Efficient Transit Schedule Design of timing points: A comparison of Ant Colony and Genetic Algorithms

This work defines Transit Schedule Design (TSD) as an optimization problem to construct the transit schedule with the decision variables of the location of timing points and the amount of slack time associated with each timing point. Two heuristic procedures, Ant Colony and Genetic Algorithms, are developed for constructing optimal schedules for a fixed bus route. The paper presents a comparison of the fundamental features of the two algorithms. They are then calibrated based on data generated from micro-simulation of a bus route in Melbourne, Australia, to give rise to (near) optimal schedule designs. The algorithms are compared in terms of their accuracy and efficiency in providing the minimum cost solution. Although both procedures prove the ability to find the optimal solution, the Ant Colony procedure demonstrates a higher efficiency by evaluating less schedule designs to arrive at a ‘good’ solution. Potential benefits of the developed algorithms in bus route planning are also discussed.     

Incorporating equity into the transit frequency-setting problem

This paper and the proposed formulation contribute to an apparent gap in transit research design by integrating equity considerations into the transit frequency-setting problem. The proposed approach provides a means to design transit service such that equitable access to basic amenities (e.g., employment, supermarkets, medical services) is provided for low-income populations or disadvantaged populations. The overarching purpose is to improve access via transit to basic amenities to: (1) reduce the disproportionate burden faced by transit dependent populations; and (2) create a more feasible transportation option for low-income households as an opportunity to increase financial security by reducing dependence on personal autos. The formulation is applied to data from a mid-sized US metropolitan area. The example application illustrates the formulation successfully increases access to employment opportunities for residents in areas with high percentages of low-income persons, as well as demonstrates the importance of considering uncertainty in the locations of populations and employment.     

The Japanese experience with mini‐cars

Despite the early appeal of the light vehicle, increases in the average annual income have allowed consumers to consider a broader range of vehicles so that the negative aspects of mini‐vehicles such as higher noise and vibration levels, the lack of horsepower and instability in certain driving conditions have made light vehicles less tolerable. The “oil shock” shattered economic projections, and people began to acknowledge that living in a world with limited resources was a harsh reality. Concurrently, congestion increased dramatically in urban areas as a result of the popularity of automobiles, and producers made a number of design changes to improve the safety and comfort limitations of light vehicles. Thus, in a world where fuel economy and ease of use gained a greater meaning, light vehicles slowly regained their original appeal.

Light vehicles may play a greater role in the future. Studies indicate that light vehicles tend to be driven by females and elderly people and current trends indicate that the number of female drivers is increasing and that the average age of the Japanese population is getting higher. Furthermore, migration patterns indicate that a greater number of people are moving to smaller cities and their outlying areas as a result of national decentralization policies. The migration pattern may popularize light vehicles because vehicle ownership rates are higher in these areas than in larger cities. Another development which may increase the popularity of light vehicles is that more families are owning more than one car and light vehicles are popular as second vehicles. Moreover, the prospects of low economic growth have tempered the importance of comfortable amenities, and the virtues of maneuverability and fuel economy have become more important.

     

A genetic algorithm-based method for improving quality of travel time prediction intervals

The transportation literature is rich in the application of neural networks for travel time prediction. The uncertainty prevailing in operation of transportation systems, however, highly degrades prediction performance of neural networks. Prediction intervals for neural network outcomes can properly represent the uncertainty associated with the predictions. This paper studies an application of the delta technique for the construction of prediction intervals for bus and freeway travel times. The quality of these intervals strongly depends on the neural network structure and a training hyperparameter. A genetic algorithm–based method is developed that automates the neural network model selection and adjustment of the hyperparameter. Model selection and parameter adjustment is carried out through minimization of a prediction interval-based cost function, which depends on the width and coverage probability of constructed prediction intervals. Experiments conducted using the bus and freeway travel time datasets demonstrate the suitability of the proposed method for improving the quality of constructed prediction intervals in terms of their length and coverage probability.     

The transit network design problem with elastic demand and internalisation of external costs: An application to rail frequency optimisation

In this paper we examine the transit network design problem under the assumption of elastic demand, focusing on the problem of designing the frequencies of a regional metro. In this problem, investments in transit services have appreciable effects on modal split. Neglecting demand elasticity can lead to solutions that may not represent the actual objectives of the design. We propose four different objective functions that can be adopted to assume demand as elastic, considering the costs of all transportation systems (car, bus and rail) as well as the external costs, and we define the constraints of the problem. Heuristic and meta-heuristic solution algorithms are also proposed. The models and algorithms are tested on a small network and on a real-scale network.     

Automatic calibration of agent-based public transit assignment path choice to count data

This work describes the calibration of a schedule-based transit assignment inside an iterative microscopic agent-based simulation. The calibration challenge implies that the behavioral rules should be modified in order to move the simulation closer to observed passenger counts. First, route choice set of agents is enriched with travel parameter utilities randomization. Secondly, the calibration interacts directly into the performance evaluation of individual daily plan of activities, so that the plan is also evaluated for its contribution to the count reproduction. In this way, appropriate plans from the calibration perspective can persist along simulation iterations. The Berlin public transport system with day-based counts is used as test scenario. The results show that the calibration approach can work with large scale scenarios, and that it is able to deal with the inter-temporal aspects implied by counts.     

Design and implementation of efficient transit networks: Procedure, case study and validity test

This paper presents and tests a method to design high-performance transit networks. The method produces conceptual plans for geometric idealizations of a particular city that are later adapted to the real conditions. These conceptual plans are generalizations of the hybrid network concept proposed in Daganzo (2010). The best plan for a specific application is chosen via optimization. The objective function is composed of analytic formulae for a concept’s agency cost and user level of service. These formulae include as parameters key demand-side attributes of the city, assumed to be rectangular, and supply-side attributes of the transit technology. They also include as decision variables the system’s line and stop spacings, the degree to which it focuses passenger trips on the city center, and the service headway. These decision variables are sufficient to define an idealized geometric layout of the system and an operating plan. This layout-operating plan is then used as a design target when developing the real, detailed master plan. Ultimately, the latter is simulated to obtain more accurate cost and level of service estimates.This process has been applied to design a high performance bus (HPB) network for Barcelona (Spain). The idealized solution for Barcelona includes 182 km of one-way infrastructure, uses 250 vehicles and costs 42,489 €/h to build and run. These figures only amount to about one third of the agency resources and cost currently used to provide bus service. A detailed design that resembles this target and conforms to the peculiarities of the city is also presented and simulated. The agency cost and user level of service metrics of the simulated system differ from those of the idealized model by less than 10%. Although the designed and simulated HPB systems provide sub-optimal spatial coverage because Barcelona lacks suitable streets, the level of service is good. Simulations suggest that if the proposed system was implemented side-by-side with the current one, it would capture most of the demand.     

Efficiency measurement in public transport: Are findings specification sensitive?

The need to measure transit system performance along with its various dimensions such as efficiency and effectiveness has led to the development of a wide array of approaches and vast literature. However, depending upon the specific approach used to examine performance, different conclusions are oftentimes reached. Using data from 15 European transit systems for a ten year time period (1990-2000), this paper discusses three important transit performance questions; (i) Do different efficiency assessment methodologies produce similar results? (ii) How are the two basic dimensions of transit performance, namely efficiency and effectiveness, related? and (iii) Are findings regarding organizational regimes (public operations, contracting and so on) sensitive to the methodological specifications employed? Results clearly indicate that efficiency scores and associated recommendations are sensitive to the models used, while efficiency and effectiveness are - albeit weakly - negatively related; these two findings can have far reaching policy implications.     

Using Focus and NomiNal Group Techniques for a Better Understanding of the Transit Disadvantaged Needs

The research presented in this paper explores the context, method, and value of focus group research in transit needs assessments. Group participatory research can generate data that are not easily obtained by other methods. The paper focuses on lessons from three Nebraska communities whose transit disadvantaged rely on community-based paratransit services. Because of the size of the paratransit population and the inability to control who showed up to the focus group sessions, a modified group research protocol was adopted in order to garner information from whomever attended the session. The population parameters and the number of people at the meetings were anticipated by the researchers and mitigated by incorporating nominal group techniques. Research findings from the focus group sessions are discussed paying particular attention to the candid and policy-specific comments made by the focus group participants. The paper concludes with an application of focus group research in transit planning.     

Transit network design for small-medium size cities

This paper proposes a novel heuristic to solve the network design problem for public transport in small-medium size cities. Such cities can be defined as those with a diameter of a few kilometers with up to a few hundred thousand residents. These urban centers present a specific spatial configuration affecting the land use and mobility system. Transportation demand is widespread in origin and concentrated in a small number of attraction points close to each other. This particular structure of demand (‘many-to-few’) suggests the need for specific methodologies for the design of a transit system at a network level. In this paper, such design methodologies are defined in terms of models and solution procedures and tested on a selected case study. The solution methods show promising results. The key variables of the model are the routes and their frequencies. The constraints of the problem affect the overall demand to be served, the quality of the proposed service (transfer, load factors) and the definition of routes.