Macroscopic and Dynamic Model of Urban Rail Transit with Delay and Congestion
Toru Seo, Tokyo Institute of Technology
Kentaro Wada, University of Tokyo
Daisuke Fukuda, Tokyo Institute of Technology
Urban mass transit often operates with high service
frequencies to serve large passenger demand, such as those during morning
commute. Their objective is to transport as many passengers as quickly as
possible. To do so, they require careful planning because their operation can be
delayed by two types of congestion, namely, train-congestion (i.e., knock-on
delays) and passenger boarding congestion, both of which interact with each
other. However, there are no tractable models representing such dynamics of
transit systems; and it makes difficult to analyze management strategies of them
(e.g., an optimal peak-period toll in morning commute situations) in a general
and tractable way.
Effect of Fare Policies on Dwell Time: A Case Study for the Pittsburgh Region
Mark Egge, Carnegie Mellon University
Zhen Qian, Carnegie Mellon University
Bus fares may be collected when passengers board or immediately prior to passengers alighting. Between these “entry fare” and “exit fare” policies, however, little work has been done to quantify their respective impacts on passenger-stop delay at stops, namely the dwell time. The Port Authority of Allegheny County (PAAC) is one of few mass transit systems to currently employ both entry fare and exit fare policies. The PAAC’s alternating fare policy offers an ideal natural experiment to investigate the effect of fare collection policy on dwell time. PAAC Automated Passenger Counter (APC) and Automatic Vehicle Location (AVL) data are analyzed to estimate dwell time under no fare collection, entry fare, and exit fare policies. It is found that the choice of fare policy can significantly impact dwell time associated with fare payment, but also that the effect of fare policy varies with route characteristics. The findings suggest that a transit system seeking to minimize fare payment’s contribution to total trip dwell time may be most effective by operating an entry fare policy on local routes with frequent stops and evenly distributed ridership, and an exit fare policy on express and BRT routes with fewer stops and substantial passenger movements at major stops.
Modeling Bus Capacity for Isolated Bus Stops
Chao Wang, Southeast University
Zhirui Ye, Southeast University
Yunlong Zhang, Texas A&M University
Wei Wang, Southeast University
Mingzhou Jin, University of Tennessee, Knoxville
This study proposed a bus capacity estimation method for bus stops, which were isolated from the influences of traffic signals and other bus stops. Data collected from the seven most common types of bus stops in China were used to validate the proposed model. The results indicated the arrival process obeyed Poisson distribution and the service time fit a lognormal distribution. In light of this, queuing models for both single-berth and multi-berth stops were developed to estimate bus stop capacity. As a comparison, the HCM model was also used for bus stop capacity estimation. The results showed that the proposed method was more accurate and reliable, with an 8.44% MAPE (Mean Absolute Percentage Error) compared to a MAPE of 17.42% from the HCM method. Sensitivity analyses were also conducted to investigate the effects of bus arrival rate, service time, and the number of bus berths on the capacity of bus stops.
Bilevel Model for Design of Transit Short-Turning Services Considering Bus Crowding
Yuxiong Ji, Tongji University
Yuchuan Du, Tongji University
H. Zhang, University of California, Davis
We develop a bi-level model to design the short-turning strategy on a bus route. The upper-level model aims at minimizing the total cost including operational cost, passengers’ waiting time cost and in-vehicle travel time cost. The lower-level model is a Logit model to assign passenger demand to different service patterns. To capture the influence of bus crowding and seat availability on passengers’ riding experiences, we develop a Markov model to describe the seat-searching process of a passenger. The Markov model is incorporated in the upper-level model to reflect the effect of bus crowding on passengers’ perceived travel times and in the lower-level model to reflect the effect of bus crowding on the service pattern choices of passengers. Algorithm is developed to produce optimal values of the frequencies of service patterns and the turnback points of short-turning patterns. The proposed methodology is evaluated in a case study. The case study demonstrates the convergence of the developed algorithm. Compared with the strategy suggested by a model that ignores the effect of bus crowding, the strategy produced by the proposed model could provide passengers with better transit experiences and reduce the total cost. Sensitivity of the optimal design to seat capacity is also investigated.
Nothing But a Good Ride: Influences of Satisfaction and Loyalty in Public Transport
Dea van Lierop, McGill University
Madhav Badami, McGill University
Ahmed El-Geneidy, McGill University
Public transport ridership retention is a continuous challenge for cities around the world. In order to develop comprehensive strategies aimed at retaining riders, it is necessary to understand the aspects of public transport that influence users to become loyal to the system. This paper systematically analyses relevant literature regarding the causes of satisfaction and loyalty in public transport. We find that service factors most influencing overall satisfaction are on-board cleanliness and comfort, punctuality and frequency of service, as well as courteous and helpful behaviour from the public transport agencies’ personnel. On the other hand, loyalty is influenced by users’ perceptions of value for money, on-board safety and cleanliness, reliability of the system, and the image and commitment to public transport that the user feels. Furthermore, the results of this review elucidate that the concept of loyalty is best defined based on a user’s intention to continue using the service, willingness to recommend it to others, overall satisfaction, but also and most importantly, a user’s image of and involvement with public transport. Public transport users who have a positive image of the agency and consider public transport an integral component of a city dweller’s daily life are more likely to demonstrate loyalty and act like ambassadors for public transport agencies as they will recommend the service to others.
Reinforcement Learning Approach for Coordinated Passenger Inflow Control of Urban Rail Transit in Peak Hours
Zhibin Jiang, Tongji University
Wei Liu, Tongji University
Bingqin Zhu, Tongji University
In peak hours, when the limited transport capacity of urban rail transit is hard to meet the travel demands, the density of the passengers waiting at the platform exceeds the critical density of the platform. Coordinated passenger inflow control strategy is required to adjust the inflow volume and relieve some demand pressure in crowded metro stations so as to ensure the safety of all passengers. However, such strategy is usually determined by the working experience of the operation staff, which is lack of the consideration of overall and dynamic performance. In this paper we introduce a new method to optimize the inflow volume of each station at a certain period of time with the aim of minimizing the safety risks in metro stations, based on reinforcement learning. We present the basic principles and fundamental components of reinforcement learning in the context of our problem domain. The simulation experiment carried out on a real-world metro line in Shanghai is constructed to test the performance of the approach. The empirical results show that reinforcement learning lead to inflow volume control strategy that is highly effective in minimizing the safety risks by reducing the frequency of passengers being stranded. Additionally, the strategy also helps to relieve the passenger congestion at certain stations.
Perception of Transfer Waiting Time at Stops and Stations in Nanjing, China
Yanjie Ji, Southeast University
Ruochen Zhang, Southeast University
Liangpeng Gao, Southeast University
Yingling Fan, University of Minnesota, Twin Cities
Travel time has been found to be the most powerful indictor of mode choice. However, overlong waiting time and waiting time on perception in transit travel are believed to significant negative obstacles to attract more choice passengers. Although previous studies have focused on traveler response to some certain factors, mainly focused on real-time information devices, fewer have addressed the mechanism of traveler response change induced by diversified factors, especially in China. To determine and weigh the different effect of factors on waiting time perception, the study conducted surveys to gain passengers’ perceptions of waiting time at different types of transit stops/stations in Nanjing, China, taking account of temperature, weather, time of day and time of week. Deep interaction and affecting mechanism of waiting time perception was determined with the SEM model. After variables filtering, a regression analysis was applied to investigate the impacts of various characteristics on transit users' perceptions of waiting time fitted with actual waiting time data. Results suggested that the waiting time at stops with no amenities could be perceived over twice as long as passengers really spend. The amenities at stops/stations could significantly reduce perceived waiting times and the difference of amenities on effect was pointed out. The complete amenities combination of bench, shelter and real-time information sign device can nearly erase the deviation between perceived time and actual time incurred as passengers’ waiting period. The appropriate installation of stops/stations amenities are made predominately based on the results of estimations.
Evaluation of Bus Transport Service Improvement Needs and Activities in Istanbul, Turkey
Aybike Ongel, Bahcesehir University
Ozum Asya Kaynarca, General Directorate of IETT
Abdullah Aktel, Tubitak Tusside
ALI UNAL, Tubitak Tusside
Fahrettin Eldemir, Yildiz Technical University
Recently, transportation policies in urban areas have been towards making public transportation more attractive and reducing private vehicle miles traveled. Public transportation service quality is an important factor in determining traveler’s mode choice. Therefore identification of service needs and hence improving service quality are essential for shifting travelers from private cars to public transportation. Bus transportation authority of Istanbul, IETT conducts customer satisfaction surveys annually. IETT also takes into account the expert panel opinions with regards to bus service improvement needs and activities when developing Bus Transportation Action Plans. This study aimed to identify the improvement needs and activities of bus transport service in Istanbul. Service improvement evaluation was conducted both quantitatively using customer satisfaction surveys and qualitatively using expert panel opinion. Service quality indexes were calculated for regular buses and Bus Rapid Transit (BRT) system as well as for the overall bus transport service in Istanbul. The priority improvement areas were assessed using Satisfaction-Priority quadrant maps. The priority areas with improvement needs identified from the maps include comfort and security for regular buses, and comfort and availability for Bus Rapid Transit system. The expert panel provided improvement activities for the bus system in Istanbul accordingly.
Improving Predictions of the Impact of Disturbances on Public Transport Usage Based on Smartcard Data
Menno Yap, TU Delft
Sandra Nijënstein, HTM Personenvervoer N.V.
Niels van Oort, Delft University of Technology
The availability of large quantities of smart card data from public transport travelling the last decades allows analyzing and predicting current and future public transport usage. Predicting the impact of planned disturbances, like temporary track closures, on public transport ridership is however an unexplored area. In the Netherlands, this area becomes increasingly important, given the many track closures operators are confronted with the last years. In this study we investigated the passenger impact of four planned disturbances on the public transport network of Den Haag, the Netherlands, by comparing predicted and realized public transport ridership using smart card data. A two-step search procedure is applied to find a parameter set resulting in higher prediction accuracy. We found that in-vehicle time in rail-replacing bus services is perceived about 1.1 times more negatively compared to in-vehicle time perception in the initial tram line. Besides, passengers do not seem to perceive the theoretical benefit of the usually higher frequency of rail-replacement bus services compared to the frequency of the replaced tram line. At last, no higher waiting time perception for temporary rail-replacement services could be found, compared to regular tram and bus services. The new parameter set leads to substantially higher prediction accuracy compared to the default parameter set. It supports public transport operators to better predict the required supply of rail-replacement services and to predict the impact on their revenues.
Benchmarking Focused on Satisfaction of Bus Transit Users
Luis Lindau, World Resources Institute (WRI)
Mariana Barcelos, WRI
Maria Beatriz Berti da Costa, No Organization
Carla ten Caten, No Organization
Cristina Albuquerque Moreira da Silva
Brenda Pereira, Embarq
Investing in quality of public transport is fundamental to keep and attract users and to foster more sustainable cities. Benchmarking is the adequate tool to identify best practices and promote an exchange of experiences to improve transport systems. Nevertheless, benchmarking focused on customer satisfaction imposes challenges due to the lack of standardization in collecting data and to the sociocultural biases inherent to opinion surveys. This paper presents a benchmarking analysis based on satisfaction data collected through a standardized survey. We propose a normalization of scores of satisfaction that: (i) reduces the effect of sociocultural biases, (ii) enables the comparison of bus systems operating in different cities, and (iii) allows the identification of potential benchmarks. The proposed method proved suitable for identifying goals, priorities and attributes of bus transit systems that can serve as reference to other cities.
Data Envelopment Analysis-Based Transit Route Performance Evaluation
Tran Duong, Queensland University of Technology
Ashish Bhaskar, Queensland University of Technology
Jonathan Bunker, Queensland University of Technology
Boon Lee, Queensland University of Technology
Measuring the performance of transit routes plays a critical role in finding operational problems and helps transit agencies allocate resources effectively. To measure the performance of transit routes, using Brisbane as a case study we employ Data Envelopment Analysis (DEA) on 42 bus routes. The analyses show that, for technical efficiency measurement, service duration is statistically associated with inefficient routes, while for service effectiveness, space-km and on-time performance (OTP) have a potential role in improving the performance of ineffective routes.
Travel Time Perception in a Multimodal Public Transport Trip
Andreas Rau, tum create limited
Meng Meng, tum create limited
Hita Mahardhika, tum create limited
Perceived travel time in public transport trip directly affects passengers’ satisfaction and therefore is an essential factor for consideration when planning and operating the public transport system. In this context, this paper presents an empirical investigation of actual and perceived travel time at each stage in a bus-rail transport trip, where first mile, in-vehicle stage, transfer stage and last mile are all considered. Data on actual and perceived travel time, socioeconomic characteristics, trip characteristics and facility usage are collected by accompany survey undertaken from passengers’ originations to destinations. The results from a series of paired differences of means T-tests show that passenger do perceived travel time to be greater than the actual amount at each stage. Three linear regression models are developed for estimation of perceived walking, waiting and in-vehicle time. Results indicate that socioeconomic characteristics, trip characteristics and facility usage seem to have an impact on passengers’ travel time perception, while the travel time spent on the previous stage does not affect the perception too much.
Responding to Challenges of Designing High-Passenger-Capacity Metropolitan Rail Carriages
Selby Coxon, Monash University
Robbie Napper, Monash University
Metropolitan railways around the world are experiencing a significant increase in patronage. Higher passenger densities, particularly during peak times of the day, have implications for train punctuality, crowding, accessibility and passenger comfort. There is a growing literature that indicates that the design of passenger accommodation has a significant influence on passenger interactions such as length of time standing, proximity to fellow travellers, their dispersal and the overall perception of physical ease, reducing stress and tension. Rail transport operators face conflicting responses to the problem in balancing capacity with consistent timetables without compromising passenger comfort.
This paper collates research undertaken at the Monash University Mobility Design Lab that analyses the design and structural issues confronting the carriage layout of a high capacity metro service. The user experience of the carriage interior is an essential part of the overall environment. The outcome of this research is intended as an enabler for the creation of strategies to design and build the next generation metropolitan trains.
Stated-Preference Survey for Estimating Passenger Transfer Penalties: Design and Application to Madrid, Spain
Rocio Cascajo, Universidad Politecnica de Madrid
Andres Garcia-Martinez, Universidad Politecnica de Madrid
Transfers in multimodal urban trips imply a disutility for users, who perceive them as a penalty when using public transport. It is therefore important to estimate the utility associated to transfers and the main factors affecting it, to allow policymakers to reduce users’ perceived disutility and enhance their intention to use public transport. The aim of this paper is to develop a Stated Preference experiment as a means of estimating the penalty perceived by commuters when making transfers in multimodal urban trips. A web-based survey combining a Revealed Preferences and Stated Preferences survey was created using Ngene software, and an efficient design was applied to estimate multinomial logit models. We present here the first stage of the research, consisting of the design and results of the pilot survey of commuters travelling by metro or urban bus within the city of Madrid, Spain. The findings reveal a pure penalty independent of the variables in the model which increases with the number of transfers. Crowded transfers provide a disutility to commuters, which rises with the number of transfers involved in the route. Further research is needed to consolidate these results with those of a final survey.