The importance of computing intermodal roundtrips in multimodal guidance systems

Most of the current intermodal traveller information applications still consider one-way journeys only. For the calculation of a roundtrip two simple one-way trips are taken into account. However, most of the journeys do not consist of simple one-way trips, as a traveller usually returns to the starting point (home, office for business trips, etc.). Also, arc cost – travel time in general – tend to be time dependent, which means that the cost of the optimum roundtrip is not necessarily the double of the cost of the optimum one-way trip. The diverse arc cost values can be based on dynamic and/or historic data. A lot of effort is spent in order to obtain and store this type of data, which is necessary for describing real-time traffic states and to make forecasts. So the next step is to make better use of this data by integrating them into the calculation of trips that take place in the future. A multimodal information service usually works as follows: The traveller indicates his starting point, his destination and the desired time of departure or arrival. The system then computes the optimum trips for private modes (car, bicycle, etc.) and public transport (all modes). It is up to the user to compare the different possibilities and to decide which one to take. Dynamic data are integrated where available. The possibility of switching between different transportation modes during the trip is rarely offered. The main reasons are the difference in the models (different graphic levels are used for different modes) and the different parameters for describing the arc cost for the different modes. Roundtrips can usually be computed for certain modes, especially for public transport, which relies on static timetable data. In this case, the intermodality is limited to some or several public transport modes of a certain region. More and more service providers offer the possibility to optimise a door-to-door trip, taking into account the time necessary to reach the first transport mode used, as well as the time to reach the destination from the last stop. This paper describes the importance of computing entire intermodal roundtrips rather than two one-way trips, as arc cost tend to vary depending on different parameters (time of the day, special events, etc.). Having more and more dynamic and historic data at hand, it should be used to the maximum possible, in order to optimise mobility habits. Computing intermodal roundtrips also means taking into account several constraints that may arise on the way, like the dependence on a certain mode or leaving behind a private vehicle at certain nodes of the network. The main constraints are pointed out, along with their importance for the calculation

Service network design for an intermodal container network with flexible due dates/times and the possibility of using subcontracted transport

An intermodal container transportation network is being developed between Rotterdam and several inland terminals in North West Europe: the EUROPEAN GATEWAY SERVICES (EGS) network. This network is developed and operated by the seaports of EUROPE CONTAINER TERMINALS (ECT). To use this network cost-efficiently, a centralized planning of the container transportation is required, to be operated by the seaport. In this paper, a new mathematical model is proposed for the service network design. The model uses a combination of a path-based formulation and a minimum flow network formulation. It introduces two new features to the intermodal network-planning problem. Firstly, overdue deliveries are penalized instead of prohibited. Secondly, the model combines self-operated and subcontracted services. The service network design considers the network-planning problem at a tactical level: the optimal service schedule between the given network terminals is determined. The model considers self-operated or subcontracted barge and rail services as well as transport by truck. The model is used for the service network design of the EGS network. For this case, the benefit of using container transportation with multiple legs and intermediate transfers is studied. Also, a preliminary test of the influence of the new aspects of the model is done. The preliminary results indicate that the proposed model is suitable for the service network design in modern intermodal container transport networks. Also, the results suggest that a combined business model for the network transport and terminals is worth investigating further, as the transit costs can be reduced with lower transfer costs

Intermodal Path Algorithm for Time-Dependent Auto Network and Scheduled Transit Service

A simple but efficient algorithm is proposed for finding the optimal path in an intermodal urban transportation network. The network is a general transportation network with multiple modes (auto, bus, rail, walk, etc.) divided into the two major categories of private and public, with proper transfer constraints. The goal was to find the optimal path according to the generalized cost, including private-side travel cost, public-side travel cost, and transfer cost. A detailed network model of transfers between modes was used to improve the accounting of travel times during these transfers. The intermodal path algorithm was a sequential application of specific cases of transit and auto shortest paths and resulted in the optimal intermodal path, with the optimal park-and-ride location for transferring from private to public modes. The computational complexity of the algorithm was shown to be a significant improvement over existing algorithms. The algorithm was applied to a real network within a dynamic traffic and transit assignment procedure and integrated with a sequential activity choice model

Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem

Impact and relevance of transit disturbances on planning in intermodal container networks

__Abstract__ An intermodal container transportation network is being developed between Rotterdam and several inland terminals in North West Europe: the European Gateway Services network. This network is developed and operated by the sea terminals of Europe Container Terminals (ECT). To use this network cost-efficiently, centralised planning by the sea terminal of the container transportation is required. For adequate planning it is important to adapt to occurring disturbances. In this paper, a new mathematical model is proposed: the Linear Container Allocation model with Time-restrictions (LCAT). This model is used for determining the influence of three main types of transit disturbances on the network performance: early departure, late departure, and cancellation of inland services. The influence of a disturbance is measured in two ways. The impact measures the additional cost incurred by an updated planning in case of a disturbance. The relevance measures the cost difference between a fully updated and a locally updated plan. With the results of the analysis, key service properties of disturbed services that result in a high impact or high relevance can be determined. Based on this, the network operator can select focus areas to prevent disturbances with high impact and to improve the planning updates in case of disturbances with high relevance. In a case study of the EGS network, the impact and relevance of transit disturbances on all network services are assessed

대중교통 연계수단으로서 Car-hailing 도입시 최적 경로 탐색 알고리즘

학위논문(석사)--서울대학교 대학원 :공과대학 건설환경공학부,2019. 8. 고승영.Promoting the use of transit helps alleviate many problems caused by excessive use of private autos, such as traffic congestion, parking problems and air pollution. In Seoul, the modal split of transit has declined in the past five years and that of private autos has increased. This means that transit is less competitive than private autos, and in order to enhance transit competitiveness, it should first evaluate its competitiveness. Most of the studies evaluating transit focused on the accessibility of transit, which can be measured using factors such as travel time, distance and fare. This study compares the two modes by using five-weekday smart card data in Seoul to obtain the passengers of transit, and by acquiring the travel time of auto and transit through application programming (API) services. Not only travel time is compared, but the number of transit passengers is considered to define transit vulnerable ODs (Origin and Destination) in Seoul. The travel occurred during the morning peak hours where traffic is concentrated is analyzed, and the OD is selected as the transit vulnerable OD when the difference in travel time between transit and auto is more than 5 minutes and the number of passengers of transit is more than 500 in 5 days. By using four multimodal integrated route generating algorithms of each vulnerable OD, combined paths between transit and car-hailing service were generated and compared with existing unimodal paths to identify how the transit competitiveness has improved. Among the multimodal paths generated by the algorithm, the optimum path is selected by calculating the generalized cost, and the optimum paths selected by each algorithm are compared. As a result, the second algorithm, which replaces the bus with the car-hailing service and selects the transfer points before and after the transfer stations of transit path as the origin and the destination of the car-hailing service, is found to find multimodal paths most efficiently. Although the multimodal paths have the shortest travel time at a specific OD in a certain time period, at the majority of the ODs, the multimodal paths have about 30% of the travel time between the car-hailing only and the transit paths. Also, the competitiveness of multimodal path was low for ODs with short travel distance, and the competitiveness of multimodal paths was high at ODs with long travel distance. It is most effective to use the car-hailing service as transit feeder where the access time is long.대중교통의 이용을 활성화하는 것은 교통혼잡, 주차문제, 대기오염 등 과도한 승용차의 이용으로 인해 발생하는 여러 문제들을 완화하는데 도움을 준다. 서울의 경우 최근 5년동안 대중교통의 수단분담률이 감소하고 승용차의 수단분담률이 증가하고 있다. 이는 승용차 대비 대중교통의 경쟁력이 낮다는 것을 의미하고, 경쟁력을 제고하기 위해서는 먼저 대중교통의 경쟁력을 평가해야 한다. 대중교통을 평가한 대다수의 논문들은 대중교통의 접근성에 초점을 두었고, 대중교통 접근성은 통행시간, 거리, 요금 등의 요소들을 이용하여 측정할 수 있다. 본 연구는 서울시 평일 5일치 교통카드 데이터를 이용하여 대중교통의 탑승객 수를 구하고, API 서비스를 이용하여, 승용차와 대중교통의 통행시간을 구득하여, 대중교통과 승용차의 통행시간을 비교하고자 한다. 단순히 통행시간만을 비교한 것이 아니라, 해당하는 출발지와 도착지를 통행했던 대중교통 탑승객 수도 같이 고려하여 서울시의 대중교통 취약 OD를 선정한다. 통행이 집중되는 오전 첨두시에 발생한 통행을 분석하고, 대중교통과 승용차의 통행시간 차이가 5분 이상 나고, 대중교통 탑승객 수가 5일동안 500명 이상인 OD를 취약 OD로 선정한다. 선정된 취약 OD에 대하여 총 네가지의 통합 수단 경로 생성 알고리즘을 이용해 car-hailing 서비스와 대중교통이 결합된 경로를 생성하여, 기존의 단일 수단 경로와 비교하고, 대중교통 경쟁력이 얼마나 개선되는지 파악한다. 알고리즘을 이용해 생성된 통합 수단 경로들 중에서 최적 경로는 일반화 비용을 계산하여 선정하고, 알고리즘 별로 선정된 최적 경로를 비교한다. 그 결과 버스를 Car-hailing 서비스로 대체하고, 환승지점 앞, 뒤 정류장들을 Car-hailing의 출발지와 도착지로 선정하는 두번째 알고리즘이 가장 효율적으로 최적의 수단 통합 경로를 찾는 것으로 나타난다. 통합 수단 경로는 특정 시간대에 특정 OD에서는 가장 짧은 통행시간을 갖기도 하지만, 대다수의 OD에서 수단이 통합된 경로는 car-hailing만 이용한 통행과 대중교통만 이용하는 통행사이의 30% 정도 수준의 통행 시간을 갖는 것으로 나타난다. 또한 통행거리가 짧은 OD에 대해서는 통합수단의 경쟁력이 낮았고, 통행거리가 긴 OD에서 통합수단의 경쟁력이 높았다. 이를 통해 통행거리가 긴 OD 중 접근 시간이 긴 곳에 Car-hailing 서비스를 대중교통 연계수단으로 도입하는 것이 가장 효과적이라 할 수 있다.Chapter 1. Introduction 1 1.1 Background 1 1.2 Objectives 3 Chapter 2. Literature Review 4 2.1 Transit Accessibility 4 2.2 Transit Path Searching Algorithm 7 2.3 Multimodal Path Generation Algorithm 8 Chapter 3. Data and Study Area 10 3.1 Data 10 3.2 Study Area 16 Chapter 4. Methodology 18 4.1 Select Transit Vulnerable ODs 18 4.2 Multimodal Integrated Path Generation Algorithms 21 Chapter 5. Results 39 5.1 Transit Vulnerable ODs 39 5.2 Optimum Multimodal Paths 42 Chapter 6. Conclusions 62 Reference 65 국문 초록 68Maste

Modeling Transit and Intermodal Tours in a Dynamic Multimodal Network

A fixed-point formulation and a simulation-based solution method were developed for modeling intermodal passenger tours in a dynamic transportation network. The model proposed in this paper is a combined model of a dynamic traffic assignment, a schedule-based transit assignment, and a park-and-ride choice model, which assigns intermodal demand (i.e., passengers with drive-to-transit mode) to the optimal park-and-ride station. The proposed model accounts for all segments of passenger tours in the passengers' daily travel, incorporates the constraint on returning to the same park-and-ride location in a tour, and models individual passengers at a disaggregate level. The model has been applied in an integrated travel demand model in Sacramento, California, and feedback to the activity-based demand model is provided through separate time-dependent skim tables for auto, transit, and intermodal trips

Minimum costs paths in intermodal transportation networks with stochastic travel times and overbookings

In intermodal transportation, it is essential to balance the trade-off between the cost and duration of a route. The duration of a path is inherently stochastic because of delays and the possibility of overbooking. We study a problem faced by a company that supports shippers with advice for the route selection. The challenge is to find Pareto-optimal solutions regarding the route's costs and the probability of arriving before a specific deadline. We show how this probability can be calculated in a network with scheduled departure times and the possibility of overbookings. To solve this problem, we give an optimal algorithm, but as its running time becomes too long for larger networks, we also develop a heuristic. The idea of this heuristic is to replace the stochastic variables by deterministic risk measures and solve the resulting deterministic optimization problem. The heuristic produces, in a fraction of the optimal algorithm's running time, solutions of which the costs are only a few percent higher than the optimal costs

An integrated framework for freight forwarders:exploitation of dynamic information for multimodal transportation

Advent of real-time information broadcasting technologies, growth in demand for air-cargo, and increased congestion and variability on air-road network, are the main forces compelling today\u27s air-freight forwarders to improve their operational decision-making to be more competitive and responsive to needs of customers. This research studies the air-cargo transportation on both road (short-haul) and air (long haul) network from the perspective of a mid-size freight forwarder. We develop a routing algorithm for congestion avoidance on air-network based on historical data and introduce an innovative approach to incorporate real-time information to enable dynamic routing of cargo on a stochastic air-network. In the road network, we introduce a new class of pickup and delivery problems to carry out the customer load pickups, fleet management, cargo-to-flight assignments, and airport deliveries in a multiple airport region under alternative access airport policy. The main contributions of this research to the air-cargo literature are the study of the value of real-time information and introduction of the concept of dynamic air-cargo routing. In addition, this is the first study that provides an operational framework to implement the alternative access airport policy. This research also contributes to operations research and logistics literature by introducing a new class of pickup and deliveries with time-sensitive and pair-dependent cost structure. It also contributes an innovative algorithm based on successive subproblem solving for Lagrangian decomposed mixed integer programming that shows to be efficient in obtaining near optimal solutions in reasonable time. The performances of the algorithms presented in this research are tested through experimental and real-world case studies. The results demonstrate that dynamic routing with real-time information can dramatically improve delivery reliability and reduce expected cost on the air-network. Moreover, they confirm that alternative access airport policy can greatly enhance a forwarder\u27s options and reduce the operational and service costs while improving the service levels

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle