Road Supply Research Articles

Urban Traffic Light Control via Active Multi-Agent Communication and Supply-Demand Modeling

Urban traffic light control is an important and challenging real-world problem. By regarding intersections as agents, most of the reinforcement learning-based methods generate agents’ actions independently. They can cause action conflict and result in overflow or road resource waste in adjacent intersections. Recently, some collaborative methods have alleviated the above problems by extending the observable surroundings of agents, which can be considered inactive cross-agent communication methods. However, when agents act synchronously in these works, the perceived action value is biased, and the information exchanged is insufficient. In this work, we first propose a novel Multi-agent Communication and Action Rectification (MaCAR) framework. It enables active communication between agents by considering the impact of synchronous actions of agents. Another fundamental problem of traffic light control is the balance between traffic demand and road supply capacity. To fully describe the relation between traffic demand and road supply capacity (Supply-Demand modeling, SD), we further model and forecast the Supply-Demand relation to facilitating the effectiveness of the model’s action. The experiments show that our model outperforms state-of-the-art methods on both synthetic and real-world datasets. Combining the SD with MaCAR, SD-MaCAR can further boost the traffic light control performance even in traffic accident scenarios.

국가 지속가능발전목표(K-SDGs)의 시너지 및 상충 관계 분석 : 목표 15(육상 생태계 보전)를 중심으로

South Korea developed Korean Sustainable Development Goals (K-SDGs) to achieve Sustainable Development Goals (SDGs). According to the Sustainable Development Report 2021, South Korea’s performance index of Goal 15 (Life on Land) reflected a decreasing trend. Yet, since the SDGs are all interlinked, implementation strategies should be developed based on their interlinkages. This study aims to suggest forest policies to enhance synergies and reduce trade-offs between K-SDG Goal 15 (Life on Land) and other goals by analyzing the interactions of indicators of Goal 15 (Life on Land) and those of other goals. We surveyed 36 forestry scientists from government research institutes to evaluate the interlinkages. The results show that 115 of 128 indicators have synergy with K-SDG 15 (Life on Land). Among them, indicators 2.2.1 (Farm Household Income), 9.1.1 (Road Supply Rate), 7.2.2 (Share of New • Renewable Energy over Primary Energy), and 11.1.2 (Expansion of Housing Supply) revealed relatively strong trade-offs. We suggested different approaches to mitigate trade-offs such as policies to include forest roads in road expansion plans and to create green spaces in urban development plans. On the other hand, most of the indicators of Goals 7 (Clean Energy), 11 (Sustainable Cities), and 13 (Climate Action) showed synergistic effects. We emphasized sustainable forest management and other policies to enhance the value of forests. In sum, goals are designed to maintain the balance between conserving the environment and development. Thus, we should take account of measures to develop sustainably and to preserve the environment.

Dynamic Wireless Charging for Inductive Power Transfer Systems in Electric Vehicles

The charging plate creates magnetic fluxing. The charging plate and the adjacent coil can induce current without any contact. By the new trends, wireless charging got more social attention to the outside world as an alternative method for primitive wired charging. Even though wireless charging was implemented to various electronics industries, it is still proven that wired charging is faster than the wireless. But can make the gadget hot, which may not be good for the battery efficiency. The wireless charging does not degrade the battery. A vehicle that is powered by an electric motor rather than a typical petrol or diesel engine is referred to as an electric vehicle. The electric motor is powered by rechargeable batteries. In this article, the dynamic wireless charging of electric vehicles introduces a new methodology of charging even when the vehicle is in motion. The dynamic wireless charging is proposed to allow power transfer to the electric vehicles when they are in motion. Multiple inductive pads should be buried under the roadways. The inductive pads should be energized by a power supply. The track which is dedicated for the wireless charging should have enough distance so that the vehicles can charge up to a stable value until they leave the charging track. This proposed methodology reduces unnecessary time wastage for charging of vehicles. Hardware results obtained the primary pads mounted on road and power supply for primary roads. Besides, it will flow the efficient inductive power transfer and time saving opportunity.

Modelling the road network capacity considering residual queues and connected automated vehicles

This paper investigates the network capacity considering residual queues and connected automated vehicles. First, the weighted network outflow is introduced to measure the network capacity. Then, two bilevel models are built to calculate the network capacity with residual queues under the user equilibrium (UE) principle and the system optimum (SO) principle, respectively. The UE-based network capacity model is employed to estimate the capacity of the dedicated road network for human-driven vehicles (HVs), while the SO-based network capacity model is employed to estimate the capacity of the dedicated road network for connected automated vehicles (CAVs). Furthermore, by combining the two proposed network capacity models, a model to allocate link capacity between CAV lanes and HV lanes to maximise the whole network capacity is presented, in which the CAV travellers’choice behaviour of driving modes is considered. Finally, through two numerical examples, the characteristics of the proposed models are demonstrated and their potential applications are discussed. The results show that the proposed models are capable of 1) identifying critical links and potential critical links of networks, 2) guiding the land-use development and macroscopic travel demand management, 3) evaluating network optimisation schemes, and 4) allocating the road supply to CAVs and HVs efficiently.

How do low-income commuters get to work in US and Mexican cities? A comparative empirical assessment

This paper applies multinomial logit models to examine how metropolitan urban form, housing type and socioeconomic factors covary with individuals’ commute mode choice for 1.2 million low-income workers in the USA and Mexico. Comparing the commute patterns of low-income households across the USA–Mexico border sheds light on the consistency of estimated relationships across global contexts and the likely transferability of transportation and land use policies from the Global North to the Global South. We find many common relationships on each side of the border, despite substantial socioeconomic and urban differences. For example, wealthier and better-educated low-income workers in low-density metropolitan areas with substantial road supply are more likely to drive to work and less likely to use active modes. We also find some considerable differences between the magnitude and even direction of associations between predictor variables and commuter mode choice. In terms of public policy, efforts to reduce driving or promote compact development are more likely to reduce driving and more likely to be pro-poor in Mexico than in the USA. In Mexico, just 13% of low-income workers commute by car and dense urban form is relatively strongly associated with increases in transit, non-motorised modes and working at home. High rates of driving and auto-oriented urban form make policies to reduce driving particularly likely to be regressive in most US metropolitan areas.

PRELIMINARY ANALYSIS ON THE SUCCESS OF COMMUNITY-BASED COMMUNITY ROAD PROGRAM RELATED TO COMMUNITY CHARACTERISTICS, IN PASURUAN CITY

As a developing country, Indonesia still has a lot of urban slum areas. Ministry of Public Works and Public Housing create the KOTAKU program, City without Slum. To realize the KOTAKU objective, two projects were conducted the NSUP and the NUSP. Pasuruan City was given the NUSP-2 project, in 2016, covered 11 slum areas, dealt with community road, community sanitation, and community water supply. The success of the community road program had been evaluated. The program was relatively unsuccessful in a coastal area dominated by fisherman settlement. In the next to the coastal area dominated by supporting fishermen supporting an activity, the program was relatively fairly successful. While in urban slum areas dominated by middle-income families, the program was successful.

Coupling Natural Hazard Estimates with Road Network Analysis to Assess Vulnerability and Risk: Case Study of Freetown (Sierra Leone)

Many of the world’s most disaster-prone cities are also the most difficult to model and plan. Their high vulnerability to natural hazards is often defined by low levels of economic resources, data scarcity, and limited professional expertise. As the frequency and severity of natural disasters threaten to increase with climate change, and as cities sprawl and densify in hazardous areas, better decision-making tools are needed to mitigate the effects of near- and long-term extreme events. We use mostly public data from landslide and flooding events in 2017 in Freetown, Sierra Leone to simulate the events’ impact on transportation infrastructure and continue to simulate alternative high-risk disasters. From this, we propose a replicable framework that combines natural hazard estimates with road network vulnerability analysis for data-scarce environments. Freetown’s most central road intersections and transects are identified, particularly those that are both prone to serviceability loss due to natural hazard and whose disruption would cause the most severe immediate consequences on the entire road supply in terms of connectivity. Variations in possible road use are also tested in areas with potential road improvements, pointing to opportunities to harden infrastructure or reinforce redundancy in strategic transects of the road network. This method furthers network science’s contributions to transportation resilience under hydrometeorological hazard and climate change threats with the goal of informing investments and improving decision-making on transportation infrastructure in data-scarce environments.

Private road supply in networks with heterogeneous users

We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. There are two parallel links for one origin and destination pair and two groups of travellers, where the group with the higher value of time also has higher schedule delay values. Previous scholars argued that as users become more heterogeneous, they benefit more from product differentiation, making private supply of roads more efficient. However, we find that local monopoly power might also increase if there is a ‘separating equilibrium’, which is an equilibrium where at least one group only uses one private road due to the different combinations of toll and congestion of the two roads. The private road can thus increase its toll without worrying about the competition from the other road for this group: it has a local monopoly over them. This lowers the efficiency of private supply. The problem is especially severe with flat tolls, which are constant over the peak. With fine tolls – which vary continuously over the day – there tends to be a pooling equilibrium – where both types use both roads – and competition remains intense. Flat tolling is also worse for users than fine tolling, as it has higher generalized prices.

Impact of Major Road Supply on Individual Travel Time Expenditure: An Exploration with a 30-Year Variation of Infrastructure and Travel

This study estimates the impact of major road supply on individual travel time expenditures (TTEs) using data that cover 30-year variations in transportation infrastructure and travel behavior. The impacts of the supply of road and rail infrastructure are estimated with a data set that combines records of large-scale household travel surveys in the Tokyo metropolitan area conducted in 1978, 1988, 1998, and 2008. Linear and Tobit models of individual TTEs are estimated by following the behavior of birth cohorts over the 30-year period. The models incorporate the changes in transportation infrastructure, measured as lane kilometers of two levels of major road stock and vehicle kilometers of urban rail service. The results show significant negative effects of lane kilometers for higher-level and lower-level major roads on the TTEs for all travel purposes and for commuting, after controlling for socioeconomic backgrounds and generations of individuals. This study discusses that, in Tokyo, the estimated effect is more likely to reflect the effect of a major road network per se on individual TTEs than the (indirect) effect of major road supply on individual TTEs working through land development activities (i.e., induced car travel demand). For example, the caveat is that actual road investment decisions still need to consider the induced component of road traffic in addition to the (direct) effect that is estimated in this study.

Demand imbalances and multi-period public transport supply

This paper investigates multi-period public transport supply, i.e. networks in which capacity cannot be differentiated between links and time periods facing independent but nonidentical demand conditions. This setting is particularly relevant in public transport, as earlier findings on multi-period road supply cannot be applied when the user cost function, defined as the sum of waiting time and crowding costs, is nonhomogeneous. The presence of temporal, spatial and directional demand imbalances is unavoidable in a public transport network. It is not obvious, however, how the magnitude of demand imbalances may affect its economic and financial performance. We show in a simple back-haul setting with elastic demand, controlling for total willingness to pay in the network, that asymmetries in market size reduce the attainable social surplus of a service, while variety in maximum willingness to pay leads to higher aggregate social surplus and lower subsidy under efficient pricing. The analysis of multi-period supply sheds light on the relationship between urban structure, daily activity patterns, and public transport performance.

Does This Road Go on Forever? Modelling Sustainability of Infrastructure in Developing Countries

There are not enough roads in developing countries but it is not for a lack of spending to address this shortfall. Multilateral and bilateral development agencies have invested billions of dollars to build up new transportation networks because the shortage of road supply constrains trade and economic growth. However, these new roads often do not last as long as initially anticipated so many of the same donors worry that governments will not provide sufficient maintenance of these investments. In turn, economists suggest that weak maintenance performance may be due to low institutional capacity in the recipient country or even a lack of budgetary funds—both easy fixes that warrant an optimal benefit stream according to their economic rate of return in HDM4 models (“ERR”). However, these maintenance reforms have had mixed results which we argue is the result of a deeply entrenched institutional concern that requires intricate analysis and project-tailored reform approaches to remedy. Even then, these reforms may not exhibit incremental benefits for an ERR. In sum, ERR models of roads should include a rigorous political economy analysis as a due diligence prerequisite in order to substantiate any included assumptions of maintenance reforms resulting from a donor project.

Marginal congestion costs in the case of multi-class traffic: A macroscopic assessment for the Paris Region

Although road congestion caused by freight activities is often pointed-out by researchers and public deciders as a major issue, few studies model time losses at a macroscopic-regional level within a “multi-class traffic” framework. This research proposes such empirical assessment for the Paris region, using a simple method based on individuals' trip durations. We combine information on passengers and commercial transport (to describe road demand) with a GIS describing the stock of infrastructures (road supply) on that territory.According to econometric results, the travel times react differently to the flow of similar and dissimilar vehicles: Cars and vans are more impacted than trucks by the volume of “small” vehicles, whereas “large” vehicles are more affected than cars and vans by the presence of other large vehicles. Our methodology thus highlights varying and reciprocal congestion impacts, which is not common in the literature. We then propose various marginal congestion costs, for various origin-destination pairs, various time periods and various types of vehicles. In particular, we decompose external losses incurred to each category of vehicles by each category of vehicles. These results constitute valuable materials for future appraisals of transport policies in the Paris region.

Private Road Supply in Networks with Heterogeneous Users

We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. There are two parallel links for one origin and destination pair and two groups of travellers, where the group with a higher value of time also has higher schedule delay value. Previous scholars argued that as users become more heterogeneous, they benefit more from product differentiation, making private supply of roads more efficient. However, we find that local monopoly power might also increase. This may occur if one group prefers one road over the other as the two offer different combinations of toll and travel delay. The private supplier can thus increase the toll on its link without worrying that the targeted travellers will move to the other link. This can undermine the efficiency of private supply of roads. The problem is especially severe with flat tolls. With queue-eliminating tolls, both types tend to travel on both roads, and competition remains relatively intense. Flat tolling is always worse for users than time-variant tolling as it has the higher generalized prices, and it also leads to a lower welfare.

Understanding congested travel in urban areas.

Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.

Commercial Road Supply with Incentive Regulation

Price regulation to limit monopoly charging by a commercial road supplier prevents full transfer from users to the supplier of marginal benefits from investing and maintaining to improve service quality. Marginal revenue from quality improvements falls short of marginal social benefit leading to underprovision. A form of incentive regulation is proposed that ensures full benefit transfer. Out of revenues raised from users, the regulator pays the supplier a shadow toll that varies with the level of service quality as measured by users’ average generalized costs. Under the assumptions of the model, profit-maximizing and economically efficient investment and maintenance outcomes align.

Evaluating the modal split of overland transportation of general cargo in Brazil using a market share model

This paper presents a methodology developed to evaluate the modal split of land transport of general cargo in Brazil and possible reasons for the prevalence of road transport over rail, using a market share model. No studies were found using the market share model for planning cargo transport, in spite of its generic nature which makes it readily applicable to any market, service, utility or commodity. The methodology was applied in three transport corridors, two groups of general cargo and enabled us to establish that Brazilian rail operations are still uncompetitive in terms of logistics costs when transporting general cargo of high aggregate value. Moreover, transport supply is a determinant factor for the greater use of road transport in Brazil's general cargo transport matrix, and the demand for general cargo transport in Brazil is elastic in relation to this factor. For low aggregate value general cargo (AV1), a 1% reduction in the gap between road and railway supply leads to an increase in the railway market share of 4.5% through TC1 (São Paulo -Porto Alegre -São Paulo), 4.9% through TC2 (Santos -Brasilia -Santos), and 3.3% through TC3(São Paulo -Rio de Janeiro -São Paulo). For high aggregate value general cargo (AV2), this elasticity was more pronounced. A 1% reduction in the gap between road and railway transport supply leads to an increase in the railway market share of 4.2% through TC1, 11.9% through TC2, and 9.6% through TC3.

Analysis and Optimization of Hangzhou East Area Traffic Based on the Congestion Index Detection Platform

With the rapid development of urbanization in China and the motorization’s fast pace of high speed as well as the national automobile industry process, many cities in our country have been facing a huge problem - traffic congestion in recent years. And the essence of the problem is the imbalance between road traffic supply and traffic demand in the process of urban development. Aimed at the problem of traffic congestion, this paper based on Hangzhou city’s traffic congestion index of monitoring data from testing platform and statistical data from field survey , studied the Hangzhou east area of road traffic running situation, analyzed the causes of the east area of Hangzhou road congestion, and thus to adjust and optimize the road traffic system of the area, put forward reasonable system solutions and proposals to improve the management level

Road Supply in Central London: Addition of an Ignored Social Cost

Studies examining the social cost of driving usually ignore the opportunity cost of having roads in place: the associated land rents. Especially for geographic regions where land is valuable, including the rent costs may even lead governments to close some roads. By using the London congestion charging zone case, a more general long-run social cost curve is calculated with the addition of the rents. Based on the optimal road usage concept, this study found that including the rents in the cost/benefit analysis significantly affects the results and can increase the social cost by up to 200% and decrease the optimal road usage by 40%.

2A2-P04 空気圧駆動式イモムシ型管内走行ロボットの力学的解析(特殊移動ロボット(2))

Nowadays, pipes buried under a road supply houses with water and town gas. Pipes must be periodically inspected in order to prevent the accident caused by leakage of fluid in pipes. We have proposed inspecting pipes using by green caterpillar type in-pipe mobile robot. The robot is structured by three somites and four suction brakes. The somites imitates the waving motion, and the suction brake imitates the proleg of the green caterpillar. The somites movement and the act of clinging to pipe all using by suction brakes uses pneumatic pressure. The pneumatic pressure is feeded to the robot from air comprresor and vacuum pomps through air feeding tubes. Now, we derive equilibrium of forces using by dynamics models of moving robot. As a result, we can predict traction force of the robot.

Reducing Car Use in Canberra: A Holistic Policy Approach

Reducing car use allows cities to lower greenhouse gas emissions and improve population health and social welfare. Car use can be made less attractive by making driving less convenient, making other modes of transport more convenient, and by nudging people into reconsidering their habits where driving has become impractical. A mixture of all three options is optimal, and most effective with people who are open to changing their behaviour. With transport playing a complex role in everyday life, a holistic approach to its use is essential. The Australian Capital Territory (ACT) Government has sound aims regarding sustainable transport, but its Transport for Canberra: Transport for a sustainable city 2012–2031 report published in 2012 contains some contradictions and inefficiencies in the effort to shift Canberra’s population away from driving as a default travel mode. The lack of evidence-based public transport plans and behaviour change programs will weaken Canberra’s efforts, and the failure to reduce road supply will oppose them. The ACT Government has failed to fully seize the opportunity to reduce car use and hence improve population health and social welfare.