Modal Split Model Research Articles

Capturing impacts of travel preference on connected autonomous vehicle adoption of risk-averse travellers in multi-modal transportation networks

ABSTRACT This paper proposes a reliability-based combined modal split and traffic assignment model for the multi-modal transportation network with uncertainties in which the travellers' travel preferences, vehicle ownership, and the characteristics of connected autonomous vehicles (CAVs) are considered. Travellers are classified into captive travellers and choice travellers according to their preference for travel modes and vehicle ownership. The choice travellers need to make a tradeoff among the out-of-pocket cost, comfort, and travel time reliability and make decisions between continuing to commute by subway or purchasing a human-driven vehicle (HV) or CAV. The dogit-nested-logit model is adopted to characterise the effect of travel preference on the adoption of CAVs of the choice travellers, and the multinomial logit model is adopted to capture the effect of the differences between HV and CAV on information quality and value of travel time reliability on the path choice behaviour of travellers. The problem is formulated as an equivalent variational inequality model based on the properties of the equilibrium state, and its equivalency and solution existence are discussed. A path-based algorithm is employed for solving the problem, which combines the Monte Carlo simulation-based method and the column generation method. Numerical experiments are presented to illustrate the properties of the proposed models and validate the algorithm.

Kombinasi Model Trip Generation-Modal Split (G-MS) Dalam Perencanaan Bus Bandara Terintegrasi

The modal split model can be varied to other model in the concept of four step models transportation. This approach model can be varied depending on the purpose of transport planning, such as the modal split planning process which is carried out at the trip generation calculation stage, and in this process the movement of public transport can be directly separated from private transport with the assumption that someone who will travel can choose the model that is influenced by socioeconomic valiable. The model combined experiment (G-MS) was carried out on the route to and from Jambi’s Sultan Thaha Airport, which is one of the transportation nodes that plays an important role in regional development in Jambi City. The aim of this research is to analyze potential demand using a combination of the Trip Generation-Modal Split (G-MS) model. Based on the results of the analysis using the binomial ratio logit model with the value Y = Proportion of passengers/days. The passenger distribution area is devided base on zones where the zones that have the potential to be passenger gathering point are zone 9, zone 10 and zone 11. Calculation of the chi-square test (goodness of fit test) shows that the calculation X2 value is 11.583 and the table X2 is 14.067 because X2 count <X2 table, then H0 is accepted which means the observation results are the same as the average model results so that model validation is declared successful, so this research can be used to calculate passenger demand to plan airport buses.

Revisiting modal split as an urban sustainability indicator using citizen science

This paper discusses three uses of modal split indicators, and illustrates how it evolved from a technical, intermediate step in transport analysis, over a measure of transport system efficiency to a symbolic urban sustainable mobility indicator. A framework which includes 11 factors is presented and applied to the different uses of the modal split indicator. Besides the comparison of the three main uses of modal split in research and practice, this contribution focuses on a citizen science project (Straatvinken) in the region of Flanders, Belgium. In this project thousands of citizens carry out traffic counts. While the project was initially set up to monitor modal split targets in the urban area of Antwerp, the emphasis shifted towards street liveability. This is visible in the fact that the citizen science project added a narrative-based liveability survey to capture experiences with and evaluations of the liveability at street level. The case illustrates that citizen science is, besides a tool to address data gaps, also an approach to increase the validity of indicators. The reason is that citizen science, which seems to be underexplored in transport studies, differs in what gets measured, how it is measured and why. This approach has proven to provide a fine-grained, integrated assessment of street-level changes in the composition and intensity of the traffic and their effects on the perceived liveability. We argue that it strengthens and complements traditional modal split measurements at the regional or urban level, which typically rely on the modelling of individual mobility behaviour based on household travel surveys. Traditional approaches allow observing broad trends in mobility choices at the regional level, but they do not provide insights in how those individual choices translate into effects at street level. Although often initiated out of certain sustainability concerns, existing modal split models do not reveal how an observed modal shift at the regional level affects the perceived liveability or sustainability at street level.

Stated Preference Analysis With Latent Variables for Higher Speed Rail

Recently, the necessity to redefine the mode selection model (modal split model) has emerged owing to the diversification of transportation systems. In addition to socio-economic factors, preference factors and user characteristics significantly affect the selection of transportation mode. Therefore, user preferences are reflected in the modal split model. The latent class model is highly descriptive, and its suitability can be improved. With the advent of high-speed rail (Great Train eXpress [GTX]), Seoul has established a competitive and complementary relationship for the demand of passengers between general and great express rail. Therefore, a modal split model reflecting the characteristics of the GTX, which is redefined by applying a latent variable to the stated preference analysis, is necessary. Latent class analysis uses the Bayesian information criterion and log-likelihood to distinguish the travel property (Cluster1), station property (Cluster2), and transfer property (Cluster 3). After comparing the time values for each cluster, the GTX preference is analyzed based on the inner and outer circle situations. A model that accurately reflects the characteristics and preferences of passengers is proposed in this paper. In the future, strategies can be established for the inner and outer circle situations, and higher operational efficiency can be achieved by combining the GTX and subway.

Accessibility-based vulnerability analysis of multi-modal transportation networks with weibit choice models

This study proposes utility-based accessibility measures and a weibit-based analysis method for analyzing multi-modal transportation network vulnerability. To account for the multi-dimensional travel choice behavior in multi-modal transportation networks, an advanced weibit-based combined modal split and traffic assignment model is adopted to derive the accessibility measures based on the weibit-expected travel disutility from both route choice and mode choice dimensions. The accessibility at the modal split level is derived from the nested weibit model, while that at the route choice level is obtained based on the path-size weibit model. The proposed weibit-based vulnerability measures are inherently suitable for assessing the relative degradation in network performance and can measure the vulnerability of networks with heterogeneous scales without overestimating the importance of modes or routes sharing similar features. Using a simplified multi-modal transportation network of Hong Kong, numerical experiments are conducted to demonstrate the properties of the proposed multi-modal vulnerability analysis. The results indicate that the proposed analysis can effectively address similarity and heterogeneity issues in the analysis of choice behavior and network vulnerability, which are often ignored by the traditional logit-based measures.

Multimodal Urban Transportation Network Capacity Model Considering Intermodal Transportation

Transportation network capacity is an important indicator from measuring the performance of a transportation system. Previous studies on the capacity of multimodal networks have not considered transfers between different transportation modes. In fact, because of the diversified development of the urban transportation system, travelers are no longer limited to a single transportation mode in daily travel. This paper thus proposes an improved network capacity model considering intermodal transportation in urban multimodal transportation systems. The proposed network capacity model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) model. The CMSTA model consists of a cross-nested logit (CNL) in the phase of mode split to account for intermodal transportation and a path-size logit (PSL) in the phase of traffic assignment to account for route overlapping. Also, we consider the flow interaction of different modes (e.g., car and bus) when they share the same links. The Barzilai–Borwein step size method is used to efficiently solve the lower-level CMSTA model (i.e., the CNL-PSL model) of which the objective function is complicated. The numerical results demonstrate the advantages and features of the proposed model. The model is also applied to a real network case to assess the network capacity of the multimodal transportation system.

Parking Allocation Index Analysis of Office Building Based on the TOD Measurement Method

Under the overall strategic guidance of emission peaks and carbon neutrality, an increasing number of cities are focusing on sustainable transportation development as an important measure for sustainable transportation development. Transit-oriented development (TOD) can guide residents to green trip options and reduce the dependence on private cars. Many cities have qualitatively reduced the parking allocation index of office buildings around rail stations, and quantitative research on the influence area and degree of TOD is lacking. This paper selects office buildings in the rail transit station influence area as the research object, puts forward the TOD measurement method of rail transit stations based on the improved “Node-Place” model, and clusters the stations under different measurement indices by the K-means algorithm. For different types of stations, the multinomial logit (MNL) model is used to build different types of trip mode split models to put forward the reduction calculation method of the parking allocation index of office buildings in the rail transit station influence area. Finally, this paper applies the revision of Nanjing’s allocation index in 2019, and the TOD measurement is identified through the “Node-Place-Connection” model. The optimized calculation method of the parking allocation index for office buildings is proposed. The results indicate that the method can reduce parking allocations to encourage the use of green transportation and guide the construction of urban sustainable transportation systems.

Developing a Modal Split Model Using Fuzzy Inference System in Ramadi City

Several different deterministic and probabilistic mathematical approaches have been used to develop modal split models. The data collected by a questionnaire survey approach is frequently associated with subjectivity, imprecision, and ambiguity. additionally, several linguistic terms are used to express some of the transportation planning variables. This can be solved by modeling mode choosing behavior with artificial intelligence techniques such as fuzzy logic. In this research, Ramadi city in Iraq has been selected as a study area. For the purpose of obtaining data, the study area was divided into traffic analysis zones (TAZ). The total number of traffic zones was set as 28 traffic zones, 22 were internal traffic zones and 6 external traffic zones. Field surveys and questionnaires are used to collect data on traffic, land use, and socioeconomic characteristics factors (age, gender, vehicle ownership, family income, trip purpose, trip origin and destination, trip time, waiting duration, duration inside mode, trip origin and destination, trip cost, and type of mode used for transport). The results showed that the modal split models based on the fuzzy inference system can deal with linguistic variables as well as address uncertainty and subjectivity and they gave very good prediction accuracy for future prediction. Fuzzy inference system proved that all factors affected the mode choice with a very strong correlation coefficient (R) equal to 93.1 for general trips but when the results were compared with multiple linear regression model found that the correlation coefficient (R) equal to 28.9 for general trips and the most influential factors on the mode choice are car ownership, age and trip cost. Thus, it can be concluded that fuzzy logic models were more capable of capturing and integrating human knowledge in mode selection behavior. In addition, this study will help decision-makers to plan transportation policies for Ramadi city

Modal Split Model Using Multiple Linear Regression Analysis

Several modal split models have been created around the world to forecast which mode of transportation will be selected by the trip - maker from among a variety of available modes of transportation. This modeling is essential from a planning standpoint, as transportation systems typically receive significant investment. In this study, the main purpose was to develop a mode choice model using multiple linear regressions for Ramadi city in Iraq. The study area was divided into traffic analysis zones (TAZ) to facilitate data collection. The data was collected through a home interview of the trip makers in their home units through a questionnaire designed for this purpose. The result showed that the most influential factors on the mode choice for the general trips model using multiple linear regressions are car ownership, age, and trip cost. This model gave a good correlation coefficient of 0.829 meaning that the independent variables explain 82.9 of variance in the dependent variable (type of mode), which will help transport planners in developing policies and solutions for future

Impacts of short-term measures to decarbonize maritime transport on perishable cargoes

The International Maritime Organization (IMO) has adopted a strategy to reduce emissions from international shipping that sets very ambitious targets. The first set of actions, so-called short-term measures, are expected to be implemented by 2023 and result in a reduction of emission intensity by at least 40% by 2030 compared with 2008 levels. Compliance may be achieved through a reduction in sailing speeds, but certain countries have raised concerns on the ramifications of longer transit times on their exports, particularly for perishable products. In this paper, we present a methodology to assess the impacts of various short-term measures on perishable products. We use an extension of a nested modal split model to examine shifts towards other modes of transport. We demonstrate our methodology with a transpacific case study carrying perishable products from South America to China. We compare the short-term measures currently under discussion, in one of the first academic studies to explore these issues. These include a speed limit approach, a power limit, and a goal-based measure. Our results show that a power limit or a goal-based measure would offer some advantages to liner shipping operators using more efficient vessels, unlike a speed limit. Using 2008 as the benchmark year has resulted in small speed reductions required by the liner shipping sector to reach its targets. For perishable cargoes, small speed reductions can be tolerated by the shippers without significant modal shift. Choosing the right short-term strategy is of utmost importance to promote clean shipping practices in the following years.

An ex-ante analysis of transport impacts of a distance-based heavy goods vehicle charge in the Netherlands

In 2017, the newly installed Dutch government announced in its coalition agreement to introduce a distance-based heavy goods vehicle charge, similar to the charges levied in other European countries. To study the possible transport impacts, we applied available models and methods in preparation for the introduction of this truck charge in the Netherlands in 2023, in order to present decision information to the government on different aspects of the charge. In this paper we present the analysis of different implementation scenarios for a distance-based truck charge. Different behavioural responses can be expected in terms of freight transport demand, mode choice, logistic efficiency, and route choice. Many studies however lack sufficient detail to properly describe the impact of road charges for HGV on OD flows and freight traffic. In our contribution we explore the bandwidth of impacts of different pricing schemes, using strategic transport models for freight demand and traffic assignment, with detailed modal split and route choice models, ensuring a proper representation of generalsed transport costs. We explain how we use available transport models in an overarching analytical framework to make a comprehensive impact assessment of the different responses, and to decompose the impacts on the different responses. Final impacts are quantified in terms of freight demand (spatial pattern of transport flows), modal split and traffic flows (route choice, and congestion).Depending on the pricing scenario the tonne kilometres decrease by 0.4%–4.8% on average. The modal shift impacts are stronger on longer transport distances: this is explained both by the larger impact of a distance-based charge on these routes, and by higher substitution possibilities to barge or rail. The results indicate that the overall impacts of the introduction of the different charging alternatives are moderate. However, the network impacts at local level can be substantial due to the impact of re-routing of truck trips to avoid charge.

Mode Choice Change under Environmental Constraints in the Combined Modal Split and Traffic Assignment Model

With the increasing level of air pollution and fine dust, many countries are trying to prevent further environmental damage, with various government legislations, such as the Kyoto Protocol and the Paris Agreement. In the transportation field, a variety of environmental protection schemes are also being considered (e.g., banning old diesel vehicles, alternate no-driving systems, electric car subsidies, and environmental cost charging by tax). Imposing environmental constraints is a good approach to reflect various environmental protections. The objective of this research was to analyze the mode-choice and route-choice changes based on imposing environmental constraints. For the objective, a combined modal split and traffic assignment (CMA) model with an environmental constraint model was developed. For the environmental constraint, carbon monoxide (CO) was adopted, because most of the CO emissions in the air are emitted by motorized vehicles. After a detailed description of the model, the validity and some properties of the model and algorithm are demonstrated with two numerical examples (e.g., a small and a real network in the city of Winnipeg, Canada). From the numerical results, we can observe that imposing the small restriction (or strict) value has more efficiency in mode change and reducing network emission.

Morning modal split model of economically active people in Zilina region

The paper deals with the parameterization of the morning modal split in the four-step model of the traffic prognosis for the economically active population. Multiple Logit model theory is the process of calculating the modal split. This model is in common use for transport modeling. Its advantage is that we can choose from more independent variables. The estimation of Logit function parameters is based on a transport - sociological survey in the Žilina region.The choice of a specific transport mode of transport is expressed by the utility function. The Biogeme program was used for the trip utility function parameters estimation. The primary task was to create a set of Logit functions performance parameters for Žilina region transport conditions, specifically for the economically active population group in the morning rush time (05:00 – 09:00). Person groups are characterized by their behavior in the transport process. The modal split was taken into account in the trip distribution by transport modes: car - driver, car - passenger, bike, pedestrian transport, public transport, bus and train.

Railway's Impacts on Modal Shift Potential Towards Intermodal Transportation: A Case Study in Lao PDR.

Chinese government has developed transport infrastructure rapidly under Belt and Road Initiative (BRI) strategy. The BRI strategy is China's economic development strategies for expanding trade and cultural influence towards countries in western and eastern regions, including ASEAN. The development of BRI strategy is consists of two main components i.e., (i) the Silk Road Economic Belt, follows the historical overland Silk Road through Central Asia, Iran, Turkey and eventually to Europe, and (ii) the Maritime Silk Road, originates in the South China Sea, passing through the Malacca Strait, the Indian Ocean, and the Red Sea and extending into the Mediterranean Sea (Chris & Elizabeth, 2015). Due to the BRI strategy, more than 6000 trains made the journey from China to Europe in 2018, which is an increase of 72% compared to 2017. China has sent more than 11,000 freight trains to Europe and back since the BRI strategy was announced in 2013. Railway networks have been constructed under the BRI strategy for connecting 48 Chinese cities with 42 cities in Europe through Asia. There are many railway infrastructures under the BRI strategy. The China – Laos railway (Vientiane–Boten railway) is one of project under the Silk Road Economic Belt that has been developed for serving as a key infrastructure for the economic corridor between the two countries. In nearly future, this railway will be helped to boost trade, investment and tourism for Lao PDR. and south China's Guangxi Zhuang Autonomous Region. The Vientiane–Boten railway, especially transportation time will attract both travelers and Logistics Service Providers (LSP), which can be reduced time of journey compared with road mode. In this paper, modal shift potential of travelers and freight on Kunming-Bangkok Highway (R3A), AH2, AH8, AH9, AH10, AH12, AH13, and AH18 have been investigated by considering behavioral aspects of long distance travel. Keywords: Mode Split Model, Modal Shift, Vientiane–Boten railway, Travel Behaviour

A Combined Modal and Route Choice Behavioral Complementarity Equilibrium Model with Users of Vehicles and Electric Bicycles.

The popularity of electric bicycles in China makes them a common transportation mode for people to commute and move around. However, with the increase in traffic volumes for both vehicles and electric bicycles, urban traffic safety and congestion problems are rising due to traffic conflicts between these two modes. To regulate travel behavior, it is essential to analyze the mode choice and route choice behaviors of travelers. This study proposes a combined modal split and multiclass traffic user equilibrium model formulated as a complementarity problem (CP) to simultaneously characterize the mode choice behavior and route choice behavior of both vehicle and electric bicycle users. This model captures the impacts of route travel time and out-of-pocket cost on travelers’ route choice behaviors. Further, modified Bureau of Public Roads (BPR) functions are developed to model the travel times of links with and without physical separation between vehicle lanes and bicycle lanes. This study also analyzes the conditions for uniqueness of the equilibrium solution. A Newton method is developed to solve the proposed model. Numerical examples with different scales are used to validate the proposed model. The results show that electric bicycles are more favored by travelers during times of high network congestion. In addition, total system travel time can be reduced significantly through physical separation of vehicle lanes from electric bicycle lanes to minimize their mutual interference.

A Combined Modal Split and Traffic Assignment Model With Capacity Constraints for Siting Remote Park-and-Ride Facilities

From the perspective of urbanization, commuters' long-distance and diversified trips are suitable for the connection between city and suburbs. The existing park-and-ride (P&R) facilities can influence user travel decisions, promoting the usage of public transportation and reducing the environmental pollution, but the P&R lots are usually located near train stations that the construction of lots at these locations is costly and complex. It is important to analyze the need for P&R and its capacity before its construction. Therefore, this paper proposes a bi-level model for determination of optimal location and capacity of a remote P&R (RPR) facility that allows a user to park a vehicle in a suburban area at lower cost and then take a bus to the nearby train station. A combined modal split and traffic assignment model with capacity constraints is developed as a lower-level model, and a nested-logit model is adopted to manage the mode similarity. The upper-level optimization is conducted based on the generalized cost of the transportation system according to the budget and environmental limits. The performance of the proposed model is experimentally verified that the optimal RPR scheme shifts commuters from the automobile mode to the transit and RPR modes, thus improving the social benefit dramatically. The model and analysis provide insights that may help operators determine how RPR facilities can be established to meet social cost improvement goals.

A study on parking supply optimization in central business districts considering the two-way interaction between car traveling and parking

This paper proposes a bilevel programming model to optimize the parking supply in a central business district (CBD) considering the interaction between car traveling and car parking. The upper model (UM) determines the number and locations of parking lots in a CBD with the objective of minimizing the average impedance of all car trips. The lower model (LM) is a modal split and assignment combination model for calculating the traffic flow under various parking supply schemes. In addition to the bilevel model, a gravity model (GM) is proposed to calculate the car trips that are induced by the added parking lots. The interaction between car traveling and parking can be simulated by the feedbacks between the UM and LM. A case study is performed with real data from Dalian City. The results show that there is a negative correlation between parking supply increments and the average traveling impedance when the number of parking spaces is lower than the optimal value; however, the average traveling impedance will start to increase with the increase in parking supply when the number of parking spaces is higher than the optimal value.

A study on parking supply optimization in central business districts considering the two way interaction between car traveling and parking

This paper proposes a bilevel programming model to optimize the parking supply in a central business district (CBD) considering the interaction between car traveling and car parking. The upper model (UM) determines the number and locations of parking lots in a CBD with the objective of minimizing the average impedance of all car trips. The lower model (LM) is a modal split and assignment combination model for calculating the traffic flow under various parking supply schemes. In addition to the bilevel model, a gravity model (GM) is proposed to calculate the car trips that are induced by the added parking lots. The interaction between car traveling and parking can be simulated by the feedbacks between the UM and LM. A case study is performed with real data from Dalian City. The results show that there is a negative correlation between parking supply increments and the average traveling impedance when the number of parking spaces is lower than the optimal value; however, the average traveling impedance will start to increase with the increase in parking supply when the number of parking spaces is higher than the optimal value.

Developing an Empirical Pipeline and Rail Crude Oil Mode Split and Route Assignment Model

In recent years, improvements in pipeline capacities and connectivity have been inhibited by environmental and political concerns (e.g., the Dakota and Keystone XL pipeline expansion projects). This has resulted in a greater dependency on rail transport, and this modal shift of crude oil from pipeline to rail is likely to become more pronounced in the future. Therefore, there is a need to assess the impacts of future changes in pipeline/rail network connectivity, modal attributes, and shipment protocols, on the expected pattern of crude oil shipments. This paper presents a rule-based mode split and route assignment model that reflects real-world allocation, assignment, and apportionment rules. The decision-making process underlying this model is the shipper, who is prioritized by the carrier when there is limited pipeline capacity available. The proposed algorithm allows for the inclusion of crude oil shipments and the pipeline network into conventional freight demand models by capturing the complex interactions of crude shippers, pipeline carriers, and regulatory bodies. This paper demonstrates how the model can be used to predict changes in Canadian crude oil flow patterns and mode shares subject to changes in specific transportation network attributes or crude oil demands.

Modelling Rail-Based Park and Ride with Environmental Constraints in a Multimodal Transport Network

Environmental sustainability is a significant aspect in the sustainable development of modern urban cities, especially in the road transport system. As traffic demands increase, public transport requires more promotion to accommodate the increasing travel demands while maintaining the environmental quality. Public transport, however, is less attractive in vast suburb areas mainly due to its longer travel distance and waiting time. Therefore, this paper proposes a rail-based Park-and-Ride (RPR) scheme to promote public transport in the multimodal transport network. To remedy the heterogeneous distribution of vehicle pollutants in the network, regulations in environmental sensitive districts are required and studied in this paper. To quantitatively evaluate and analyse this joint RPR and environmental regulation strategy in multimodal transport systems, this paper develops an environmental constrained combined modal split and traffic assignment (EC-CMSTA) model. The proposed formulation adopts the concept of fix-point to reformulate the nonlinear complementarity conditions associated with the combined modal split and user equilibrium conditions, which is subsequently incorporated into a VI formulated nonlinear complementarity conditions associated with environmental constraints. The proposed VI formulation can handle a general constraint structure, which enhances the modelling adaptability and flexibility. The strictly monotone and Lipschitz continuity properties of this model are rigorously proved, giving rise to efficient algorithms for the model. A customized projection based self-adaptive gradient projection (SAGP) algorithm is then developed. Numerical studies demonstrate that the EC-MSTA model could enhance the behavioural modelling of network users’ travel decisions and assist in quantitatively evaluating the effectiveness of RPR schemes and environmental regulations.