Driver Perceptions on Taxi-sharing and Dynamic Pricing in Taxi Services: Evidence from Athens, Greece.

The taxi industry has changed dramatically during the last decade, as ride-sourcing applications, ride-sharing and alternative pricing schemes have emerged, either as complementing or competitive services and strategies. After some years of familiarity with such trends, it is interesting to explore where the taxi industry stands with respect to possible service innovations. This paper explores behavioral patterns of drivers, focusing on issues such as their preferred way of conducting business, and their views on introducing taxi-sharing and dynamic pricing. Data collected from a face-to-face questionnaire survey in Athens, Greece are exploited, and appropriate econometric models are developed for the purposes of the study. The analysis shows that young and/or educated drivers, as well as those who are familiar with new technologies are more willing to accept innovations in taxi services. Results from a stated choice experiment show that on average 3.5 euros is the extra charge that the taxi market would accept to offer a taxi-sharing service. However, results reveal that the value of taxi-sharing varies across different groups of drivers. Overall, findings indicate that in the years to come, competition by other services, (e.g. ridesharing) will force the taxi industry to adopt new models of operation and pricing.

Using Fuzzy Clustering of User Perception to Determine the Number of Level-of-Service Categories for Bus Rapid Transit

The concept of level of service (LOS) is meant to reflect user perception of the quality of service provided by a transportation facility or service. Although the LOS of bus rapid transit (BRT) has received considerable attention, the number of levels of service of BRT that a user can perceive still remains unclear. Therefore, in this paper, we address this issue using fuzzy clustering of user perception. User perception is defined as a six-dimension vector of the perceived arrival time, perceived waiting time, bus speed perception, passenger load perception, perceived departure time, and overall perception. A smartphone-based transit travel survey system was developed, with which user perception surveys were conducted in three BRT systems in China. Fuzzy C-Means clustering, improved using a simulated annealing genetic algorithm, was adopted to partition user perception into two to ten clusters. Seven cluster validity indices were used to determine the appropriate number of LOS categories. Our results indicate that users can perceive two to four levels of service.

Understanding Transantiago Users’ Motivations for Paying or Evading Payment of Bus Fares

Transantiago, the public transport system implemented in Santiago, Chile, remains a controversial subject of public debate due to constantly increasing fare evasion rates throughout its decade-long existence. TheTransantiago, the public transport system implemented in Santiago, Chile, remains a controversial subject of public debate due to constantly increasing fare evasion rates throughout its decade-long existence. The research question under consideration in this paper is as follows: What motivates individuals to evade or pay bus fares? To answer this question, we developed a multidisciplinary study that combined relevant engineering expertise with a sociological perspective and combined quantitative analyses with qualitative methodologies to include new variables and categories that previous studies on the subject have omitted. We formulated a poll, which was administered to Transantiago, the public transport system implemented in Santiago, Chile, remains a controversial subject of public debate due to constantly increasing fare evasion rates throughout its decade-long existence. The research question under consideration in this paper is as follows: What motivates individuals to evade or pay bus fares? To answer this question, we developed a multidisciplinary study that combined relevant engineering expertise with a sociological perspective and combined quantitative analyses with qualitative methodologies to include new variables and categories that previous studies on the subject have omitted. We formulated a poll, which was administered to 503 public transport system users. The data we obtained were analyzed using a factor analysis. As a result, we identified 6 dimensions that explain motivations for fare evasion: i) behavior and social norms, ii) the public transport service’s image, iii) social acceptance of evasion, iv) trip planning, v) anti-evasion methods, and vi) fear of law enforcement. public transport system users. The data we obtained were analyzed using a factor analysis. As a result, we identified 6 dimensions that explain motivations for fare evasion: i) behavior and social norms, ii) the public transport service’s image, iii) social acceptance of evasion, iv) trip planning, v) anti-evasion methods, and vi) fear of law enforcement. research question under consideration in this paper is as follows: What motivates individuals to evade or pay bus fares? To answer this question, we developed a multidisciplinary study that combined relevant engineering expertise with a sociological perspective and combined quantitative analyses with qualitative methodologies to include new variables and categories that previous studies on the subject have omitted. We formulated a poll, which was administered to 503 public transport system users. The data we obtained were analyzed using a factor analysis. As a result, we identified 6 dimensions that explain motivations for fare evasion: i) behavior and social norms, ii) the public transport service’s image, iii) social acceptance of evasion, iv) trip planning, v) ineffective anti-evasion measures, and vi) fear of law enforcement.

People-focused and Near-term Public Transit Performance Analysis

Public transit ridership forecasts have long played a role in understanding the potential success of a policy or investment, but their limitations have led researchers and practitioners to identify other performance analysis approaches. Accessibility, or the ease of reaching opportunities, has become very popular and widely used for this purpose. But commonly used accessibility measures also embody weaknesses that are seldom acknowledged; these limit their utility for truly understanding the benefits of transit investments. In this paper, we identify the pros and cons of these competing approaches and offer a third strategy. Specifically, we describe how revealed travel behavior data, potentially combined with near-term forecasts, can provide information about how current public transit users will be affected by a new project. While acknowledging the limitations of this approach, we demonstrate how accessibility can be misleading when applied without an understanding of ridership patterns.

Occupational Health and Job Satisfaction Assessment of Bus Rapid Transit (BRT) Drivers

Several studies have focused on ergonomics of commercial and urban bus drivers; however, there exists a dearth of research on BRT drivers. This study was conducted to investigate the factors affecting the BRT drivers' mental health and satisfaction. The study was carried out on 171 BRT drivers in Tehran, Iran. The required data were collected through two questionnaires. The Classification and Regression Tree (CART) and Hierarchical clustering (HC) was used to extract factors affecting mental health and satisfaction of BRT drivers. The important factors affecting BRT drivers' mental health were: dispute with passengers, depression, BMI, criminal behaviours of passengers, driver's retirement conditions, driver's family conditions, fatigue and the rostering. In addition, the most important factors affecting driver satisfaction were: bus repairs, driver's seat and the sound inside the cabin. Possible practical application includes: creating a counseling and psychotherapy unit and improving the quality of buses and repairment.

User Acceptance of Autonomous Public Transport Systems (APTS): Extended UTAUT2 Model

The purpose of this study is to investigate the factors affecting the acceptance and use of the APTS by its potential users. To achieve this, an integrated and expanded user acceptance model is introduced to explain the factors affecting the Behavioral Intention to use the APTS. A total of 316 surveys were conducted, from 275 participants by online surveys and 41 participants by face to face interviews. With the data that are acquired from Public Transportation (PT) users in Istanbul, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model is modified and Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, Habit, Trust and Safety, Perceived Usefulness, Perceived Risk and Behavioral Intention constructs are utilized in the model. Age, gender and frequency of PT usage are included in the model to examine the moderating effect on the constructs while the model is tested with Structural Equation Modeling (SEM). The proposed model explains the 72 % of variances in this study which proves that the model has stronger predictive power compared with the previous Technology Acceptance Model (TAM) and UTAUT models. Performance Expectancy, Social Influence, Habit, and Trust and Safety constructs are concluded to have significant positive effects on Behavioral Intention. Public usage and acceptance are necessary for the complete utilization of APTS. The findings of these studies are hoped to guide the decision-makers of the PT industry to understand the factors affecting the use and acceptance of APTS and take the actions accordingly.

Increasing Boarding Lost Time at Regular Bus Stops during Rainy Conditions: A Case Study

Inclement weather conditions affect the behavior of travelers and transportation system operations. Understanding this influence can help improve operational planning schemes for any mode of transport, especially for buses. One of the factors that can be affected by rainfall is the time expended by a passenger from the moment a bus opens its doors until he/she boards the bus. This time is known as the boarding lost time (BLT); it was first introduced in the last edition of the Transit Capacity and Quality of Service Manual (TCQSM). TCQSM only considers the BLT for bus rapid transit (BRT) stations with more than one berth. Weather conditions are not considered when calculating the current BLT for a BRT system, given the provision of protective shelters over the entire boarding area of such stations. Furthermore, recommendations with regard to the BLT for regular bus stops have not been provided. This paper presents analyses of the BLT for a two-berth regular bus stop under different rainy conditions. The findings demonstrate that the increment in the BLT under heavy rainfall is significantly higher than the difference between the BLTs of Berth 2 and Berth 1 in the absence of rainfall.

Modeling bus bunching and anti-bunching control accounting for signal control and passenger swapping behavior

The conventional bus propagation process has two main shortcomings: one is bus bunching, the other is extra energy consumption by idling at signalized intersection and unexpected speed variation along the route. To overcome these problems simultaneously, an extended bus propagation model and an anti-bunching control are proposed. To extend the time-based bus propagation model, we employ finite state machine and intelligent driver model to establish a spatial-temporal based bus propagation model accounting for bus dynamic motion and passenger swapping behavior between bunching buses. To mitigate bus bunching and improve bus fuel economy in a cyber-traffic environment, an anticipated average speed planning is employed to improve headway regularity and reduce the chance of encountering red light, and then model predictive control accounting for state and control constraints is used to generate a smooth speed trajectory for connected bus to follow the commands given by anticipated average speed planning, which will in turn ensure that all the connected buses traverse signalized intersection and approach downstream stop in ecological driving behaviors. Numerical simulations show that the proposed model can imitate passenger swapping behavior when bus bunching occurs, and the anti-bunching control is suitable to mitigate bus bunching and guide connected bus to traverse signalized intersection and reach downstream stop with fewer delays.

Case study of property value transfer attributed to transit: spatial and temporal hedonic price impact of light rail in Minnesota’s Twin Cities

Does the proximity of transit increase property values, and can one example apply to another? Using a spatial and temporal hedonic price framework, a study of light rail transit’s impact on residential property values compares the station area property impacts of the Green and Blue lines in Saint Paul and Minneapolis. The study also points to when “value transfer” (used here to describe the comparison and application of property value impacts near transit) is appropriate, and what practitioners should keep in mind to maximize the effectiveness of the exercise. In the case of value transfer for transit, the study finds that intimate local knowledge matters more than special modeling specifications to appropriately capture the impacted properties and transfer the return of investment.

Factors Influencing Fixed-Route Transit Decision-Making: Exploring Differences by Disability and Community Type

Transit agencies utilize the following complementary initiatives to encourage greater fixed-route transit usage by people with disabilities: (1) implement more rigorous paratransit eligibility determination practices and (2) address the factors that deter people with disabilities from using fixed-route transit. This research focuses on the latter and uses previously conducted survey data to determine the most important factors individuals with disabilities consider when deciding to use various transportation options, and how these factors vary by disability and community type. Findings indicate that individuals with mobility impairments consistently rated the built environment factors as more important to their transit mode decision-making than scheduling-related factors. Findings also highlighted the importance of addressing complex trips when assisting riders with intellectual and cognitive disabilities. The current study also revealed that people with disabilities experience barriers differently based on where they live, suggesting the need for context sensitive interventions to support fixed-route ridership. Transit agencies should utilize this information to employ more targeted interventions to encourage greater fixed-route transit usage for individuals with disabilities.