Intercity Transportation Research Articles

Influencing Factor Analysis and Demand Forecasting of Intercity Online Car-Hailing Travel

Online car-hailing travel has become an important part of the urban transportation system and is gradually changing the mode of intercity travel. Analyzing and understanding the influencing factors of intercity online car-hailing travel hold great significance for planning and designing intercity transportation and transfer systems. However, few studies have analyzed the influencing factors of intercity car-hailing travel or forecast travel demand. This paper takes trips between Yinchuan and Shizuishan, China, as the research case and analyzes the influence of time, space, passengers, and the environment on intercity online car-hailing travel. The relationship between the urban built environment and intercity online car-hailing travel demand is also investigated through a geographically weighted regression (GWR) model. We find that the peak hours for intercity car-hailing trips are between 9:00 and 10:00 and between 16:00 and 18:00, which are significantly different from those for intracity trips. Weather conditions strongly affect the mobility of intercity trips. The urban built environment also has a significant impact on intercity car-hailing ridership, and residential districts and transportation facilities are the factors with the greatest influence on intercity online car-hailing travel. These results can provide practical help to city managers improve the management of intercity traffic and develop better transportation policies.

Inter-city transport infrastructure and intra-city housing markets: Estimating the redistribution effect of high-speed rail in Shenzhen, China

This study analyses the changes in intra-city housing values in response to improved inter-city connection brought by high-speed rail (HSR), using the opening of the Hangzhou–Fuzhou–Shenzhen Passenger Dedicated Line (HFSL) in Shenzhen, China, as an example. The opening of the HFSL and its integration into the local metro network at Shenzhen North Station provide exogenous intra-city variations in access to the surrounding economic mass. With a difference-in-differences approach, we find that the HFSL showed a negative local effect as housing values declined by 11.5%–13.3% in the proximity of Shenzhen North Station relative to areas further from the station after the opening, possibly due to the negative externalities of the HFSL. The HFSL effect can spread along the metro network and lead to, on average, a 7% appreciation of housing values around metro stations (network effect). The direction and strength of the network effect vary by metro travel time between Shenzhen North Station and metro stations. Housing values decreased by 7.7% around metro stations within 5–15 minutes of metro travel time but increased by 63.6%, 16.6% and 29.2% around metro stations within 15–25, 25–35 and 35–45 minutes of metro travel time to Shenzhen North Station, respectively. The HFSL effect on housing values diminishes when the rail travel time is above 45 minutes. We interpret these findings as evidence of the redistribution effect in the city related to HSR connection.

A new model for blood supply chain network design in disasters based on hub location approach considering intercity transportation

A new model for blood supply chain network design in disasters based on hub location approach considering intercity transportation

A new model for blood supply chain network design in disasters based on hub location approach considering intercity transportation

A new model for blood supply chain network design in disasters based on hub location approach considering intercity transportation

Surface water quality in the upstream-most megacity of the Yangtze River Basin (Chengdu): 2000–2019 trends, the COVID-19 lockdown effects, and water governance implications

Water is essential for a sustainable economic prosperity, but rapid economic growth and intensive agricultural activities usually cause water pollution. The middle and lower reaches of China’s Yangtze River Basin were urbanized and industrialized much earlier than the upper reach and have been suffering from water pollution. In the past two decades, economic growth accelerated in the upper reach due to several national economic initiatives. Based on analyzing water quality changes from 2000 to 2019 and during the COVID-19 lockdown in 2020 for Chengdu in the upper reach, we hope to provide some water governance suggestions. In 2019, water at 66% of 93 sites in Chengdu did not achieve the national III standards using measurements of 23 water quality parameters. The top two pollutants were total nitrogen (TN) and fecal coliform (FC). From 2000 to 2019, water quality was not significantly improved at the non-background sites of Chengdu's Min Basin, and the pollution in this basin was mainly from local pollutants release. During the same period, water quality deteriorated in Chengdu’s Tuo Basin, where pollution was the result of pollutant discharges in Chengdu in addition to inter-city pollutant transport. During the COVID-19 lockdown, water quality generally improved in the Min Basin but not in the Tuo Basin. A further investigation on which pollution sources were shut down or not during the lockdown can help make pollution reduction targets. Based on the results, we provide suggestions to strengthen inter-jurisdictional and inter-institutional cooperation, water quality monitoring and evaluation, and ecological engineering application.

Temporal instability of truck volume composition on non-truck-involved crash severity using uncorrelated and correlated grouped random parameters binary logit models with space-time variations

With the growing demand for inter-city freight transport, proportion of trucks in the freeway traffic has been increasing in China and worldwide in the past decade. There have been serious safety concerns for the prevalence of truck in freeway traffic given its size and weight, and the interferences of unsafe maneuvers of trucks on other traffic. However, existing literatures mainly focus on the crash severity of truck-involved crashes only. It is rare that the effects of the presence of trucks (of various classes) on the crash severity of non-truck-involved crashes (i.e. not involving any truck) are studied. To account for the effect of unobserved heterogeneity, random parameters discrete outcome models have been deployed to model the crash severity. However, the possible correlations between random parameters are seldom considered. This study aims to investigate the role of the presence and prevalence of trucks of various classes on the severity of non-truck involved crashes, with which both the uncorrelated and correlated panel-level space–time-varying heterogeneities are considered. To account for possible temporal instability, the uncorrelated and correlated grouped random parameters binary logit models are established for each separate year, based on the comprehensive crash and traffic data of eight freeway segments in Shandong of China during the period from 2016 to 2019. 4,008 crashes are extracted and grouped with space (i.e. road segment)-time (i.e. time of the day) variations considered. Results indicate that the proposed correlated grouped random parameters model is superior to the uncorrelated grouped random parameters logit model in three out of the four years. Also, correlation in the heterogeneous effects between super-large truck volume and average speed is significant. Moreover, temporal instability is revealed for majority of the factors, to different extents, including the heterogenous ones and volumes of all truck types. Nevertheless, this study addresses and discusses the fundamental issues of the temporally unstable correlation in unobserved heterogeneity between possible factors in crash severity analysis.

Rajshahi, A pollution free city: Effects of implied elements and battery rickshaw towards a sustainable environment

This paper describes how the city of Rajshahi fought back air pollution through adopting mitigation measures by identifying every possible contributing factors of the pollution. The paper also includes how implementing battery operated rickshaw as a means of intercity transportation impacted the pollution level and contributed towards sustainable environment. The paper covers the details about the problem identification process and the mitigation measures taken by the engineers in the Rajshahi City Corporation. As a result of the steps taken, Rajshahi showed a 67.2% percent decline in concentration of PM10 particles, from 195 micrograms per cubic meter of air volume in 2014 to 64 micrograms for cubic meters. This was the largest percentage reduction in PM10 concentration worldwide. PM2.5 concentration also nearly halved from 70 micrograms per cubic meter to micrograms per cubic meter. The report where this achievement was announced was published by World Health Organization (WHO). By analyzing the discussion it was concluded that Rajshahi was a model city and can be considered as a benchmark and ideal for other cities to follow to reduce air pollution and create a sustainable environment.

Personalized Multimodal Travel Service Design for sustainable intercity transport

Efficient multimodal public transport has been recognized as an effective solution for realizing sustainable intercity transport. However, it has not been well accepted by the general public due to the poor coordination among transport modes, inconvenience caused by transfers, difficulties on route plannings, etc. To address the problem and facilitate the popularity of multimodal intercity travel, this research proposed the design of personalized multimodal travel service based on SPSS (Smart Product Service System). It not only could provide multimodal route recommendations based on individual preferences, but also could improve its performance along usage. Meanwhile, the influencing factors of multimodal intercity travel is investigated, based on which the travel choice model is developed. Besides, a few-short learning method was proposed, which could mine the individual preference even from limited historical travel data. Finally, an experimental case study was conducted that demonstrates the effectiveness of the proposed solution.

Multimodal pricing model in a deficit public transport market: Implication of informal transport

This article explores one of the most important segments of public transport in developing countries, namely informal transport and its relation to the pricing system of public transport. This paper is an extension of the work of Tirachini, A. and Hensher, D.A., who have developed a model to analyze the impact of non-motorized transport on an optimal public transport pricing policy. We are looking at three congested modes of transportation, and we introduce informal transport as an independent mode of transport instead of non-motorized transport in this analysis. Informal transport has never been incorporated into an intercity transport pricing analysis and this is the first one that informal transport has been considered an autonomous mode in a pricing model. We tried to show how the pricing policy would change by considering or ignoring the Informal Transport. We propose three congested modes (Public transport, particular vehicular and informal transport) pricing model that incorporates informal transport and reconstruct the impact of a capacity constraint on optimal public transport prices. Pricing model were developed explaining the first best and second best prices and the changes effects of capacities and frequency of public transport bus.

The greening of intercity travel: Environmental protection subsidy and HSR operation planning

The transportation sector is one of the highest sectors responsible for negative environmental impacts in the cities. It is necessary for the government to inspire the local transportation system to reduce its pollution emissions. Therefore, this article uses the environmental protection subsidy (EPS) to attract passengers to choose green travel. In order to obtain the optimal solution for green transportation, we propose a bi-level multi-objective optimization model based on the collaborative optimization between EPS coefficient and high-speed rail (HSR) operation planning. There are three main game players, namely the government, HSR enterprise, and passengers. We develop a hybrid optimization algorithm to solve the model and verify this proposed methodology by using the Beijing-Tianjin-Hebei intercity transportation network. Our results show that the EPS has a significant impact on intercity travel. As demand increases, the EPS coefficient gradually decreases from 0.85 to 0. HSR's profit growth is higher than the government subsidies.

High-speed rail accessibility and haze pollution in China: A spatial econometrics perspective

With deteriorating air quality in Chinese cities, high-speed rail (HSR) has attracted serious attention as an efficient transportation system to contain haze pollution across the country. This study introduces the concept of HSR accessibility and applies the generalized spatial two-stage least square method to examine the effect of HSR on haze pollution in China. A time-varying difference-in-difference strategy is then employed to recognize the causality from HSR to the haze pollution and eliminate endogeneity. Based on a panel dataset comprising 285 cities over 2010–2018, we find a negative effect of HSR accessibility on haze pollution. An increase of one standard deviation in HSR accessibility reduces PM2.5 concentration by 0.22%. However, the HSR pollution reduction effect varies significantly across cities. It is found that HSR can reduce haze pollution by improving the efficiency of resource allocation as well as promoting industrial structure change and technological innovation. This study proposes a new solution for pollution, i.e., improving urbanization quality through intercity transport efficiency enhancement.

Quantifying the impacts of inter-city transport on air quality in the Yangtze River Delta urban agglomeration, China: Implications for regional cooperative controls of PM2.5 and O3.

The Yangtze River Delta (YRD) urban agglomeration is one of the most developed regions in China. During recent decades, this region has experienced severe regional haze and photochemical smog pollution problems. In this study, we used a source-oriented chemical transport model to quantitatively estimate the effects of inter-city transport on fine particulate matter (PM2.5) and ozone (O3) among the 41 cities in the YRD urban agglomeration during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (May 17 to June 17, 2018). The results show that inter-city transport is very significant in the YRD region. On average, the emissions from the local city, the other YRD cities, and the regions outside of the YRD contribute 25.3%, 49.9%, and 24.8% to the PM2.5, respectively, and they contribute 33.7%, 46.8%, and 19.5% of the non-background O3, respectively. On PM2.5 or O3 pollution days, the transport contribution from the non-local YRD cities becomes much more important, while the local emissions and the transport from non-YRD emissions become less important. The results also suggest that the cities within a distance of 184km and 94km contribute 60% of the PM2.5 and O3, respectively. Therefore, we recommend that regional cooperative control programs in the YRD consider emission controls over cities within these ranges. The range for primary PM2.5 (92km) is very different from that for secondary PM2.5 (515km). Cooperative emission controls of SO2 and NOx on a much larger regional scale are required to reduce the secondary PM2.5 in the YRD.

Dynamic governance decisions on multi-modal inter-city travel during a large-scale epidemic spreading

Within half a year, COVID-19 spreads to most countries in the world, as well as posed a great threat to the public health of human beings. The implementation of non-pharmaceutical intervention (NPI), including travel ban, proved to be an effective way for controlling the epidemic spreading, e.g., the ban of inter-city transportation stops transporting virus through passengers between cities. However, travel ban could significantly impact many industries, e.g. tourism and logistics, thus jeopardizing the regional economy. This paper focus on assisting the national or regional government to make dynamic decisions on restricting and recovering intercity multi-modal travel services. Our model can characterize impacts of inter-city traffic on the spread of the COVID-19, as well as on the regional economy. By applying a reinforcement learning approach, we develop an online optimization model to identify the modal-specific travel banning strategy that can balance the epidemic control as well as the negative impacts on regional economy. The numerical study based on a network of multiple cities in China shows that the proposed approach can generate better strategies compared with some existing methods.

Potential trend discovery for highway drivers on spatio‐temporal data

Inter-city transportation plays an important role in modern cities, and has accumulated massive spatio-temporal data from various sensors by IoT (Internet of things) technologies. Travel characteristics and future trends of highway behind data are valuable for traffic guidance and personalized service. As a routine domain analysis, trend discovery for highway drivers faces challenges in processing efficiency and predictive accuracy. Insufficient profiles of those drivers are available directly, sensible executive latency on huge data is hard to guarantee, and inadequate features among spatio-temporal correlations hinder the analytical accuracy. In this paper, a travel-characteristic based method is proposed to discover the potential trend of payment identity for highway drivers. Considering time, space, subjective preference and objective property, travel characteristics are modeled on monthly data from highway toll stations, through which predictive errors can be reduced by gradient boosting classification. With real-world data of one Chinese provincial highway network, extensive experiments and case studies show that our method has second-level executive latency with more than 85% F1-score for trend discovery.

Produtos florestais nativos, legalizados e comercializados no Rio Grande do Norte

Dados do sistema DOF (Documento de Origem Florestal), gerados no período de 2011 a 2016, foram analisados para identificar e quantificar os produtos florestais nativos legalizados, comercializados e transportados no estado do Rio Grande do Norte (RN), Brasil. Esses dados foram levantados junto ao Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (Ibama) e correspondem ao transporte de produtos florestais de origem nativa que têm como destino final os municípios do RN. Entre 2011 e 2016, o RN recebeu produtos madeireiros de 24 estados do país. O número de DOFs originários do RN teve crescimento médio de 22%, entre 2011 e 2014, e redução de 13%, entre 2015 e 2016, tendo-se observado a comercialização e o transporte intermunicipal em mais de 90% dos municípios. Houve a movimentação de 738 diferentes espécies transportadas, destacam-se o angelim-vermelho (Dinizia excelsa), a maçaranduba (Manilkara spp.) e o jatobá (Hymenaea spp.). Os principais produtos transportados foram: madeira serrada, lenha e resíduos de madeira. A análise dos DOFs mostra que houve avanços no monitoramento de produtos nativos comercializados e que a maioria dos produtos comercializados e transportados no RN são originários dos estados da região Norte.

A Review on Hyper loop Transport Technology

The purpose of this review is to explore on Hyperloop technology as is used in railway transportation. For the many years’ railways have been playing a significant role in mass passenger and freight transport. In the modern daily travel environment (commuter), railways face new challenges from different perspectives. For example, urban railways always focus on how to minimize the vibration and noise from trams, subways and light rail vehicles on the environment. Intercity transport must focus on how to achieve higher speeds as well as eliminating noise and vibration so as to minimize travel time and even achieve the potential of diverting passengers from air traffic and decreasing exhaust pollution in the atmosphere. Lastly, urban transport and intercity transport must all develop strategies to achieve better economic values regardless of what type of transport is used. Facing future demands and challenges, hyper loop trains provide a new option. It provides contactless operation on wheel/rail systems.

ЛОГИСТИЧЕСКИЙ ПОДХОД К ОПТИМИЗАЦИИ МАРШРУТНОЙ СЕТИ РЕГИОНА

The article presents the author's approach to the pre-project analysis of the passenger service schemes on suburban, intercity and international road transport. Studies on the directions and volume of traffic were carried out in several Urals cities. A bus traffic model from federal and regional roads to the bus station down the city's road network has been developed. The article presents the algorithm for conducting a study of the bus traffic order from the bus station down the big city’s network of roads. The fundamental principles of the logistics approach to optimizing the region route network were established.

Modeling the morphology of the intercity road network

Many aspects of the functioning of the transport network and its impact on the socioeconomic development of a territory significantly depend on its morphology. In particular, the morphological features of the network underlie the network effects, which can lead to significant changes in transport costs (both downward and upward) with minor modifications to the network. The article analyzes the factors most significant for the morphology of the intercity transport network and presents a mathematical description of the mechanisms for the realization of their influence. It is shown that the key factor is the location of network vertices in space, and a two-parameter family of models is proposed that can generate networks close to real ones, only based on information about the spatial location of their vertices. Implementation of the proposed model is demonstrated using the intercity highway network in Belarus. For this network, the optimal parameter values were selected, and it was shown that the resulting model is quite close to the original network.

Effects of the mandibular advancement device on daytime sleepiness, quality of life and polysomnographic profile of public transport drivers with obstructive sleep apnea syndrome.

ObjectiveTo evaluate the effects of the mandibular advancement device (MAD) on daytime sleepiness, quality of life (QoL) and polysomnographic profile of intercity transport drivers with obstructive sleep apnea syndrome (OSAS).Material and MethodsA quasi-experimental study evaluating intercity transport drivers from March to September 2019. The apnea-hypopnea index (AHI) was evaluated by type III polysomnography, which defined the severity of the disease. OSAS: mild (5 to 15), moderate (15 to 29), or severe (= 30). Sleepiness was assessed using the Epworth sleepiness scale, consisting of 8 questions about the likelihood of drowsiness in daily situations. QoL was assessed using the SF-36 questionnaire, which provides the score in eight domains: functional capacity, physical aspects, pain, general health status, vitality, social aspects, emotional aspects, and mental health. Drivers with OSAS underwent intervention with application of personalized MAD for 8 to 12 weeks.ResultsThe total sample (n=23) (44.77±11.56 years) had a body mass index (BMI) of 30.64±4.66kg/m2, and an OSAS prevalence of 65.2% of drivers (n=15). There were losses of 4 drivers so that the final sample of drivers with OSAS for the intervention with the MAD was 11 individuals, with an average age of 45.54±9.41 years and BMI of 32.21±3.17kg/m². There was a decrease in AHI (28.51±15.66ev/h 012.11±6.70ev/h, p=0.002) and pain (60 (50-60)040 (40-50), p=0.015) after the intervention.ConclusionThere was a reduction in AHI in intercity transport drivers after implementing the MAD procedure.

Двухуровневая модель информационного взаимодействия участников транспортного рынка

Effective organization of intercity transportation largely depends on optimization of the operational search for cargo for the transit component of the route. Carriers have the opportunity to get additional income with minimal additional costs, and transport customers get the opportunity to transport at minimum tariffs. Information interaction systems of transport market participants are used for rapid search of goods and transport. Automation of the processes of information interaction of transport market participants will significantly increase the efficiency of such information systems [1, 2]. A two-level model of information interaction is proposed, which at the first level considers the interaction «carrier-customer», and at the second one operational interaction at the level «transport-cargo». This approach allows you to automate the formation of pairs not only taking into account the technological compatibility of the cargo (application for transportation) and the vehicle, but also taking into account such non-technological parameters as reliability, payment terms, the tax system used. Based on the proposed two-level model, a modified algorithm of the minimum concessions method is proposed. Preservation of stability of pairs when using this algorithm is justified. Based on formation of a data set of actions (decisions) of customer managers and carriers, it is possible to form neural networks that minimize routine actions in the interregional transportation market and increase efficiency of information interaction.