Abstract:This paper addresses the search for a run-based dynamic optimal travel strategy, to be supplied through mobile devices (apps) to travelers on a stochastic multiservice transit network, which includes a system forecasting of bus travel times and bus arrival times at stops. The run-based optimal strategy is obtained as a heuristic solution to a Markovian decision problem. The hallmarks of this paper are the proposals to use only traveler state spaces and estimates of dispersion of forecast bus arrival times at s… Show more
“…Future work should also evaluate the possibility of integrating such special needs into upcoming advanced transit advisory tools such as those proposed in Refs. [55][56][57][58][59][60][61]. Providing specific guidance on transit services that meet such special needs can certainly improve the travel experience for users with special needs.…”
Safety is one of the most important needs of all people, but especially those with limited mobility, who face barriers of all kinds on a daily basis. The article includes a review of organizational and legal solutions for the safety of people with special needs in public transportation, as well as preliminary research aimed at identifying and classifying barriers in public transportation that limit the independent movement of people with special needs. The obtained results will be used in the development of the methodology for assessing the degree of accessibility of the studied objects and will form the basis of guidelines formulated in order to modify the existing and design the future elements of the transport system according to the principles of universal design. The problem of the lack of accessibility of public transport is the center of interest of many entities. Its solution requires a complex approach in the design process, taking into account both engineering knowledge and knowledge of the needs and constraints of different user groups. The results obtained from the study will allow the categorization of public transport modes in terms of their accessibility.
“…Future work should also evaluate the possibility of integrating such special needs into upcoming advanced transit advisory tools such as those proposed in Refs. [55][56][57][58][59][60][61]. Providing specific guidance on transit services that meet such special needs can certainly improve the travel experience for users with special needs.…”
Safety is one of the most important needs of all people, but especially those with limited mobility, who face barriers of all kinds on a daily basis. The article includes a review of organizational and legal solutions for the safety of people with special needs in public transportation, as well as preliminary research aimed at identifying and classifying barriers in public transportation that limit the independent movement of people with special needs. The obtained results will be used in the development of the methodology for assessing the degree of accessibility of the studied objects and will form the basis of guidelines formulated in order to modify the existing and design the future elements of the transport system according to the principles of universal design. The problem of the lack of accessibility of public transport is the center of interest of many entities. Its solution requires a complex approach in the design process, taking into account both engineering knowledge and knowledge of the needs and constraints of different user groups. The results obtained from the study will allow the categorization of public transport modes in terms of their accessibility.
“…According to the comparative analysis of simulation under undersaturated and oversaturated scenarios as shown in Fig. 8 , undersaturated traffic saw equal control effects of the two control methods; however, as the state of traffic flow changed from undersaturated to oversaturated, the active control method in the paper 34 had a significantly better control effect than the paper 35 . Figure 8 Comparison of control effects.…”
Though effective in theoretical simulation, the established traffic control models and optimization algorithms will result in model mismatch or even control strategy failure in actual application. However, they are commonly adopted in traffic signal control research, resulting in the unavailability of many exceptional control algorithms in practice. Simulation should function as a bridge between theoretical research and actual application, allowing the gap between the two to be communicated and made up for. However, an effective connection between the two has yet to be established to enable simulation methods in existing traffic control research. To this end, we designed and developed a simulation platform for "Online Application—HILS (Hardware-in-the-Loop Simulation)—Practice" integration over traffic signal control. In this paper, the architecture and characteristics of the integrated simulation platform were described. Besides, the function of each module of the platform was detailed, followed by listing simulation examples for six complex scenarios, with the active control scenario being selected for simulation comparison analysis. The findings demonstrated extensive road network simulation with the integrated simulation platform, multidimensional control variables, control strategies with support, as well as stable and reliable operation. It can be used to verify several sorts of traffic control simulation with variable dimensions.
“…Transfer Flow Imputation. Data loss is difficult to avoid due to various failures, manifested as a certain rate of zeros in matrix Y = { as proactively adjusting the schedules across diverse traffic vehicles and stations, and ultimately improve the efficiency and effectiveness of transport systems [32,33].…”
Section: Definition 3 Transfer Flow Prediction Traffic Prediction Is ...mentioning
Accurate forecasting of the future transfer passenger flow from historical data is essential for helping travelers to adjust their trips, optimal resource allocation and alleviating traffic congestion. However, current studies have mainly emphasized predicting traffic parameters for a single type of transport, while lacking research into transfer passenger flow influenced by multiple factors across different transport modes. Additionally, efficient traffic prediction relies on high-quality traffic data, yet data loss issues are inevitable but often ignored. To fill these gaps, we present for the first time a reliable joint long short-term memory with matrix factorization deep learning model (i.e., Joint-IF) for accurate imputation and forecasting of transfer passenger flow between metro and bus. This hybrid Joint-IF model uses a repair-before-prediction strategy to deliver the final high-quality outputs. In particular, we simulate a variety of missing combinations under the natural conditions and apply a low-rank matrix factorization to infer those lost values. In addition, we investigate the effects of crucial parameters and spatiotemporal features on transfer flow prediction. To validate the effectiveness of Joint-IF, a large series of experiments are carried out for models’ comparison and validation on the real-world transfer passenger flow dataset of the Shenzhen public transport system, and the results show that the proposed Joint-IF performs better for both imputation and forecasting of transfer passenger flow relative to the baseline models in terms of accuracy and stability.
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