On-demand systems in which passengers with similar routes can share a vehicle are expected to become a relevant part of future mobility, thanks to their flexibility and their potential impact on reducing congestion. Nevertheless, due to the long detours required by a door-to-door scheme, they induce extra costs to the users in terms of delay. In this paper, we face the design of such a system in which users might be requested online to walk towards/from nearby pick-up/drop-off points if this improves overall efficiency. We show theoretically that the general problem becomes more complex (as it contains two sub-problems that extend set-cover), analyze the trade-offs that emerge, and provide a general formulation and specific heuristics that are able to solve it over large instances. We test this formulation over a real dataset of Manhattan taxi trips (9970 requests during one hour), finding that (a) average walks of about one minute can reduce the number of rejections in more than 80% and Vehicles-Hour-Traveled in more than 10%, (b) users who depart or arrive at the most demanded areas are more likely to be required to walk, and (c) the performance improvement of the service is larger when the system receives more trip requests.

On-demand ridesharing with optimized pick-up and drop-off walking locations

With the advent of modular autonomous vehicles (MAVs), this paper presents a novel operational design for flex-route transit services to reduce operation costs of vehicles and improve the service quality of customers. The regime allows the simultaneous dispatch of a certain amount of MAVs from a bus terminal at a departure time. Each MAV is allowed to visit customers freely outside of checkpoints. Self-adaptive capacity and flexible service mode adapt time- and space-dependent demand characteristics. The presented operational design is formulated as a mixed-integer linear program that is NP-hard. A two-stage solution framework is developed to decompose the proposed mathematical programming cautiously. In the first stage, customized dynamic programming with valid cuts is designed to solve a bus scheduling problem efficiently. In the second stage, an effective and fast heuristic is proposed to solve a variant of the dial-a-ride problem and satisfy the technical requirements for developing on-line applications. Numerical examples and a case study show the effectiveness of the proposed design by comparing the flex-route transit services using traditional vehicles.

Improving flex-route transit services with modular autonomous vehicles

When demand for transportation is low or highly variable, traditional public bus services tend to lose their efficiency and typically frustrate (potential) passengers. In the literature, a large number of demand-responsive systems, that promise improved flexibility, have therefore been developed. At present, however, a comprehensive survey of these systems is lacking. In this paper, we fill this gap by presenting a unifying framework that classifies all demand-responsive public bus systems. The classification is mainly based on three degrees of responsiveness: dynamic online, dynamic offline, and static. For each system we discuss the specific optimization problem modeled, whether realistic data is considered, and the size of the instances used for testing. Where possible, we try to draw conclusions on the current state of the literature and try to identify potential avenues for future research. Different tables are included to structure and summarize the information of all papers. 

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A survey on demand-responsive public bus systems

Customized bus (CB) is an increasingly popular mode of transportation in many cities around the world. However, studies on CB network design have mostly overlooked three options that may further improve system performance: passenger-route assignment, passenger transfer, and modular vehicles. To bridge this gap, this paper proposes to design a transfer-based CB network with a modular fleet while simultaneously optimizing the passenger-route assignment. To solve the optimal network structure with this new design paradigm, we formulate the network design problem into a nonlinear mixed integer optimization model. A linearization approach and a particle swarm optimization (PSO) algorithm are proposed to solve the exact and near-optimal solution(s) to the model, respectively. Numerical experiments are conducted on the Sioux Falls network and a large-scale network in Chengdu, China. Results show that the customized PSO algorithm efficiently provides high quality near-optimal solutions compared with CPLEX, the genetic algorithm, and the simulated annealing algorithm. Results also show that incorporating passenger-route assignment optimization and the transfer operation produces a more cost-effective CB operational network with less operational costs and higher service quality. The benefit increases as the passenger demand grows.

Transfer-based customized modular bus system design with passenger-route assignment optimization

Cross-border transport infrastructure (CTI) has been regarded as critical for boosting and supporting the coordinated development of regions. However, so far, very limited studies have examined the interconnection performance of CTI with particular emphasis on the overall dynamics of the complicated CTI system and how the dynamic interactions of management measures would affect the system performance as a whole. Therefore, this paper takes on a dynamic and holistic view to investigate how the overall interconnection performance of CTI is affected by the dynamic interactions of management measures. First, four broad indicators for measuring CTI interconnection performance, transportation time reliability, transportation easy accessibility, transportation safety, and transportation operating service quality were identified and analyzed. Second, the causal interactions among main variables were analyzed through causal-loop diagrams. Third, a system dynamics (SD) approach was employed to develop a model for quantifying the effects of variables. Finally, the model was verified and applied with data of the Hong Kong–Zhuhai–Macao Bridge; policy analysis was conducted as well. The findings prove that the dynamic interactions among various management measures are critical in evaluating the interconnection performance of CTI. In particular, impacts of certain combination sets of policies would be larger when management measures are collectively considered. The proposed model can be used as a basis for simulating various management measures, so that the optimum policy combinations can be explored in advance to improve the interconnection performance of CTI. 

System Dynamics Approach for Evaluating the Interconnection Performance of Cross-Border Transport Infrastructure

Modular vehicle (MV) technology offers the possibility of flexibly adjusting the vehicle capacity by docking/undocking modular pods into vehicles of different sizes en route to satisfy passenger demand Based on the MV technology, a modular transit network system (MTNS) concept is proposed to overcome the mismatch between fixed vehicle capacity and spatially varying travel demand in traditional public transportation systems To achieve the optimal MTNS design, a mixed-integer nonlinear programming model is developed to balance the tradeoff between the vehicle operation cost and the passenger trip time cost The nonlinear model is reformulated into a computationally tractable linear model The linear model solves the lower and upper bounds of the original nonlinear model to produce a near-optimal solution to the MTNS design This reformulated linear model can be solved with off-the-shelf commercial solvers (eg, Gurobi) Two numerical examples are used to demonstrate the applicability of the proposed model and its effectiveness in reducing system costs

Vehicle dispatching in modular transit networks: A mixed-integer nonlinear programming model

The longest cross-sea bridge worldwide, i.e., the Hong Kong-Zhuhai-Macao Bridge (HZMB), opened in October 2018, integrating nine cities and two special administrative regions of China’s Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The GBA is one of the regions with the most active economic vitality in China and has an important strategic position in the overall national development. Using full-sample freeway toll data of the GBA, this paper proposed a new structured evaluation methodology that combines the node degree, traffic volume, and topological and flow field-theory (e.g., agglomeration and distribution) to explore the hub city ranking and evolution in this area. The data period we selected to analyze is immediately before and after the opening of the HZMB, and we assess the counties’ centrality changes in the GBA by analyzing these data. The findings reported in this paper can reflect the traffic hub evaluation process and provide more macroscopic intercity transportation views to the government.

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Data-Driven Analysis of Traffic Volume and Hub City Evolution of Cities in the Guangdong-Hong Kong-Macao Greater Bay Area

Internet-based transit services have the potential to enable fully connected, safe, reliable, efficient, and flexible service in the public transit system. The flexible transit system (FTS) allows passengers to make individual travel requests and receive customized door-to-door service by specifying their origins and destinations (OD), departure time range, and willingness to pay (WTP). Unlike the uniform and stable WTP in our previous paper, we consider an exponential decay function for the real pickup locations of passengers, and we proposed a joint design of two-level bus stops in temporal and spatial variations of travel demands. To ensure practical applications of this real-time FTS model, we combine the traversing method and the improved tabu search algorithm. A numerical example from Guangzhou is conducted to demonstrate the applicability of the proposed model and its effectiveness in reducing system cost.

/pdf/operational-design-for-a-real-time-flexible-transit-system-1uh55wqidl.pdf

Peiqun Lin

Papers

Vehicle dispatching in modular transit networks: A mixed-integer nonlinear programming model

Data-Driven Analysis of Traffic Volume and Hub City Evolution of Cities in the Guangdong-Hong Kong-Macao Greater Bay Area

Operational Design for a Real-Time Flexible Transit System Considering Passenger Demand and Willingness to Pay