Multimodal Transportation最新文献

China has taken a number of positive measures to meet the requirement of environmental protection. The switch to electricity especially in transport sector is considered as a promising way to reducing greenhouse gas (GHG) emissions and facilitating to meet China's carbon neutral target in 2060. Besides, because of the overall impact of the COVID-19 on the transport sector, the future measures imposed by the government on electric vehicles (EVs) remain in high uncertainty. Taking the characteristics of different vehicles, business models, uncertainty of government financial subsidies and environmental factors into consideration, a replacement optimization model for a taxi fleet is proposed in this study under the cap-and-trade system. We assume that the taxi company has four types of vehicles to purchase or lease and manage to maximum the pecuniary advantages and environmental benefits simultaneously. Experimental results analyze that EVs and battery-swap electric vehicles (BSVs) are highly competitive when government subsidies do not decline. During the early stage of the planning horizon, adjusting the fleet continuously and timely can help the company to realizing the maximum revenue.

In recent decades, increasing emphasis is being placed on sustainable freight transport. The aim of this study is to discern how detailed the calculation of CO₂e emissions in road transport is. For this, the study conducted a sample review with 53 scientific sources and 121 annual reports. Only 14 out of the 53 scientific sources incorporated emissions that occur as a by-product of energy supply. Not more than 14 of the 121 companies included emissions from transportation activities of both the upstream and downstream processes. Therefore, the study highlights the necessity for new and validated models to support decision-making processes that sustainably reduce CO₂e emissions.

This study examines three methods of collaboration and profit-sharing for less-than-truckload (LTL) carriers. The collaboration methods are evaluated under the scenario that all participating carriers share some or all of their pickup and delivery jobs with a central authority who will assign jobs to carriers and determine optimal vehicle routes to maximize profit. The novelty of this work is that it allows carriers to retain some of their jobs. Collaboration Method 1 is a two-step approach where the first step involves the central authority determining the job allocation for the shared jobs and the vehicle routes for each carrier that includes their retained and allocated jobs to maximize total profit. The second step involves dividing the total profit among the carriers using a contribution-based profit-sharing model. Collaboration Method 2 is a one-step approach where the central authority simultaneously determines the job allocation and vehicle routes, and at the same time allocates profit to the carriers with fairness constraints included in the model. Collaboration Method 3 is also a two-step approach similar to Method 1, except that in the first step, the central authority determines the job allocation and vehicle routes for only the shared jobs (not including retained jobs). Mathematical models and solution algorithms based on large neighborhood search (LNS) are proposed for all three methods. The numerical experiments are conducted using hypothetical networks with up to 30 jobs and 3 carriers. Results indicate that on an average the total profit from Method 1 is 5.3% higher than that of Method 2 and 11.88% higher than that of Method 3. The total profit from Method 2 is 6.60% higher than that of Method 3.

New mobility concepts are needed as cities become ever more congested and polluted by traffic. One factor for the growing traffic volume is the increasing delivery traffic leading to a need for sustainable concepts for urban logistics and last-mile delivery. Innovative vehicle concepts, like automated micro-vehicles, present one promising approach. However, not much is yet known about drivers and barriers for the acceptance of these vehicles from the perspective of other road users – i.e. those people sharing traffic space with automated micro-vehicles. In two consecutive animation-based experiments (n = 107, n = 543), we analysed the effect of varying behaviour and design of automated micro-vehicles on other road users’ risk perception, trust, and acceptance. Speed, braking behaviour, automation mode, number of vehicles in convoy, distance between vehicles as well as colour design significantly affect risk perceptions, trust, and partly acceptance. The results inform the development and regulation of automated micro-vehicles.

Ride pooling (RP) is a transport mode using on-demand buses to combine the trips of multiple users into one vehicle. Its required fleet size and carbon emissions are quantified by the system’s efficiency. Due to the complex interplay between street network, buses, users and dispatch algorithm, efficiency case studies are available but bottom-up predictions are not. Here we close this gap using probabilistic and geometric arguments in an analytical model framework. Its modular design allows for adaptation to specific usage scenarios and provides an over-arching view of them. In a showcase on Euclidean spaces, our model quantifies how RP outperforms private cars as user demand increases. Its predicted power-law scaling is verified using a custom simulation framework, which further reveals improved scaling on real street networks and graphs with hierarchical structures. Henceforth, our work may help to identify street networks well-suited for RP, and predict key performance indicators analytically.

Several Canadian cities observed a shift from public transit use to private cars and active transport modes during the COVID-19 pandemic. At a moment where pre-pandemic public transit users are reconsidering their travel options, studies describing their attitudes toward cycling are lacking. Because most trips in urban areas involve short- and mid-range travel, cycling is seen as a promising environmentally sustainable means of transportation. This study aims to describe how pre-pandemic public transit users in Toronto and Vancouver view cycling, including their comfort with available infrastructure, cycling frequency, and perceived barriers to adoption. Data from the Public Transit and COVID-19 Survey, a web-based panel survey of over 3500 regular transit riders in Toronto and Vancouver administered in May 2020 and April 2021 were analysed. Applying Geller's typology, 70% of participants could be classified as interested but concerned and one fifth as no way no how regarding their comfort levels toward cycling. Women were more likely to be no way no how cyclist type. Weather, lack of safe routes, and having to carry things were the main barriers to cycling in both cities. Our results give insight on who should be targeted by city initiatives aiming to promote changes toward more active modes of transportation. Further studies with a causal design are required to identify possible mitigating strategies to the main barriers to cycling.

Exploring approaches for improving the service quality (SQ) of the urban multimodal transportation hub (MMTH) and alluring new passengers for providing seamless and sustainable mobility are the major concerns and objectives for transport planners and operating agencies in the contemporary world. Considering the fact, the present study endeavours to identify the association of users’ socio-demographics and travel characteristics with different service quality levels developed for a MMTH. The data was collected from 515 users of Anand Vihar MMTH, Delhi. K-means clustering categorized SQ in three levels: low, medium, and high. Association Rules Mining approach was used to generate various interesting rules, which also highlighted the disparity among users’ perceptions on the basis of three different SQ levels. Results demonstrated that the ‘passengers travelling 3 to 5 times per week’, ‘those who were having the availability of driving license’, ‘users with more than 15 minutes of transfer time’, and ‘the female users’ were the least satisfied with the SQ of MMTH. Interestingly, ‘the graduates with high-income travelling for work purpose’ and ‘users who were retired from their jobs’ were highly convinced with SQ. The research outcomes will be advantageous to the transport policy makers while implementing the user-based policies in the MMTH for embellishing the public transport infrastructure and to make the urban cities inclusive, resilient, safe and sustainable.

There are many different ways of practicing coworking, and many different forms of CoWorking Spaces (CWSs). In this paper, we define CWSs in economic and spatial terms, and we provide some explanations on the transport mode used to travel to. Is the transport mode used to get to CWSs the same as that which is usually used for travel for work purposes? Does the spatial location of the CWS (in large city - medium-sized town - rural community) have an impact on the transport mode choice? The key issue is determining whether these new working spaces favor a shift in travel behavior toward practices less centered on the car. We use a survey of coworkers conducted in 2019 in the Auvergne-Rhône-Alpes Region (AURA), from which data is processed using a binomial logit model. The estimation results show that the mode choice for traveling to CWSs does not allow us to identify a characteristic that is fundamentally different from mode choice for work purpose. However, the availability of a parking place in CWSs is identified as a possible public policy level.

Multimodal facilities are being built in a majority of urban areas to accommodate both motorized and non-motorized traffic. The resulting transportation system is susceptible to complex interactions between different modes and users. These complex interactions are hard to quantify and capture on a regular basis. There is a need to rely on a microsimulation platform to replicate such real-world scenarios and forecast future conditions. This study focuses on assessing the effect of heterogeneous traffic conditions involving multiple modes like light rail transit (LRT), walking, bicycling, and motorized traffic on vehicle delay at intersections using Vissim traffic simulation software. A 2.5-mile urban arterial corridor comprising of seven at-grade and two grade-separated signalized intersections along US-29 route in the city of Charlotte, NC, USA was chosen for analysis and modeling. Base simulation model was developed by replicating the traffic scenario for the year 2018 (without LRT and non-motorized traffic). External controllers like VisVAP and Viswalk were used to assign signal priority and model heterogenous traffic conditions. The vehicle operational performance of the corridor improved along the major street after the addition of the LRT. An increase in vehicle delay on the major street was observed with an increase in the non-motorized traffic. Contrarily, the operational performance of the cross-streets at at-grade intersections did not see any significant change due to the addition of non-motorized traffic. The proposed framework assists planners to assess the impact of adding a new transit system like LRT and associated non-motorized traffic on the urban corridor.

The majority of cities in both developed and developing countries are confronted with negative externalities from imbalanced land-use and transportation systems. This is mainly due to fast urbanization process as well as the separated planning of the land use and transportation systems. In most of these countries, new towns and cities are being built in the suburban areas to meet the growing demands. However, there are limited methods in the literature detailing how the balance of land use and the transportation system can be examined, especially those involving new town developments. In this study, a framework is proposed. Within the proposed framework, an integrated land-use transport model is developed (using the Production, Exchange, and Consumption Allocation System (PECAS)) and calibrated to forecast land-use activities, which includes a land-use sub-model for estimating future land use patterns and a multimodal transport sub-model to predict travel demand. Furthermore, a method for evaluating the balance between land use activities and the transportation system is adopted and modified at both the local level – traffic analysis zone (TAZs) and system-level – region connecting the new city and main city. The proposed balance evaluation framework is applied to the Yangtze River New City (YRNC) of the City of Wuhan as a case study. The results from the case study show that the proposed framework can be used to examine the balance of land use and transportation system of new towns and cities at both local and regional levels as a versatile decision-support system (DSS) for sustainable planning and development of new towns and cities.