive position in the market (Hawes & Rao, 1985; Martilla & James, 1977; Myers, 1999). The study found mobile app-based taxi services in Dehradun excelled in areas like app usability, availability of vehicles, precise locations, quick response time, multiple payment options, and the ability to call the driver through the app. The study also found that the drivers’ communication skills, map familiarity, smooth driving, and passengers’ security during the trip were satisfactory. However, the study recommends improvements in the availability and waiting time of the vehicles during odd hours, variation in taxi fares, drivers’ cancellation of rides, and availability of discounts.

Money, Violence and Power: Towards Understanding the South African Minibus Taxi Industry

ABSTRACT: The article seeks to add to the understanding of the South African minibus taxi industry, where violence plays a central role in enabling accumulation and regulating order. Qualitative interviews, reviews of documents and participant observations show how different parts of the minibus taxi industry benefit from, or are disadvantaged by, their respective positions within the industry and their relationship with the broader motor vehicle sector and state. It focuses on how little impact state policies and interventions have had over the forty years of the existence of the minibus taxi industry. Instead of becoming a blueprint for black middle-class formation, relatively few individuals – called taxi bosses – who resemble the mafia within the taxi industry and parts of the formal private sector and the state have benefited from the development of a particular set of extra-legal, social, economic and political relations. In contrast, the majority of taxi drivers and owners of taxi vehicles continue to be marginalised from achieving decent livelihoods and accumulating wealth, while commuters are not provided with safe and affordable public transport.

How Does Uber Tie Together a Digital Economy and Technological innovation?

The business landscape has undergone a transformative era with the rise of the digital economy and technological innovation. Even traditionally stable industries have experienced disruptions. This abstract explores the remarkable journey of Uber, a company that has achieved household name status and become a Fortune 500 giant. From its modest beginnings to its current status as a multi-billion-dollar powerhouse, Uber serves as an inspiring example of technological progress, innovation, and entrepreneurial success in the digital age. The rise of Uber showcases the significant influence of technology on traditional sectors like transportation. With its groundbreaking platform, Uber completely transformed how people travel, posing a challenge to the long-established taxi industry. This article delves into how Uber utilized digital technologies to develop a convenient and efficient transportation service that revolutionized the entire industry. Through its success story, it exemplifies the potential for ambitious startups to disrupt established markets and prosper in today's dynamic digital economy.

An Approach for Discovering Urban Transport Service Problem Based on Hotline

This paper presents a methodology for actively discovering knowledge in transport hotline databases by analyzing complaints reported by citizens, aiming to assist transportation management departments in planning actions to investigate and improve service quality. The proposed model uses text mining techniques and applies latent Dirichlet allocation (LDA) to identify topics that are related to transportation services. Consequently, we actively analyzed over 230,000 phone calls occurring in a certain province between 1st January and 31st December 2021. Specifically, we actively analyzed nearly 22,000 phone calls about the taxi industry within a selected city, and identified six topics, including lost and found (27.1%), car blocking (20.6%), attitude and behavior (17.1%), online car-hailing (12.8%), illegal operations (11.2%), and fare issues (11.2%). By actively referring to past and ongoing best practices, we actively recommend several policy implications. The proposed method thus actively transforms the service center record into a customer feedback-based assessment system to intently monitor drivers’ professionalism while efficiently addressing customers’ complaints and concerns.

A model for the adoption of transport management systems in the South African taxi industry

A model for the adoption of transport management systems in the South African taxi industry

Profit Analysis of Taxi Industry Under the Sharing Economy Business Model - Take Didi Kuaidi as An Example

The emergence of the sharing economy provides the value reconstruction of the scarcity of idle resources, provides an efficient business model for economic growth and transformation, and becomes an important driver of supply-side reform. Didi Kuaidi is a combination of transportation and the Internet, that is, a form of application that combines actual objects with the Internet. For people's travel, it can also better meet people's short-distance needs, and a new business model makes it have a larger commercial space. At present, Didi Kuaidi ranks in the forefront of domestic Didi Kuaidi operators and seems to be able to sit in Diaoyutai from the perspective of scale. However, Didi Kuaidi still faces many challenges. This paper analyzes the connotation and role of the sharing economy, expounds the operating mechanism and development status of the sharing economy business model, and then makes a case analysis of Didi Kuaidi's business model. It puts forward policy suggestions for the healthy and sustainable development of the sharing economy, including focusing on the construction of Didi Kuaidi, improving service management procedures, actively realizing automated system operation, rational business operation, transforming operating costs, and expanding Didi Kuaidi's promotion methods. It is of great significance to the development of Didi Kuaidi.

How does autonomous vehicles affect taxi industry? A two-stage Van Damme based tripartite evolutionary game perspective

As urban passenger transportation focuses more on economic efficiency and road safety, autonomous driving technology is being introduced in the taxi industry. Interests differ among automobile manufacturers, taxi companies, and the government in promoting the adoption of autonomous taxis (ATs). This paper investigates the impact of multiple factors in the mixed traffic operation mode on the tripartite game using the two-stage Van Damme model. It also analyzes the game-breaking key to automobile manufactures' decision in the dual stable situation. The findings are as follows: (1) Under government non-promotion, independent R&D guides taxi companies to adopt ATs more effectively. Under government promotion, the social acceptance and loss of technology dominance have varying impacts on the game results. (2) Adjusting infrastructure cost and subsidy intensity can lead to a single stable situation when taxi companies and the government adopt a wait-and-see approach. (3) The loss of technology dominance shifts game leader from automobile manufacturers to the government. (4) Taxi companies would only adopt ATs when the social acceptance is moderate, as it exhibits an inverted U-shaped relationship. These findings provide valuable insights for how to better promote the adoption of ATs under both promotion and non-promotion by the government.

Comparative Analysis of Usage Patterns and Underlying Determinants for Ride-hailing and Traditional Taxi Services: A Chicago Case Study

As app-based ride-hailing (or e-hailing) services have achieved great success worldwide, the traditional taxi industry faces an unprecedented crisis. To gain a deeper understanding of these two distinct modes that both offer door-to-door mobility services, in this study, we use Chicago as a case to comparatively analyze the travel patterns of the app-based ride-hailing and traditional taxi services and understand how socio-demographic and urban land use attributes affect the usage of two services in temporal and spatial dimensions. We employ the local regression models named geographically and temporally weighted regression (GTWR) models that can capture the spatiotemporal nonstationarity between variables as the primary analysis tool. Four GTWR models that predict the average hourly taxi or ride-hailing trip volume on weekdays or weekends for each community area are carefully constructed with R^2 all above 0.98. The nonstationarity test shows all variables exhibit extra local variations, indicating the necessity of using the GTWR models to explore the attributes’ spatiotemporal impacts. Spatial error models (SEM) and ordinary least square (OLS) models, global regression models, are also built as comparisons and benchmark references. The differences between global and local regression models are illustrated through clustering analysis. To compare and contrast the usage patterns of ride-hailing and taxi services, we analyze the temporal-spatially varying coefficients of GTWR models. Interpretations are provided for our interesting findings, including the strong trip generation power of the population in the South Side area, the attitude of white people towards taxi services is positive but ambiguous towards ride-hailing services, young people's opposing behaviors towards taxi services on weekdays and weekends, and the opposite relationship between transit and taxi or ride-hailing in certain areas. Based on these key findings, we offer some planning and operational suggestions, such as developing mobile apps, implementing price-related strategies, strengthening partnerships with local businesses, building multi-modal transportation, clarifying customer segmentation, providing auxiliary services, etc.

Students Satisfaction of Using E-Hailing in UiTM Puncak Alam, Selangor, Malaysia

E-hailing is a transportation service that allows passengers to book a ride through a digital platform or mobile application instead of hailing a taxi or car on the street. The services connect passengers with drivers of private vehicles, often through a network of independent contractors. Key companies providing e-hailing services around the world include Grab, Uber, Maxim and others. Many says that e-hailing has disrupted the traditional taxi industry by offering more convenience, pricing transparency, and even offer a higher level of service through driver and vehicle ratings. These services have become an integral part of modern urban transportation, providing an alternative to traditional taxis and public transportation. Providers of e-hailing work hard to keep customers satisfied and loyal to their platforms through a combination of strategies and features designed to enhance the overall customer satisfaction. This study aims to investigate the roles of accessibility, safety, comfortability and price on customers’ satisfaction on e-hailing services, and proposes some suggestions to improve the services. This research espoused a quantitative research methodology by using a survey approach. Data was collected from 108 retail management students of the Faculty of Business and Management, Puncak Alam Campus, Selangor Malaysia. The data were analysed using the Statistical Package of Social Sciences (SPSS). The analyses carried out inclusive of descriptive analysis and cross tabulation analysis. The results show the four variables have roles on students’ satisfaction. This study also determines to provide several solution factors about some e-hailing issues faced by the students. This finding will provide the solutions on how e-hailing needs to improve their services to satisfy students in UiTM Puncak Alam Campus, Selangor Malaysia.

Effects of Aging on Taxi Service Performance: A Comparative Study Based on Different Age Groups

Rapid population aging has significantly impacted labor supply and posed substantial challenges for the taxi industry, which have not yet been fully comprehended. Here, for the first time, we employ a large-scale dataset of taxi driver operations from China, establishing a comprehensive indicator system of taxi service performance, encompassing economic, environmental, and safety aspects. Through the application of multivariate regression models and other statistical analysis techniques, we have thoroughly investigated the mechanisms through which aging influences taxi service performance. Our research reveals that older drivers, despite exhibiting higher operational efficiency and greater inclination towards stability, underperform in time efficiency metrics, such as income per hour worked, owing to a more conservative working style. Furthermore, aging manifests negative effects on safety and environmental performance. Adjusting the driving strategies of older taxi drivers, such as regulating daily working hours and refining passenger-searching area preferences, can help mitigate these adverse impacts.