Estimating the Capacity of a Curbside Bus Stop with Multiple Berths Using Probabilistic Models

Capacity estimation of a curbside bus stop is essential to evaluation of its operation, reliability and performance. Arrival buses and served buses will form an overflow queue and an interlocking queue in loading areas with high frequencies. Therefore, bus stop blockage may reduce the stop capacity. The capacity of a bus stop is modelled as a function of the blockage probability, the arrival of buses, and the service time, while considering the no-overtaking principle and allowable-overtaking principle. This study aims to estimate the capacity, minimum arrival time and maximum service time based on the blockage probability and number of berths. The results indicate that congestion can be effectively alleviated by increasing the number of berths when the demand for loaded buses is low due to the significantly changing probability threshold for a NO stop. A congestion and stopping principle is important when multiple bus routes converge at the same bus stop. By combination with an actual case, an optimal overtaking principle is obtained using a computer program written in the MATLAB environment. The developed methodology can be practically applied to determine the loading principle and designated stopping berths for multi-route buses

Car Delay Model near Bus Stops with Mixed Traffic Flow

This paper proposes a model for estimating car delays at bus stops under mixed traffic using probability theory and queuing theory. The roadway is divided to serve motorized and nonmotorized traffic streams. Bus stops are located on the nonmotorized lanes. When buses dwell at the stop, they block the bicycles. Thus, two conflict points between car stream and other traffic stream are identified. The first conflict point occurs as bicycles merge to the motorized lane to avoid waiting behind the stopping buses. The second occurs as buses merge back to the motorized lane. The average car delay is estimated as the sum of the average delay at these two conflict points and the delay resulting from following the slower bicycles that merged into the motorized lane. Data are collected to calibrate and validate the developed model from one site in Beijing. The sensitivity of car delay to various operation conditions is examined. The results show that both bus stream and bicycle stream have significant effects on car delay. At bus volumes above 200 vehicles per hour, the curbside stop design is not appropriate because of the long car delays. It can be replaced by the bus bay design

Development of Level-of-Service Criteria based on a Single Measure for BRT in China

Bus rapid transit (BRT) has gained popularity as a cost-effective way of expanding public transit services, and its level of service (LOS) is receiving increasing attention. However, relatively little is known about the precise criteria that can consistently and objectively classify the LOS of BRT into different levels. This paper introduces the measure of “unit delay” to develop BRT LOS criteria, defined as the sum of delays a bus experiences at stops and intersections and on a 100m link. Based on field surveys conducted on BRT in Changzhou, China, we obtained a unit delay data set and established BRT LOS criteria using Fuzzy C-means Clustering. The LOS criteria can be applied for operational, design, and planning analyses for BRT systems. A method to examine the operational conditions in spatial and temporal dimensions and pinpoint the service bottlenecks of a BRT system is presented

Queuing analysis and optimization of public vehicle transport stations: A case of South West Ethiopia region vehicle stations

Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options, sometimes illegally. The root cause is corruption, which leads to traffic jams, stops and packs vehicles beyond their safe carrying capacity, and violates passengers' human rights and freedoms. This study focused on optimizing the time passengers had to wait in public vehicle stations. This applied research employed both data-gathering sources and mixed approaches. Then, 166 samples of key informants of transport stations were taken using the Slovin sampling formula. The time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The study also focused on determining the minimal response time required for passengers and vehicles queuing to reach their ultimate destinations within the transportation stations in Tepi, Mizan, and Bonga. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4 hours to 1.5 hours, quality, safety and designed load performance calculations employed. Stakeholders are asked to implement the model and monitor the results obtained

Using digitalisation for data-driven freight curbside management. A perspective from urban transport planning

Given trends in urbanisation, e-commerce, active mobility and modal shifts, streets have sprung up as scenes of conflict where competing demands for curbside space have increased. Because public space is limited, urban transport planners are called to solve public space conflicts by defining how much space is allocated to specific users as a means to achieve sustainable cities. In the allocation of curbside space, freight parking operations are sometimes overlooked compared to other curbside uses such as private vehicles parking. However, limited space for freight deliveries generates negative impacts on urban traffic (e.g. due to double parking), as well as on emissions and companies’ efficiency (e.g. due to the need to cruise for parking). This thesis aims to contribute to current understandings of the need for and uses of data to inform curbside management decision-making for freight parking from the perspective of urban transport planning. To that end, a case study was conducted to collect and analyse data about freight curbside operations using quantitative and qualitative methods, and a cross-sectional research design facilitated the exploration of the impacts of curbside interventions on cities’ sustainability worldwide

Study on the Calculation Models of Bus Delay at Bays Using Queueing Theory and Markov Chain

Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Firstly, the process that buses are delayed at bays is analyzed, and it was found that the delay can be divided into entering delay and exiting delay. Secondly, the queueing models of bus bays are formed, and the equilibrium distribution functions are proposed by applying the embedded Markov chain to the traditional model of queuing theory in the steady state; then the calculation models of entering delay are derived at bays. Thirdly, the exiting delay is studied by using the queueing theory and the gap acceptance theory. Finally, the proposed models are validated using field-measured data, and then the influencing factors are discussed. With these models the delay is easily assessed knowing the characteristics of the dwell time distribution and traffic volume at the curb lane in different locations and different periods. It can provide basis for the efficiency evaluation of bus bays. Document type: Articl

Modelling bus delay at bus stop

A bus may be blocked from entering and exiting a stop by other buses and traffic lights. The objective of this paper is to model each type of delay under these phenomena and the overall delay a bus experiences at a stop. Occupy-based delay, transfer block-based delay and block-based delay are defined and modelled. Bus delay at stop is just the sum of these three types of delay. Bus arrival rate, bus service rate, berth number and traffic lights are taken into consideration when modelling delay. Occupy-based delay is modelled with mean waiting time in Queueing theory. Transfer block-based delay and block-based delay are modelled based on standard deviation of waiting time and the probabilities of their occurrences. Two stops in Vancouver, Canada are selected for parameter estimation and model validation. The unknown parameter is estimated as 0.4230 using Ordinary Least Squares (OLS), which indicates that 42.3% of waiting time variation can be attributed to buses being blocked by the buses in front and red light for the selected stops. Model validation shows the average accuracy rate of the proposed model is 75.07% for the selected stops. Bus delay at stop evidently increases when arrival rate is more than 85 buses per hour for the given service time (50 s), ratio of red time to cycle length (0.65) and berth number (2). We also figure out that bus delay at stop evidently increases when service time is more than 60 s for the given arrival rate (54 buses per hour), ratio of red time to cycle length (0.65) and berth number (2). The proposed model can provide a tool for bus stop design and offer the foundation for service quality evaluation of transit. First published online 28 January 201

An analysis of the passenger vehicle interface of street transit systems with applications to design optimization

This research analyzes the Passenger Vehicle Interface of the street transit systems and presents applications for design optimization. The Passenger Vehicle Interface (PVI) is defined as the interaction between the passenger and vehicle elements of the street transit system. Human observer and photographic studies were conducted in 17 cities in the United States and Canada to measure the time for queues of passengers to board various transit vehicles. The data were analyzed by considering seven factors that affect the Passenger Vehicle Interface: Human Factor, Modal Factor, Operating Practices, Operating Policies, Mobility, Climate and Weather, and Other System Elements. Those effects which could be quantified were divided into the categories of direction of flow, method of fare collection, and door characteristics and use. A series of equations for each of these categories was developed to predict passenger service time when the number of alighting or boarding passengers is known or estimated. A range of values was developed for the parameters of each equation to reflect the effects of unquantifiable factors such as the type of passenger, physical characteristics of the passenger, passenger preferences, baggage carried, seating configuration, and congestion. The use of Passenger Influence Zones has indicated that passenger service time can range from approximately six to 14 percent of total trip time, depending upon vehicle type, door use, and method of fare collection. These zones have also been used to indicate how vehicle door use and characteristics can increase berth requirements by up. to 200 percent, and New different methods of fare collection can increase berth productivity in terms of passengers per hour by 87 percent. Distributions of passenger service times through the vehicle doors were identified based on the analysis of photographic studies and determined to be represented by an Erlang function. The analysis also inferred that the K value in the Erlang function is equal to the number of doors on the vehicle and that the minimum service time is approximately equal to half the average service time. The validity of the Erlang functions was determined by using the special purpose simulation programming language, GPSS, and the Erlang functions to estimate the time requirements for queues of passengers to board vehicles. The simulated times were compared with observed times, and the differences were found to be not statistically significant at the 95 percent level. A GPSS model was used to simulate the operations of a street tran sit loading area and to evaluate the effects of method of fare collection upon queue length and average waiting time under varying rates of passenger arrivals. This research provides sufficient information to perform sub- optimizations of several operations within the Passenger Vehicle Interface. Although not directed toward an optimization of street transit systems, it does provide the necessary information about the Passenger Vehicle Interface for others to perform this optimization after they have assembled comparable information on system elements and other interactions

Priority infrastructure for minibus-taxis : an analytical model of potential benefits and impacts

Many governments in the global south are grappling with challenges of improving the quality of informal transport, and an inability to pay for service improvements. This paper asks the question whether efficiency benefits might be gained through strategic implementation of once-off infrastructure interventions providing priority to informal vehicles at intersections. We note that informal drivers already indicate this demand through (illegal) driving behaviour in traffic. We use a drone to observe indicative behaviours among minibus-taxi drivers in South Africa. We identify interventions that would formalise this behaviour: a single lane pre-signal strategy, queue-jumping lane, and dedicated public transport lane. The objective of the paper is to quantify the potential economic impacts of such treatments on minibus-taxi operators, passengers and other road users. The findings indicate that substantial savings could be realised in terms of travel time, user cost, and operating cost to taxi passengers and drivers without additional costs being incurred by other road users. The single-lane pre-signal strategy, the queue-jumping lane and the dedicated taxi lane saw a decrease in total hourly cost of 12%, 14% and 30% respectively, including construction cost, user cost, and agency cost, indicating a net social benefit. If part of these savings were passed on to passengers, priority infrastructure could serve as an implicit subsidy to public transport users.The Volvo Research and Educational Foundation (VREF) via the BRT Centre of Excellence.http://www.journals.co.za/ej/ejour_civileng.htmlam2022Civil Engineerin

Modelling bus bunching and holding control with vehicle overtaking and distributed passenger boarding behaviour

Headway fluctuation and bus bunching are commonly observed in transit operations, while holding control is a proven strategy to reduce bus bunching and improve service reliability. A transit operator would benefit from an accurate forecast of bus propagation in order to effectively control the system. To this end, we propose an ‘ad-hoc’ bus propagation model taking into account vehicle overtaking and distributed passenger boarding (DPB) behaviour. The latter represents the dynamic passenger queue swapping among buses when bunching at bus stops occurs and where bus capacity constraints are explicitly considered. The enhanced bus propagation model is used to build the simulation environment where different holding control strategies are tested. A quasi first-depart-first-hold (FDFH) rule is applied to the design of headway- and schedule-based holding control allowing for overtaking, with the objective to minimise the deviation from the targeted headway. The effects of control strategies are tested in an idealized bus route under different operational setting and in a real bus route in Guangzhou. We show that when the combined overtaking and queue-swapping behaviour are considered, the control strategies can achieve better headway regularity, less waiting time and less on-board travel time than their respective versions without overtaking and DPB. The benefit is even greater when travel time variability is higher and headway is smaller, suggesting that the control strategies are preferably deployed in high-frequency service