An integrated line planning and timetabling model is formulated with the objective of minimizing both user inconvenience and operational costs. User inconvenience is modeled as the total time ...passengers spend in a railway system, including waiting at origin and transfer stations. The model is solved using a cross-entropy metaheuristic. The line plan and timetable of Israel Railways is used as a benchmark. Using the same amount of resources, the average journey time of passengers is reduced by 20%.
This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). ...The scheduling heuristic, based on linear programming theory, aims at finding minimal user ride time schedules in worst-case quadratic time. The algorithm can either return feasible routes or it can return incorrect infeasibility declarations, on which feasibility can be recovered through a specifically-designed heuristic. The algorithm is furthermore supplemented by a battery management algorithm that can be used to determine charging decisions for electric and autonomous vehicle fleets. Timing solutions from the proposed scheduling algorithm are obtained on millions of routes extracted from DARP and e-ADARP benchmark instances. They are compared to those obtained from a linear program, as well as to popular scheduling procedures from the DARP literature. The proposed procedure mostly yields optimal solutions, with nearly-optimal solutions occurring in only 27 out of 21.5 million cases on DARP instances. Additionally, it demonstrates an average speed improvement of around 60% compared to a linear program and performs comparably to benchmark scheduling approaches from the DARP literature, while outperforming them in solution quality.
•We introduce a highly-efficient scheduling heuristic for dial-a-ride problems.•We present an original battery management heuristic for electric fleets.•We benchmark the developed heuristics against state-of-the-art methodologies.•We conduct a comprehensive analysis, testing our methods on millions of instances.•We show remarkable speed-up and quality, outperforming the state-of-the-art.•We envision future integration in metaheuristic and exact methods.
The electric autonomous dial-a-ride problem Bongiovanni, Claudia; Kaspi, Mor; Geroliminis, Nikolas
Transportation research. Part B: methodological,
04/2019, Volume:
122
Journal Article
Peer reviewed
Open access
•We Introduce the electric Autonomous Dial-A-Ride Problem and formulate it as a 2 index and 3 index MILP.•We integrate battery and vehicle autonomy aspects along with standard DARP features.•We ...devise a Branch-and-Cut algorithm and propose new problem-specific valid inequalities.•The proposed Branch-and-Cut algorithm is tested against benchmark instances from literature and new benchmark instances derived from real data.
In the Dial-a-Ride-Problem (DARP) a fleet of vehicles provides shared-ride services to users specifying their origin, destination, and preferred arrival time. Typically, the problem consists of finding minimum cost routes, satisfying operational constraints such as time-windows, origin-destination precedences, user maximum ride-times, and vehicle maximum route-durations. This paper presents a problem variant for the DARP which considers the use of electric autonomous vehicles (e-ADARP). The problem covers battery management, detours to charging stations, recharge times, and selection of destination depots, along with classic DARP features. The goal of the problem is to minimize a weighted objective function consisting of the total travel time of all vehicles and excess ride-time of the users. We formulate the problem as a 3-index and a 2-index mixed-integer-linear program and devise a branch-and-cut algorithm with new valid inequalities derived from e-ADARP properties. Computational experiments are performed on adapted benchmark instances from DARP literature and on instances based on real data from Uber Technologies Inc. Instances with up to 5 vehicles and 40 requests are solved to optimality.
•Develop a Markovian model to estimate losses due to vehicle and spot shortages.•Introduce a new proactive relocation policy that utilizes reservation information.•Compare with inventory rebalancing ...relocation policies and a centralistic full-knowledge model.•Test the framework in a real field-test in Grenoble with 27 stations and 80 vehicles.
In this paper, we study the operations of a one-way station-based carsharing system implementing a complete journey reservation policy. We consider the percentage of served demand as a primary performance measure and analyze the effect of several dynamic staff-based relocation policies. Specifically, we introduce a new proactive relocation policy based on Markov chain dynamics that utilizes reservation information to better predict the future states of the stations. This policy is compared to a state-of-the art staff-based relocation policy and a centralistic relocation model assuming full knowledge of the demand. Numerical results from a real-world implementation and a simulation analysis demonstrate the positive impact of dynamic relocations and highlight the improvement in performance obtained with the proposed proactive relocation policy.
•Developing a semi-autonomous Multi-Layered Personal Transit System (MuLPeTS) for last-mile service in urban areas.•Addressing the operational problem of MuLPeTS that combines an offline MILP and a ...set of online heuristics.•Designing a simulation that faithfully reproduces the features of the system and testing various management heuristics.•Presenting a numerical experiment on a real-world case study that highlights the system’s various service characteristics.
Semi-autonomous transportation systems are an intermediate step towards full automation of transportation systems. They use and benefit from the technological advances brought by automation while being already implementable at larger scale under the current regulations and within the existing urban environment.
In this paper, we present a new type of semi-autonomous transportation system referred to as Multi-Layered Personal Transit System (MuLPeTS). It consists of convoys composed of one human-driven lead vehicle guiding several autonomous small capacity trailers in which the passengers travel. These trailers can detach from a convoy and travel autonomously in a protected environment before attaching later to another convoy. The interest of this transportation concept is threefold: (i) this assembly of vehicles is able and allowed to move in mixed-traffic conditions whereas fully autonomous driving is still largely restricted; (ii) a trailer can travel autonomously in the vicinity of stations to pick-up and drop-off passengers while the convoy it was previously part of continues its route without further delay; and (iii) passengers complete their entire journey on board a single trailer, that is they avoid the need to transfer. We analyze how this new type of transportation system relates to existing alternatives and propose an operational concept for it, in which we account for passenger assignment, lead vehicle routes and trailer movements, including empty trailer relocation. We extensively test this concept within a purpose-built simulation environment to evaluate the performance of this kind of system based on real-world data instances. The results highlight the most promising operational policies and characterize favorable system configurations.
In bike-sharing systems, at any given moment, a certain share of the bicycle fleet is unusable. This phenomenon may significantly affect the quality of service provided to the users. However, to date ...this matter has not received any attention in the literature. In this article, the users' quality of service is modeled in terms of their satisfaction from the system. We measure user dissatisfaction using a weighted sum of the expected shortages of bicycles and lockers at a single station. The shortages are evaluated as a function of the initial inventory of usable and unusable bicycles at the station. We analyze the convexity of the resulting bivariate function and propose an accurate method for fitting a convex polyhedral function to it. The fitted polyhedral function can later be used in linear optimization models for operational and strategic decision making in bike-sharing systems. Our numerical results demonstrate the significant effect of the presence of unusable bicycles on the level of user dissatisfaction. This emphasizes the need to have accurate real-time information regarding bicycle usability.
In bike-sharing systems, a small percentage of the bicycles become unusable every day. Currently, there is no reliable on-line information that indicates the usability of bicycles. We present a model ...that estimates the probability that a specific bicycle is unusable as well as the number of unusable bicycles in a station, based on available trip transaction data. Further on, we present some information based enhancements of the model and discuss an equivalent model for detecting locker failures.
•We present a Bayesian model for detecting unusable bicycles in bike-sharing systems.•We use available trip data to estimate the number of unusable bicycles in real-time.•We present some information-based enhancements of the model.•An equivalent model for detection of locker failures is also discussed.
•The exertion of parking reservation policies in vehicle sharing systems is studied.•Partial parking reservations are introduced and analyzed.•Mathematical programming based lower bounds on the ...quality of service are devised.•The complete parking reservation policy is shown to be both simple and effective.•Parking overbooking policies are demonstrated not to be worthwhile.
We study the regulation of one-way station-based vehicle sharing systems through parking reservation policies. We measure the performance of these systems in terms of the total excess travel time of all users caused as a result of vehicle or parking space shortages. We devise mathematical programming based bounds on the total excess travel time of vehicle sharing systems under any passive regulation (i.e., policies that do not involve active vehicle relocation) and, in particular, under any parking space reservation policy. These bounds are compared to the performance of several partial parking reservation policies, a parking space overbooking policy and to the complete parking reservation (CPR) and no-reservation (NR) policies introduced in a previous paper. A detailed user behavior model for each policy is presented, and a discrete event simulation is used to evaluate the performance of the system under various settings. The analysis of two case studies of real-world systems shows the following: (1) a significant improvement of what can theoretically be achieved is obtained via the CPR policy; (2) the performances of the proposed partial reservation policies monotonically improve as more reservations are required; and (3) parking space overbooking is not likely to be beneficial. In conclusion, our results reinforce the effectiveness of the CPR policy and suggest that parking space reservations should be used in practice, even if only a small share of users are required to place reservations.
•We examine parking reservation policies in one-way vehicle sharing systems.•The total users excess time is used as the performance measure.•We present a detailed user behavior model.•We show ...analytically that reservations improve performance in most realistic systems.•A discrete event simulation confirms the result for a realistic system.
In this study, we propose improving the performance of one-way vehicle sharing systems by incorporating parking reservation policies. In particular, we study a parking space reservation policy in which, upon rental, the users are required to state their destination and the system then reserves a parking space for them until they arrive at their destinations. We measure the performance of the vehicle sharing system by the total excess time users spend in the system. The excess time is defined as the difference between the actual journey time and the shortest possible travel time from the desired origin to the desired destination. A Markovian model of the system is formulated. Using this model, we prove that under realistic demand rates, this policy improves the performance of the system. This result is confirmed via a simulation study of a large real system, Tel-O-Fun, the bike-sharing system in Tel-Aviv. For all the tested demand scenarios, the parking reservation policy reduces the total excess time users spend in the system, with a relative reduction varying between 14% and 34%. Through the simulation we examine additional service-oriented performance measures and demonstrate that they all improve under the parking reservation policy.
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