Dispatching control at transfer stations in multi‐hub transit networks

Among dispatching control approaches, the holding option has attracted the most attention in bus control. However, holding a vehicle at a transfer station may exacerbate the delays because more passengers might accumulate at downstream stations and may also affect other connecting routes at other transfer stations. Our problem is to minimize the total costs of dispatching ready vehicles at each transfer station along coordinated routes in a multi‐hub transit network. The total costs include the waiting cost for on‐board passengers, the missed connection costs for late arrival passengers at the subject transfer station and possible transfer costs at downstream transfer stations. We develop a heuristic algorithm to optimize the holding times based on real time information about late vehicles. The results show that ready vehicles should be held longer when the arrival variances of late vehicles are small or when many late connecting passengers are expected.     

Optimal slack time for timed transfers at a transit terminal

At transit terminals where two routes interchange passengers, total system costs may be reduced by allowing some “slack” time in the vehicle schedules to decrease the probability of missed connections. Transfer cost functions are formulated and used to determine optimal slack time for simple systems with transfers between one bus route and one rail line. Some analytic results are derived for empirical discrete and Gumbel distributions of bus arrival times. Relations between the optimal slack times and headways, transfer volumes, passenger time values, bus operating costs, and standard deviations of bus and train arrivals are also developed numerically using normally distributed arrivals. However, the proposed numerical approach can optimize slack times for any observed arrival distributions. The results provide some guidelines on desirable slack times and show that schedule coordination between the two routes is not worth attempting when standard deviations of arrivals exceed certain levels. Possible extensions of this work are suggested in the last section.     

Joint development at transit stations in the United States

Joint development, as the term is generally used in connection with transit systems in the United States, is real estate development that is closely linked to public transportation services and station facilities, and takes advantage of the market and locational advantages provided by them. Research conducted by LEK Associates for the Urban Mass Transportation Administration (UMTA) suggests that, in addition to helping shape urban growth and land development, joint development is also a surprisingly effective means of increasing transit system ridership and farebox revenues, as well as a source of increasingly significant revenues from the sale or lease of air rights.The completion of nine joint development projects in as many different cities, started under the former Urban Initiatives Program, for example, net additional annual ridership might reach 12000000 one-way trips. Net additional annual farebox revenues might reach over $9000000. This added revenue would be sufficient to repay the $62 million combined UMTA/transit operator investment in the nine projects, exclusive of the costs of the basic transit system improvements around which the projects are planned, in less than six years.Among transit authority-administered joint development programs examined in a separate study, the Washington Metropolitan Area Transit Authority (WMATA) has had the most success in generating significant value capture income. For example, the cumulative revenue realized by WMATA from just six joint development projects in the Washington, DC region, through September 1983 exceeded $ 6.9 million. Projections through fiscal year 1986 indicate cumulative revenues approximating $ 28 million will be received from developer leases.     

Bus arrival time prediction at bus stop with multiple routes

Provision of accurate bus arrival information is vital to passengers for reducing their anxieties and waiting times at bus stop. This paper proposes models to predict bus arrival times at the same bus stop but with different routes. In the proposed models, bus running times of multiple routes are used for predicting the bus arrival time of each of these bus routes. Several methods, which include support vector machine (SVM), artificial neural network (ANN), k nearest neighbours algorithm (k-NN) and linear regression (LR), are adopted for the bus arrival time prediction. Observation surveys are conducted to collect bus running and arrival time data for validation of the proposed models. The results show that the proposed models are more accurate than the models based on the bus running times of single route. Moreover, it is found that the SVM model performs the best among the four proposed models for predicting the bus arrival times at bus stop with multiple routes.     

Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network

This study evaluates an existing bus network from the perspectives of passengers, operators, and overall system efficiency using the output of a previously developed transportation network optimisation model. This model is formulated as a bi-level optimisation problem with a transit assignment model as the lower problem. The upper problem is also formulated as bi-level optimisation problem to minimise costs for both passengers and operators, making it possible to evaluate the effects of reducing operator cost against passenger cost. A case study based on demand data for Hiroshima City confirms that the current bus network is close to the Pareto front, if the total costs to both passengers and operators are adopted as objective functions. However, the sensitivity analysis with regard to the OD pattern fluctuation indicates that passenger and operator costs in the current network are not always close to the Pareto front. Finally, the results suggests that, regardless of OD pattern fluctuation, reducing operator costs will increase passenger cost and increase inequity in service levels among passengers.     

Built environment and pedestrian behavior at rail rapid transit stations in Bangkok

Urbanization and demands for mobility have spurred the development of mass rapid transit infrastructure in industrializing Asia. Differences between the character of pre-existing urban structure in these localities and worldwide precedents suggest a need for studies examining how new rapid transit systems function locally. This study of Bangkok’s elevated and underground rail systems identifies relationships between the built environment and pedestrian behavior surrounding stations. Based on details of 1,520 pedestrian egress trips from three elevated and three underground stations in 2006, multiple regression and analysis of variance (ANOVA) revealed that types of pedestrian destinations, reflecting land uses, were related to length of walking egress trips. Trips to shopping centers and office buildings were longer, while trips to eating places were shorter. The most common type of pedestrian trip recorded was to another vehicle, and trips to automobile taxis and motorcycle taxis figured prominently. Policy implications of the findings are considered.     

Transfer penalties: Another look at transit riders' reluctance to transfer

Two on-board surveys were conducted to determine how transit riders perceive transfers. The surveys were conducted before and after the imposition of a transfer in the middle of an existing bus route. Results of the surveys showed that riders perceive bus transit trips as significantly worse when the trip requires a transfer, even if transfer time is neglibible.     

Evaluating critical lines and stations considering the impact of the consequence using transit assignment model ‐case study of London's underground network

As the problem of full transit vehicles is encountered daily by passengers in most of the big cities, previous research evaluated the consequence of overcrowding in terms of on‐board crowding and passengers not being able to board with full vehicles. The impact of overcrowding in the real world is, however, not necessarily proportional to these numbers. This paper attempts to specify the critical lines and stations of a network by considering the number of passengers failing to board and attempting to evaluate its impact on service quality and safety risks. The hypothesis is that larger stations with wider platforms can often cope better with overcrowding than smaller stations. Therefore a station size dependent satisfaction function is proposed, which takes values from 0 to 1. The method is applied to London's underground network with a number of scenarios which show critical stations in the network if delays occur.