Introducing change to transportation and energy systems: the case of alcohol fuels

This paper describes the application of optimization techniques to the problems of garage location and bus routing. The technique employed involves the decomposition of a garage location and bus routing model into two submodels. Solutions for the garage location and bus routing submodels are combined iteratively to find an optimal solution for the overall optimization model. Significant cost savings realizable for the Transit Authority of River City (Louisville, Kentucky) were calculated by implementing the results.     

Location of bus garages

The location of bus garages is a complex issue that has received recent attention in the literature. Given a bus system, the number of bus garages and their locations depend on garage cost, deadheading cost and environmental impacts. An approximate analytical model is used to determine the number of bus garages that minimizes the above costs. The concept of a slowly varying density of bus-route origins (hence deadheads) per unit area is used to model deadheading costs. The increased deadheading caused by breakdowns and accidents is also considered. The garage cost is modeled as a function of the number of buses stored. A closed-form solution is obtained for the optimal density of garages, when the garage cost function is linear. The actual locations of garages and the allocations of buses to the garages are found using a discrete space location-allocation model formulated so as to consider the environmental impact associated with buses deadheading through populated neighborhoods.     

Optimization Of Headway,Vehicle Size and Route Choice for Minimum Cost Feeder Service

ABSTRACT

Many people use public transportation systems to reach their destination, while others use personal vehicles. Poor transportation systems do not attract ridership. Therefore, the usage of passenger cars increases, and traffic and environmental conditions deteriorate. Efficient public transportation has been recognized as one of the potential ways of mitigating air pollution, reducing energy consumption, improving mobility and alleviating traffic congestion. The objective of this study is to optimize a bus feeder service that provides the shuttle service between a recreation center (e.g. Sandy Hook, NJ) and a major public transportation facility, subject to site-specific constraints such as vehicle schedules, bus availability, service capacity and budget. The decision variables include bus headway, vehicle size and route choice. The solution methodology integrating both analytical and numerical techniques is developed, which optimizes the decision variables. Finally, the proposed solution methodology is applied to a case study. Numerical results, including optimal solutions and sensitivity analyses, are presented while the level of coordination between the feeder service and a major transportation service is discussed.     

Contribution to the design of the Athletes Bus Network during the Athens 2004 Olympic Games

This paper describes important aspects of the design of the Athletes transportation system for the Athens 2004 Olympic Games. The unique characteristics of this network include the close dependence of the vehicle schedules on the competition and training program, the requirement for 100% service reliability, as well as the requirement for full system monitoring and control. In this paper we present methods for the development of service specifications, estimation of the bus fleet size, the design of the network’s organization and management system, and corresponding critical implementation issues. All these issues are relevant to the design and management of bus transport systems for large events.     

Scheduling lane conversions for bus use on city-wide scales and in time-varying congested traffic

The paper explores what can occur when select street lanes throughout a city are periodically reserved for buses. Simulations of an idealized city were performed to that end. The city’s time-varying travel demand was studied parametrically. In all cases, queues formed throughout the city during a rush, and dissipated during the off-peak period that followed. Bus lanes were activated all at once across the city, and were eventually deactivated in like fashion. Activation and deactivation schedules varied parametrically as well. Schedules that roughly balanced the trip-time savings to bus riders against the added delays to car travelers were thus identified.Findings reveal why activating conversions near the start of a rush can degrade travel, both by car and by bus. Balance was struck by instead activating lane conversions nearer the end of the rush, when vehicle accumulation in the city was at or near its maximum. Most of the time savings to bus riders accrued after the conversions had been left in place for only 30 min. Leaving them for longer durations often brought modest additional savings to bus travelers. Yet, the added delays to cars often grew large as a result.These findings held even when buses garnered high ridership shares. This was the case when lane conversions gradually induced new bus trips among residents who formerly did not travel. It was also true when high ridership was a pre-existing feature of the city. Activating conversions a bit earlier in a rush was found to make sense only if commuters shifted from cars to buses in very large numbers. Findings also unveiled how to fine-tune activation and deactivation schedules to suit a city’s congestion level. Guidelines for scheduling conversions in real settings are furnished. So is discussion on how these schedules might be adapted to daily variations in city-wide traffic states. Roles for technology are discussed as well.     

Heuristic approaches for solving large-scale bus transit vehicle scheduling problem with route time constraints

This paper presents new models for multiple depot vehicle scheduling problem (MDVS) and multiple depot vehicle scheduling problem with route time constraints (MDVSRTC). The route time constraints are added to the MDVS problem to account for the real world operational restrictions such as fuel consumption. Compared to existing formulations, this formulation decreases the size of the problem by about 40% without eliminating any feasible solution. It also presents an exact and two heuristic solution procedures for solving the MDVSRTC problem. Although these methods can be used to solve medium size problems in reasonable time, real world applications in large cities require that the MDVSRTC problem size be reduced. Two techniques are proposed to decrease the size of the real world problems. For real-world application, the problem of bus transit vehicle scheduling at the mass transit administration (MTA) in Baltimore is studied. The final results of model implementation are compared to the MTA's schedules in January 1998. The comparison indicates that, the proposed model improves upon the MTA schedules in all respects. The improvements are 7.9% in the number of vehicles, 4.66% in the operational time and 5.77% in the total cost.     

Bus dispatching at timed transfer transit stations using bus tracking technology

A timed transfer terminal synchronizes the arrival of incoming vehicles with the departure of outgoing vehicles so as to minimize transfer delays. Most bus timed transfer terminals follow fixed schedules, and do not utilize intelligent transportation systems for vehicle tracking and control. This paper reviews technologies that enable real-time control of timed transfer. We evaluate the benefits of tracking bus locations and executing dynamic schedule control through the simulation of a generic timed transfer terminal under a range of conditions. Based on empirical data collected by the Los Angeles County/Metropolitan Transit Agency, we found delay over segments of long-headway bus lines to be negatively correlated with lateness at the start of the segment, indicating that buses have a tendency to catch up when they fall behind schedule. The simulation analysis showed that the benefit of bus tracking is most significant when one of the buses experiences a major delay, especially when there is a small number of connecting buses.     

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.     

Vehicle scheduling under stochastic trip times: An approximate dynamic programming approach

Due to unexpected demand surge and supply disruptions, road traffic conditions could exhibit substantial uncertainty, which often makes bus travelers encounter start delays of service trips and substantially degrades the performance of an urban transit system. Meanwhile, rapid advances of information and communication technologies have presented tremendous opportunities for intelligently scheduling a bus fleet. With the full consideration of delay propagation effects, this paper is devoted to formulating the stochastic dynamic vehicle scheduling problem, which dynamically schedules an urban bus fleet to tackle the trip time stochasticity, reduce the delay and minimize the total costs of a transit system. To address the challenge of “curse of dimensionality”, we adopt an approximate dynamic programming approach (ADP) where the value function is approximated through a three-layer feed-forward neural network so that we are capable of stepping forward to make decisions and solving the Bellman’s equation through sequentially solving multiple mixed integer linear programs. Numerical examples based on the realistic operations dataset of bus lines in Beijing have demonstrated that the proposed neural-network-based ADP approach not only exhibits a good learning behavior but also significantly outperforms both myopic and static polices, especially when trip time stochasticity is high.     

Intermodal Transit System Coordination

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.     

A column generation algorithm for the bus driver scheduling problem

Bus driver scheduling aims to find the minimum number of bus drivers to cover a published timetable of a bus company. When scheduling bus drivers, contractual working rules must be enforced, thus complicating the problem. In this research, we develop a column generation algorithm that decomposes this complicated problem into a master problem and a series of pricing subproblems. The master problem selects optimal duties from a set of known feasible duties, and the pricing subproblem augments the feasible duty set to improve the solution obtained in the master problem. The proposed algorithm is empirically applied to the realistic problems of several bus companies. The numerical results show that the proposed column generation algorithm can solve real‐world problems and obtain bus driver schedules that are better than those developed and used by the bus companies. Copyright © 2016 John Wiley & Sons, Ltd.     

上海市城市机动车停车场(库)环保设计优化研究

对上海市7家建筑、环评设计院的15位工程师开展问卷调研,运用Cronbach’sα系数量化了问卷的信度,并根据调研结果,随机实测4座停车场16辆车的洗车污水,进行对标分析与Kruskal-Walli test,最终对城市机动车停车场(库)提出了设计优化建议。结果表明:问卷的Cronbach’sα系数为0.639,信度较好。未经过处理的停车场洗车污水样本存在超标现象,COD的超标区间为[4.23%,108.32%],TP的超标率为10.00%,BOD₅的超标区间为[22.40%,139.40%]。COD、BOD₅、SS的检测结果受车型大小的影响,呈正相关关系。建议从洗车设施、绿荫绿化等方面优化城市停车场(库)的环保设计。     

Evaluate bus emissions generated near far-side and near-side stops and potential reductions by ITS: An empirical study

In this paper, we use second-by-second automatic vehicle location data to estimate bus emissions near far-side and near-side stops. We classify the bus running state near a stop into approach, dwell, and departure. A vehicle specific power approach is used to estimate bus emissions for each state. We show that bus emissions generated near stops can be significantly reduced by using certain intelligent transportation systems techniques.     

Modular route bus design – A method of meeting transport operation and vehicle manufacturing requirements

This research examines the problem of route bus specification and vehicle manufacturability. In order for bus operators to provide transport services, a range of vehicle configurations must be available from bus manufacturers, generating variety which has a negative impact on the manufacturing process. Larger part inventories, uncontrolled labour tasks and more troublesome maintenance are known impacts of this variety. This research identifies the functional necessities in route bus interior design and reduces the problems in bus manufacture and operation caused by specification diversity by proposing a modularised system of bus design. In particular, it makes recommendations as to how bus configuration should be carried out, ensuring an optimum mix of operational and manufacturing needs:

• 1.Determine user needs before the bus specification process.
• 2.Designs to be developed by the manufacturer in response to user needs.
• 3.This design should be standardised where possible, as suggested by the user needs.
• 4.Where user needs dictate product variations, apply a mass customisation approach to accommodate these needs.

The recommendations are communicated in design proposals for a modular bus interior, demonstrated by four cases designed to meet the present status quo of bus interior design and predictions for the future of the field.     

The use of space availability information in “PARC” systems to reduce search times in parking facilities

Two different ways to manage availability information in parking facilities were evaluated in this article. First, in level 4 PARC systems (Parking Access and Revenue Control), when occupancy percentages for all garage levels are above 90% and 95%, the information on variable message sign (VMS) panel will indicate that there are no free spaces – censoring information. In this article, zoning is understood as the second information management tool; it consists of placing vehicle detection systems at intermediary points around the facility in such a way as to separate it into internal zones. It is a variation applicable to facilities with level 2 PARC systems, such as those in shopping centres, where a modification of the vehicle counting algorithm in the main program of the PARC system allows the determination of the number of free spaces in specific zones within the parking facility. According to the simulations that were carried out after testing an existing choice model, level 4 PARC systems are sufficiently effective in small facilities; the option of preparing “false” information when 5 or 10 free spaces are left on a garage level in order to influence user decisions has few practical repercussions. However, the separation into internal zones proposed for level 2 PARC systems shows a 16.2% reduction in search time.     

Optimizing coordinated transfer with probabilistic vehicle arrivals and passengers' walking time

Supporting efficient connections by synchronizing vehicle arrival time and passengers' walking time at a transfer hub may significantly improve service quality, stimulate demand, and increase productivity. However, vehicle travel times and walking times in urban settings often varies spatially and temporally due to a variety of factors. Nevertheless, the reservation of slack time and/or the justification of vehicle arrival time at the hub may substantially increase the success of transfer coordination. To this end, this paper develops a model that considers probabilistic vehicle arrivals and passengers walking speeds so that the slack time and the scheduled bus arrival time can be optimized by minimizing the total system cost. A case study is conducted in which the developed model is applied to optimize the coordination of multiple bus routes connecting at a transfer station in Xi'an, China. The relationship between decision variables and model parameters, including the mean and the standard deviation of walking time, is explored. It was found that the joint impact of probabilistic vehicle arrivals and passengers' walking time significantly affects the efficiency of coordinated transfer. The established methodology can essentially be applied to any distribution of bus arrival and passenger walking time. Copyright © 2017 John Wiley & Sons, Ltd.     

Joint optimization of a rail transit line and its feeder bus system

A model is developed for jointly optimizing the characteristics of a rail transit route and its associated feeder bus routes in an urban corridor. The corridor demand characteristics are specified with irregular discrete distributions which can realistically represent geographic variations. The total cost (supplier plus user cost) of the integrated bus and rail network is minimized with an efficient iterative method that successively substitutes variable values obtained through classical analytic optimization. The optimized variables include rail line length, rail station spacings, bus headways, bus stop spacings, and bus route spacing. Computer programs are designed for optimization and sensitivity analysis. The sensitivity of the transit service characteristics to various travel time and cost parameters is discussed. Numerical examples are presented for integrated transit systems in which the rail and bus schedules may be coordinated.     

Vehicle scheduling for on-demand vehicle fleets in macroscopic travel demand models

Transportation - The planning of on-demand services requires the formation of vehicle schedules consisting of service trips and empty trips. This paper presents an algorithm for building vehicle...     

A new offline optimization approach for designing a fuel cell hybrid bus

In this study a hydrogen powered fuel cell hybrid bus is optimized in terms of the powertrain components and in terms of the energy management strategy. Firstly the vehicle is optimized aiming to minimize the cost of its powertrain components, in an official driving cycle. The optimization variables in powertrain component design are different models and sizes of fuel cells, of electric motors and controllers, and batteries. After the component design, an energy management strategy (EMS) optimization is performed in the official driving cycle and in two real measured driving cycles, aiming to minimize the fuel consumption. The EMS optimization is based on the control of the battery’s state-of-charge. The real driving cycles are representative of bus driving in urban routes within Lisbon and Oporto Portuguese cities. A real-coded genetic algorithm is developed to perform the optimization, and linked with the vehicle simulation software ADVISOR. The trade-off between cost increase and fuel consumption reduction is discussed in the lifetime of the designed bus and compared to a conventional diesel bus. Although the cost of the optimized hybrid powertrain (62,230 €) achieves 9 times the cost of a conventional diesel bus, the improved efficiency of such powertrain achieved 36% and 34% of lower energy consumption for the real driving cycles, OportoDC and LisbonDC, which can originate savings of around 0.43 €/km and 0.37 €/km respectively. The optimization methodology presented in this work, aside being an offline method, demonstrated great improvements in performance and energy consumption in real driving cycles, and can be a great advantage in the design of a hybrid vehicle.     

Disruption management in public transit: the bee colony optimization approach

Disruptions in carrying out planned bus schedules occur daily in many public transit companies. Disturbances are often so large that it is necessary to perform re-planning of planned bus and crew activities. Dispatchers in charge of traffic operations must frequently find an answer to the following question in a very short period of time: How should available buses be distributed among bus routes in order to minimize total passengers' waiting time on the network? We propose a model for assigning buses to scheduled routes when there is a shortage of buses. The proposed model is based on the bee colony optimization (BCO) technique. It is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. It has been shown that this developed BCO approach can generate high-quality solutions within negligible processing times.