Bus capacity--how many buses a bus stop or facility can serve in a given period of time--is not just a theoretical concept, but something with real impacts on bus operations in terms of bus speed and reliability. The papers in this session advance the understanding of bus capacity in the following areas: mid-block bus stop capacity with and without yield-to-bus rules, bus-bus interference at bus stops and its effects on bus stop queuing and dwell time, optimizing the vehicle capacities and frequencies used on the routes in a transit network, and accounting for passengers with mobility aids, strollers, large packages, etc. when estimating dwell time.
Frequency and Vehicle Capacity Determination Using a Dynamic Transit Assignment Model
Oded Cats, Delft University of TechnologyShow Abstract
Stefan Glück, Delft University of Technology
We integrate for the first time a dynamic transit assignment model into the tactical planning phase. The settings of service frequencies and vehicle capacities determine line capacity and have significant consequences for level of service and operational costs. The objective of this study is to determine frequency and vehicle capacity at the network-level while accounting for the impact of service variations on users and operator costs. To this end, we propose a simulation-based optimization approach. The proposed model allows accounting for variations in service headways and crowding as well as their consequences for passenger flows distribution, all of which have not been accounted for in the tactical planning insofar. Practical benefits of the model are demonstrated by an application to a bus network in the Amsterdam metropolitan area. This study contributes to the development of a new generation of methods that integrate reliability into the tactical planning phase to improve service quality.
Capacity Estimation of On-Street, Mid-Block, Off-Line Bus Stops Considering Yield-to-Bus Rule
Faheema Hisham, Queensland University of TechnologyShow Abstract
Jonathan Bunker, Queensland University of Technology
Ashish Bhaskar, Queensland University of Technology
The effectiveness of an on-street bus facility is dependent on general traffic volume that shares the buses’ travel lane. The Transit Capacity and Quality of Service Manual (TCQSM) methodology estimates facility bus capacity based on critical stop operation. The aim of this study is to better understand performance of an on-street, mid-block, off-line bus stop by relating bus stop capacity to adjacent lane traffic volume. Contributions of this paper are twofold. The TCQSM methodology incorporates the impact of adjacent lane traffic volume on stop bus capacity at mid-block bus stops through its effect on re-entry delay, however does not consider the impact of the bus stop itself on adjacent lane traffic capacity. This paper introduces a novel methodology to estimate the additional time required to accommodate adjacent lane traffic volume under saturated conditions. Second, the TCQSM methodology does not reflect the impact of yield-to-bus (YTB) rule on re-entry delay at jurisdictions where it applies. This paper modifies the current TCQSM methodology by allowing for the YTB rule. A microscopic simulation model is developed in-order to cross validate the theoretical model developed.
Analyzing the Impact of Bus Stop Queuing and Bus Interactions on Bus Dwell Times
Travis Glick, Portland State UniversityShow Abstract
Miguel Figliozzi, Portland State University
Dwell, the amount of time a bus services a bus stop, is a primary contributor to transit travel times and variability. The Transit Capacity and Quality of Service Manual (TCQSM) capacity analysis incorporates the concept of a failure rate to estimate the delays caused by a bus arrival at a stop when all loading areas are occupied. In the TCQSM, failure rate is used in combination with dwell time variability and the average dwell time to estimate a value that is added to the dwell time and the clearance time to reach a desired failure rate. Empirical research efforts have not yet quantified these type of delay. Utilizing new bus interaction scenarios and variables this research quantifies the impacts of different types of bus stop failure and interactions in Portland, OR. Novel results of detailed statistical analysis utilizing linear and log-linear regressions are discussed and compared. Results show that the interaction of buses of different routes have a measurable and significant impact on dwell durations. These results may be applied to improve dwell prediction models and to analyze the potential impact of route overlaps on dwell times.
Dwell Time Models of Passenger Encumbrance and Mobility Aid Use on Low-Floor Transit Vehicles
Lidia Kostyniuk, University of Michigan, Transportation Research InstituteShow Abstract
Clive D'Souza, University of Michigan, Ann Arbor
ABSTRACT This paper examined the effects of boarding and alighting passengers with mobility aids (wheelchairs, scooters, walkers and canes), or with large items (carts, strollers, bicycles, or carrying an infant) on bus stop dwell time in a fixed-route bus service. Data from the public transit system in Ann Arbor, Michigan were used in a case-control design that matched observations from 180 bus stops with at least one passenger encumbered with a mobility aid or large item boarding or alighting (cases) with 448 bus stops with the same number of passengers boarding and alighting but without any encumbrances (controls). A sequence of linear regression models examined the relationship between dwell time and the addition of variables representing encumbered passengers and ramp use to a set of explanatory variables typically used in dwell time analysis. The addition of the variables of total encumbered passengers and use of ramp increased the variance explanation of a dwell time model based on boarding passengers by fare payment, alighting passengers by door use, and passenger load from 37% to 55%. The findings indicate distinct patterns in the durations for boarding and alighting by passengers with vs. without encumbrances, and when a ramp is not used. This finding suggests that accounting for the presence of encumbered passengers and ramp use in dwell time analyses could help transit operators make their service more efficient and inclusive for all passengers and encourage more use of fixed-route transit among individuals with disabilities.