Luca Quadrifoglio

Comparing Ant Colony Optimization and Genetic Algorithm Approaches for Solving Traffic Signal Coordination under Oversaturation Conditions

This article proposes to solve the oversatu- rated network traffic signal coordination problem us- ing the Ant Colony Optimization (ACO) algorithm. The traffic networks used are discrete time models which use green times at all the intersections throughout the consid- ered period of oversaturation as the decision variables. The ACO algorithm finds intelligent timing plans which take care of dissipation of queues and removal of block- ages as opposed tothe solecost minimization usually per- formed for undersaturation conditions. Two scenarios are considered and results are rigorously compared with solutions obtained using the genetic algorithm (GA), tra- ditionally employed to solve oversaturated conditions. ACO is shown to be consistently more effective for a larger number of trials and to provide more reliable so- lutions. Further, as a master-slave parallelism is possible for the nature of ACO algorithm, its implementation is suggested to reduce the overall execution time allowing the opportunity to solve real-time signal control systems. only a short time, the time to clear the network may be significant. Costs of infrastructure renewal and expan- sion may be cost prohibitive, and, under limited bud- gets, strategies are needed that enhance the mobility

An insertion heuristic for scheduling Mobility Allowance Shuttle Transit (MAST) services

In this paper, we develop an insertion heuristic for scheduling Mobility Allowance Shuttle Transit (MAST) services, an innovative concept that merges the flexibility of Demand Responsive Transit (DRT) systems with the low cost operability of fixed-route systems. A MAST system allows vehicles to deviate from the fixed path so that customers within a service area may be picked up or dropped off at their desired locations. Such a service already exists in Los Angeles County, where MTA Line 646 is a MAST nighttime service, transporting passengers between a business area and a nearby bus terminal. Since the current demand is very low, the service is entirely manageable by the bus operator, but a higher demand would certainly require the development of a scheduling algorithm. The proposed insertion heuristic makes use of control parameters, which properly regulate the consumption of the slack time. A set of simulations performed in the service area covered by the existing MTA Line 646 at different demand levels attests the effectiveness of the algorithm by comparing its performance versus a first-come/first-serve (FCFS) policy and optimal solutions generated by a commercial integer program solver. The results show that our approach can be used as an effective method to automate scheduling of this line and other services similar to it.

A multimodal location and routing model for hazardous materials transportation

The recent US Commodity Flow Survey data suggest that transporting hazardous materials (HAZMAT) often involves multiple modes, especially for long-distance transportation. However, not much research has been conducted on HAZMAT location and routing on a multimodal transportation network. Most existing HAZMAT location and routing studies focus exclusively on single mode (either highways or railways). Motivated by the lack of research on multimodal HAZMAT location and routing and the fact that there is an increasing demand for it, this research proposes a multimodal HAZMAT model that simultaneously optimizes the locations of transfer yards and transportation routes. The developed model is applied to two case studies of different network sizes to demonstrate its applicability. The results are analyzed and suggestions for future research are provided.

Performance and Design of Mobility Allowance Shuttle Transit Services: Bounds on the Maximum Longitudinal Velocity

We develop bounds on the maximum longitudinal velocity to evaluate the performance and help the design of mobility allowance shuttle transit (MAST) services. MAST is a new concept in transportation that merges the flexibility of demand responsive transit (DRT) systems with the low-cost operability of fixed-route bus systems. A MAST system allows buses to deviate from the fixed path so that customers within the service area may be picked up or dropped off at their desired locations. However, the main purpose of these services should still be to transport customers along a primary direction. The velocity along this direction should remain above a minimum threshold value to maintain the service attractive to customers. We use continuous approximations to compute lower and upper bounds. The resulting narrow gap between them under realistic operating conditions allows us to evaluate the service in terms of velocity and capacity versus demand. The results show that a two-vehicle system, with selected widths of the service area of 0.5 miles and 1 mile, is able to serve, respectively, a demand of at least 10 and 7 customers per longitudinal mile of the service area while maintaining a reasonable forward progression velocity of about 10 miles/hour. The relationships obtained can be helpful in the design of MAST systems to set the main parameters of the service, such as slack time and headway.

Mobility allowance shuttle transit (MAST) services: MIP formulation and strengthening with logic constraints

Abstract We study a hybrid transportation system referred to as mobility allowance shuttle transit (MAST) where vehicles may deviate from a fixed path consisting of a few mandatory checkpoints to serve demand distributed within a proper service area. In this paper we propose a mixed integer programming (MIP) formulation for the static scheduling problem of a MAST type system. Since the problem is NP-Hard, we develop sets of logic cuts, by using reasonable assumptions on passengers’ behavior. The purpose of these constraints is to speed up the search for optimality by removing inefficient solutions from the original feasible region. Experiments show the effectiveness of the developed inequalities, achieving a reduction up to 90% of the CPU solving time for some of the instances.

Optimal Zone Design for Feeder Transit Services

Feeder transit services generally operate within residential service areas and move customers to and from a transfer point that connects to a major fixed-route transit network. Feeders can operate in a traditional fixed-route or in an emerging demand-responsive fashion. In designing such systems, planners may divide the entire service area into zones independently served by a single feeder line to provide better customer service, lower operating cost, and make management of the operations easier. An analytical model is developed to help decision makers determine the number of zones in a residential service area while balancing customer service quality and vehicle operating costs. For fixed-route and demand-responsive feeder transit, closed-form expressions and numerical procedures are used to derive the optimal number of zones as a function of the main parameters. Analytical expressions are validated by simulation runs.

A methodology for comparing distances traveled by performance-equivalent fixed-route and demand responsive transit services

Abstract Public transport systems are confronted by the need to improve their economic effectiveness in order to meet customer requirements at acceptable costs for transit providers, which are often heavily subsidized. Our goal is to understand how the organizational form of the transit system impacts on system productivity. Our methodology consists of comparing performance in terms of distance traveled of two competing transit services, a traditional fixed-route and a demand responsive service, while ensuring a comparable service to the same set of customers. We consider several scenarios, which depend on the road network, service quality level, and demand density. According to our findings, demand responsive transit services perform better for high-quality service levels and low demand density scenarios.

Sensitivity Analyses over the Service Area for Mobility Allowance Shuttle Transit (MAST) Services

A Mobility Allowance Shuttle Transit (MAST) system is an innovative concept that merges the flexibility of Demand Responsive Transit (DRT) systems with the low cost operability of fixed-route bus systems. It allows vehicles to deviate from the fixed path so that customers within the service area may be picked up or dropped off at their desired locations. In this paper, we summarize the insertion heuristic presented by Quadrifoglio et al. (2007) for routing and scheduling MAST services, and we carry out a set of simulations to show a sensitivity analysis of the performance of the algorithm and the capacity of the system over different shapes of the service area. The results show that a slim service area performs better in general, but also that the positive effects of a proper setting of the control parameters of the heuristic is much more evident for wider service areas. In addition, a performance comparison shows that MAST systems can provide a better service to customers than fixed-route ones even for a slim service area.

Evaluation of Zoning Design with Transfers for Paratransit Services

This paper evaluates the effects of including transfers between service zones on overall service performance in a paratransit system. Transfers were included to improve the operational efficiency of a system when maintenance of a desirable zoning structure was obligatory. This proposed innovative service design was compared with more traditional cases of no transfer zoning and no zoning. A set of instances was generated from demand data obtained from the Metropolitan Transit Authority of Harris County, Texas, and evaluated through simulation analyses. The results demonstrated that under a zoning structure, this transfer design (in comparison with a nontransfer design) provided noticeable improvements in efficiency measures and better passenger trips per vehicle revenue hour while maintaining a minimum customer service standard; however, the overall performance of the no-zoning strategy used by the Houston, Texas, Metropolitan Transit Authority of Harris County performed the best, on average.

2-Vehicle zone optimal design for feeder transit services

Feeder transit services perform the crucial first/last mile access to transit by connecting people within a residential area to a major transit network. In this paper, we address the optimal zone design problem faced by planners for feeder transit services with high demands and long length of service area, where a two-vehicle operation is assumed to be adopted in each zone. By balancing customer service quality and operating cost, we develop an analytical model of the system by assuming continuous approximations. Closed-form expressions and numerical procedures are employed to derive the optimal number of zones to aid decision makers in determining the best design as a function of the main parameters. Analytical expressions and results are then validated by simulation analysis.