Road Transport Modes Research Articles

Comparative Analysis of Gini Coefficient, GDP, Energy Consumption, and Transportation Modes on CO2 Using NARDL (Nonlinear Distributed Lag Autoregressive Model) for the USA

The significance of the transportation sector, notably in terms of the carbon emission factor, is an undeniable fact. Along with this fact, individuals’ transportation preferences depend on their income levels. In this context, when the issue is considered, the income level in the USA pushes people toward cheap air travel. The main reason for this is that it is cheap, accessible, and transports one to their destinations quickly. Thus, from the perspective of road transportation, bus transportation is popular among the public. The reason why both air and road transportation modes are empirically evaluated together through income distribution is due to the preference of the US people. In this context, the effectiveness of active transportation on both air and highways in the USA from 1975 to 2023 is investigated by taking into consideration the income distribution. Empirical findings obtained through the FMOLS, DOLS, CCR, and NARDL models demonstrate that all independent variables, including GDP, energy use, air transportation, and the Gini coefficient, affect carbon dioxide emissions. In addition, wavelet analysis is performed to comprehend the form of and fluctuations in the series, which are vital to monitoring the periodical changes.

Does the type of transportation mode matter in the effect of freight transportation on the environmental pollution of OECD countries?

This study aims forward to explain the effect of freight transportation on environmental pollution and to investigate the role played by the usage rates of road and railway transportation modes in this relationship. As an auxiliary problem of the research, it was tried to determine whether there is a threshold value for these types of transportation and what consequences will arise in terms of environmental pollution below and above this threshold. For this purpose, the data of OECD countries for the period 2000-2018 were analyzed with the PSTR method. Analysis results showed a non-linear relationship between freight transportation and environmental pollution and that the road/rail transportation ratio plays an important role in this relationship. The determined threshold value is 68.18% for road freight transport and 29.55% for rail freight transport. Below the determined threshold values, as the amount of cargo transported increases, the rate of carbon emission increase gradually increases in both types of transport. Above the threshold values, road transport increases the rate of increase even more, while rail transport decreases this rate of increase. Within the scope of these results, countries should develop policies to increase the use of railways in freight transport while reducing the use of roads.

Toward A Comprehensive Framework for Accessibility Measures for Movement-Challenged Persons

Access is one of the most important rights for persons with disabilities (PWDs), particularly for movement-challenged persons (MCPs). To adopt appropriate policy measures that ensure this right for MCPs, it is necessary to evaluate accessibility appropriately. There are, however, very few accessibility measures applicable to MCPs. The current study proposes a framework for a novel comprehensive accessibility measure for MCPs (CAMMCP) by integrating parameters of universal design and the impact of mode-specific challenges faced by MCPs with existing accessibility measures following an origin-to-destination approach. The study presents a literature review of existing accessibility measures and suggests approaches to modify measures to suit mobility challenges faced by MCPs. Modified accessibility measures have been integrated with other parameters related to universal design and mode-specific problems. Universal-design-related parameters will include ramp slope and curb cuts, which can be measured through physical survey. Information on the impact of mode-specific challenges to MCP accessibility can be collected through questionnaires and participatory survey methods. The study also suggests approaches to modifying existing accessibility measures that do not differentiate between mobility constraints for MCPs and non-MCPs when evaluating accessibility. CAMMCP will be helpful for transportation policymakers taking the initiative to improve built-environment accessibility for MCPs as well as for evaluating projects through the lens of transport equity. It can be particularly helpful in determining walkability and transit-service accessibility. Hopefully, it will help build better road networks and transportation modes to develop a sustainable and inclusive transportation system.

Shapley value cost allocation model for multimodal freight transport carriers

The downstream petroleum products distribution is beset with significant challenges due to ageing pipeline infrastructure, pipeline vandalism and other logistical constraints. These challenges have given rise to soaring pump prices of premium motor spirit (PMS), product shortages and unavailability across some locations in Nigeria. Thus, deploying alternative transport modes for PMS distribution is explored to improve product distribution efficiency. The decision to combine inland waterway transport (instead of pipeline network) and road transport modes would activate the intrinsic advantages inherent in the multimodal transport system. However, the efficiency outcome of using multi-modes may be eroded if the multimodal transport operators compete (instead of collaborating) in service provisions. This research investigated cost efficiency in cooperative collaboration among multimodal transport carriers. We proposed collaboration among six multimodal transport operators. The aim of encouraging such a large-scale coalition (S) is the expectation that costs emanating from their joint operation would be reduced. We applied the Shapley value cost allocation method to distribute the costs of operation and profit to the collaborators. After the analysis, we observed that the unit cost for coalition S1 was reduced by N17.16 (5.10 %) million naira. Similarly, we observed respective reductions in unit costs for coalitions S2, …, S10. We observed a reduction in cost by N107.84 million naira, which represents a 6.15 % reduction in total unit cost for the multimodal transportation carriers. Thus, the observed cost efficiency represents savings due to distribution chain efficiency if the multimodal transport carriers collaborate to improve product availability. Working as a coalition would offset PMS pump price variation attributable to distribution chain inefficiency.

Pass-through of oil prices to Brazilian inflation: An analysis between 2014 and 2023

ABSTRACT The price of fuels, and consequently, the price of oil, is one of the elements of historical relevance for the general price level that the Brazilian population faces, given the country’s dependency on the road transportation mode for product distribution and the potential ripple effects that the oil price naturally exerts on other sectors of the economy. Therefore, the aim of the present study is to quantify the influence of oil prices on the overall price index of the Brazilian economy for the period between January 2014 and May 2023. To achieve this objective, a model based on a hybrid New Keynesian Phillips curve was constructed, and the estimation was performed using Structural Vector Error Correction (SVEC) models. As a result, we find that, although oil prices are not the most significant drivers of inflation, their influence is present, positive, and persists for a considerable number of periods.

Future Trends: Predicting the Evolution of Rail and Road Transportation in Logistics

The logistics industry represents the vital circulatory system of the global economy, responsible for the efficient movement of goods across sprawling supply chain networks. Historically, rail and road transportation modes have been the workhorses of logistics operations, facilitated by their extensive infrastructure and versatility in cargo handling. However, the convergence of rapid technological advancements, evolving consumer expectations, and mounting environmental pressures is catalyzing a transformative shift in the future evolution of these pivotal transportation sectors. This comprehensive study delves into the emerging trends that are poised to reshape the rail and road transportation landscape within the logistics realm. By synthesizing insights from industry leaders, academic research, and cutting-edge technological developments, the study aims to provide a holistic perspective on the forthcoming changes and their far-reaching implications. The study’s main objective is to integrate semi-autonomous and autonomous cars into fleets of transportation vehicles. The advent of self-driving trucks and trains promises to revolutionize logistics operations by enhancing efficiency, reducing human error, and optimizing route planning. Concurrently, this transition raises critical concerns related to workforce displacement, regulatory frameworks, and cybersecurity vulnerabilities that necessitate proactive mitigation strategies. Moreover, the logistics industry faces mounting pressure to embrace sustainable practices and curtail its environmental footprint. Consequently, the rail sector is anticipated to experience a renaissance fueled by its inherent energy efficiency and lower carbon emissions compared to road transportation. Innovations in electric and hydrogen-powered locomotives, coupled with advancements in rail infrastructure, could position rail as a greener and more cost-effective solution for long-haul freight movement. Concurrently, the road transportation sector is poised for a transformation driven by the proliferation of electric and alternative fuel vehicles. This adoption is projected to accelerate as battery technology improves, charging infrastructure expands, and governments implement stricter emissions regulations. Furthermore, the integration of advanced telematics systems and realtime data analytics could optimize route planning, load management, and vehicle maintenance, further enhancing the operational efficiency of road-based logistics.

Automatic Drawbridge Scheduling by Integrating Highway and Waterway Traffic Flow Information

As inland waterway usage intensifies, it increasingly intersects and conflicts with railway and road transportation modes, highlighting the need for efficient management of these critical junctures. In particular, movable bridges represent a key intersection of highway and waterway Traffic but also a potential source of conflict. This paper proposes and analyzes the use of automatic schedulers that consider both highway and waterway Traffic, reduce conflicts, and make key decisions about bridge use. The METANET macroscopic Traffic model is elaborated to allow the simulation of drawbridge openings on the highway mainline, based on the modelling of mainstream metering. Several MPC-based schedulers are proposed using the designed highway Traffic model and key vessel information, aiming to study the impact of the bridge opening and scheduling on highway Traffic. The simulation results indicate a significant reduction in Traffic conflicts at drawbridge intersections due to the implementation of these schedulers. The functioning of the schedulers is shown to be robust and demonstrate verifiable behavior, indicating their high potential in real-world applications.

Opportunities for Multimodal Transport Development to Promote a Sustainable Environment

The rapidly growing global production and trade increase the demand for transport and logistics, leading to the establishment of increasingly more new companies providing these services. This also results in a much larger number of vehicles, which is not always a positive thing. Excessive vehicle traffic leads to an increase in environmental pollution, noise and traffic accidents, which have a highly negative impact on society and, more specifically, on human health. The negative impact on the environment has been increasing, and therefore representatives of national politics, the transport and logistics sectors should be alarmed and take action to reduce the environmental pollution. The development of the transport system should be carefully planned and geared towards achieving green and sustainable transport. In order to create a sustainable freight transport network, certain alternatives that could help to stop or at least reduce the process of environmental pollution should be pursued. One of such alternatives is the use of multimodal transport, which involves several different modes of transport for transporting one freight. This both distributes and reduces the burden on the currently dominant road transport mode, which contributes significantly to environmental pollution and is not sufficiently sustainable.

ASYMMETRIC IMPACT OF DIFFERENT TYPES OF ROAD TRANSPORT ON ECONOMIC GROWTH IN THE SEHRADEGROUP COUNTRIES: AN EMPIRICAL ANALYSIS OF THE NARDL FRAMEWORK

The contemporary economy depends on an effective transportation system, and road haulage assumes a crucial function in fostering dynamic economic growth and commerce. This article aims to investigate the influence of various road transportation modes on economic growth in the Visegrad countries. In this study, the nonlinear autoregressive distributed lag (NARDL) model was employed to scrutinize the asymmetrical impact of various transport modes on GDP. We used quarterly data from 2004–2021 for the Visegrad countries. In addition, a Toda-Yamamoto test was performed to establish causality between variables. The study found evidence of differing impacts of transport modes on economic growth in the examined countries. Specifically, international, and cross-trade transport had a balanced effect on GDP growth, whereas cabotage and domestic transport had an imbalanced impact. The Toda-Yamamoto method's causality analysis results demonstrate bidirectional causality between freight work and GDP in both international and domestic transportation for the Czech Republic, Poland, and Poland's cross-trade. On the other hand, unidirectional causality was established for cross-trade in Hungary, Slovakia, and the Czech Republic. Based on the conducted estimation, it was deduced that the impact of specific transport modes on economic growth is uneven and reliant on both the transport mode and the country. The significant results obtained hold critical implications for economic policy, enabling the adaptation of strategies and regulations to foster growth based on variances in the influence of road transportation on the economy.

Development of AI-Augmented optimization technique for analysis & prediction of modal mix in road transportation.

Transport sector contribution to global emissions is a known fact, however, the mitigation path to achieve nationally determined goals for carbon reduction is often not specified, A simplified technique based on minimax optimization using Grey relational grade and Random forest narrows down on most contributing input variables from twelve road transport modes. This is a region-specific, scenario-based technique applied to north Punjab, Province of Pakistan that first categorizes modes based on their emission and then integrates with AI modeling using Deep Neural Network to develop sustainable trade-offs for carbon reduction. The output parameter translates the problem into a systematic iterative technique that predicts optimization options with different scenarios to bring out an environment-friendly transport mix. A 25% reduction applied to the five most emission-releasing modes like Diesel Light and Heavy Duty vehicles, Gas Light and heavy-duty vehicles, and Gas-Cars results in 16.54 MT of Carbon dioxide which is 54.35% reduced to the predicted 36.24 MT for the year 2044. Similarly in another scenario replacing 25% Gas and Diesel Light Duty vehicles respectively by adding 50% Petrol Light Duty vehicles leads to 18.94 MT of emissions which brings the emission value in 2044 at par with emission releases of the year 2014. The technique offers a forward path that allows environment-friendly modal mix combinations based on business-as-usual to offer transport mix solutions for carbon reduction. It is a generalized model that is based on a customized transport mix. Future studies can also be applied to intermodal tradeoffs like rail, air, waterways, etc.

Deep transfer learning-based anomaly detection for cycling safety

Introduction: Despite the general improvements in road safety, with the growing number of bicycle users, cycling safety is still a challenge as demonstrated by the fact that it is the only road transport mode with an increase in the number of fatalities in EU cities. Problem: Moreover, to analyze the problem to improve the road transport system, the traditional network screening based on crash statistics is a reactive approach and less effective due to the lack of suitable bicycle data availability, as well. In such a framework, new opportunities for data collection in smart cities and communities are emerging as proactive approaches to identify critical locations where safety treatments can be effectively applied to prevent bicycle crashes. Method: This research applied a deep transfer learning model to detect anomalies in cycling behavior that can be associated with traffic conflicts or near-miss crashes. Results: The paper presents how to build a users’ tailored riding model named DTL AD to detect and localize riding anomalies by using a set of data in the National Marine Electronics Association (NMEA) string of Global Navigation Satellite System (GNSS) recorded with instrumented bicycles by different cyclists. Conclusion: More specifically, DTL AD exploits a convolutional autoencoder (CAE) with transfer learning to reduce data labelling and training effort. Practical Application: A case study demonstrates the identification of anomalies in cycling behavior visually represented on Geographic Information Systems (GIS) maps, showing how data clustering is well located in high-risk areas.

Applying network flow optimisation techniques to minimise cost associated with flood disaster.

The estimated amount of $1016673.37 becomes a benchmark for the government, research agencies and other developmental agencies for the purpose of planning. By using the air and road transport modes, and allowing direct and indirect transportation to the PODs, it saved time, resulting in many lives being saved.

An integrated cross entropy methodology for planning scheme evaluation of highway transportation hub with interval-valued intuitionistic fuzzy information

After entering the 21st century, China’s national economy has shown a rapid growth momentum, the comprehensive transportation system has been continuously improved, the road traffic infrastructure has made remarkable achievements, and the modern logistics industry has also risen rapidly and grown rapidly, which has greatly changed the market demand for road transport hubs. The road transport hub is the main node of the road transport network, the hub of passenger and freight distribution of road transport, and the organizational center for the interconnection of road transport and other transport modes and the development of comprehensive transport. Highway transportation hub is an important part of highway transportation infrastructure and plays an important role in highway transportation. The planning scheme evaluation of highway transportation hub is a multi-attribute decision making (MADM). This paper intends to propose a MADM methodology based on cross-entropy (CE) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for planning scheme evaluation of highway transportation hub. First of all, this paper extends the cross entropy method under the IVIFSs to propose the interval-valued intuitionistic fuzzy number CE(IVIFN-CE) method, it enlarges the application range of the CE method. Secondly, a new MADM model for planning scheme evaluation of highway transportation hub based on IVIFN-CE algorithm is proposed.

Towards autonomous inland waterway vessels — a comprehensive analysis of regulatory, liability and insurance frameworks

The use of maritime autonomous vessels for the inland waterway (IWW) transport can revolutionise the current logistics supply chain and enable the shifting of the cargo transportation from the less efficient road and rail transport modes. However, the lack of guidelines and requirements for the operation and testing of autonomous vessels must be addressed to enable autonomous operations. This study aims to identify the gaps of the prevailing regulatory, liability and insurance frameworks and propose viable recommendations for the operation and testing of the autonomous IWW vessels. The theoretical case study of a next-generation autonomous ship operating in European IWW along with the required key enabling technologies is considered. A systematic methodological approach is followed focusing on the existing, transition and next-generation stages for developing autonomous vessels. The existing stage deals with classifying the identified gaps considering the categories of high, moderate or low severity, whereas the anticipated new stakeholders with associated risks in the context of autonomous vessels are analysed. The transition stage discusses recommendations to mitigate the identified gaps of the analysed existing frameworks by either developing interpretations, amending existing instruments or proposing new instruments. The proposed recommendations demonstrate a pathway towards upgrading the existing frameworks based on the identified severity levels and hence are expected to be beneficial for the policymakers whilst preparing the roadmap for the design and operation of next-generation autonomous ship (NGAS).

The usefulness of artificial intelligence for safety assessment of different transport modes

Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency of transportation systems. However exchange of knowledge between transport modes has been limited. This paper reviews the ML and AI methods used in different transport modes (road, rail, maritime and aviation) to address safety problems, in order to identify good practices and experiences that can be transferable between transport modes. The methods examined include statistical and econometric methods, algorithmic approaches, classification and clustering methods, artificial neural networks (ANN) as well as optimization and dimension reduction techniques. Our research reveals the increasing interest of transportation researchers and practitioners in AI applications for crash prediction, incident/failure detection, pattern identification, driver/operator or route assistance, as well as optimization problems. The most popular and efficient methods used in all transport modes are ANN, SVM, Hidden Markov Models and Bayesian models. The type of the analytical technique is mainly driven by the purpose of the safety analysis performed. Finally, a wider variety of AI and ML methodologies is observed in road transport mode, which also appears to concentrate a higher, and constantly increasing, number of studies compared to the other modes.

Study on Chest Injuries Due to Blunt Object in Road Accident

In India, people use local transport for travel. Since accidents prevail in these developing countries, India is not exceptional. The number of vehicle increases daily, and road accident occurs every two minutes. Chest injuries are widespread during accidental cases. This significantly contributed to the trauma during unintentional cases. Trauma generally affects young adults. Based on the above facts, the present study aims to determine the pathologies associated with chest injuries due to blunt objects in road accidents and to assess the blunt chest injuries among accident victims traveling in different road transportation modes and furthermore, to observe the injury pattern and its correlation with the victim's position during the road traffic accident. The study was carried out in the Branch of FMT, Raj Rajeswari Medical College and Hospital Bangalore. Data were collected from 100 cases of death caused by a road traffic accident that was presented for medico-legal post-mortem at the mortuary in the FMT department from December 2013 to May 2015. The study reports the maximum number (42%) of chest injuries occurred between the age group of 21-30 years, followed by 24% in the age group 31 � 40, with a maximum (62%) accidental cases in two-wheeler riders. The result showed that 48% of patients had rib fractures, 12% vertebral fractures, 10% sternum fractures, and 4% clavicle fractures during accidental cases, with haemothorax in 56% of cases. The result also showed that death was due to shock and hemorrhage in 92 patients and 6% due to coma. Specific injury prevention programs focusing on road safety should be implemented to limit and control the incidence of such injuries in light of our results.�

Modelling Dry Port Systems in the Framework of Inland Waterway Container Terminals

Overcoming the global sustainability challenges of logistics requires applying solutions that minimize the negative effects of logistics activities. The most efficient way of doing so is through intermodal transportation (IT). Current IT systems rely mostly on road, rail, and sea transport, not inland waterway transport. Developing dry port (DP) terminals has been proven as a sustainable means of promoting and utilizing IT in the hinterland of seaport container terminals. Conventional DP systems consolidate container flows from/to seaports and integrate road and rail transportation modes in the hinterland which improves the sustainability of the whole logistics system. In this article, to extend literature on the sustainable development of different categories of IT terminals, especially DPs, and their varying roles, we examine the possibility of developing DP terminals within the framework of inland waterway container terminals (IWCTs). Establishing combined road–rail–inland waterway transport for observed container flows is expected to make the IT systems sustainable. As such, this article is the first to address the modelling of such DP systems. After mathematically formulating the problem of modelling DP systems, which entailed determining the number and location of DP terminals for IWCTs, their capacity, and their allocation of container flows, we solved the problem with a hybrid metaheuristic model based on the Bee Colony Optimisation (BCO) algorithm and the measurement of alternatives and ranking according to compromise solution (i.e., MARCOS) multi-criteria decision-making method. The results from our case study of the Danube region suggest that planning and developing DP terminals in the framework of IWCTs can indeed be sustainable, as well as contribute to the development of logistics networks, the regionalisation of river ports, and the geographic expansion of their hinterlands. Thus, the main contributions of this article are in proposing a novel DP concept variant, mathematically formulating the problems of its modelling, and developing an encompassing hybrid metaheuristic approach for treating the complex nature of the problem adequately.

Energy assessment of e-motorcycles as a clean transport mode for passenger mobility: A case of Ilala District, Dar es Salaam

Electric motorcycles or e-motorcycles is a clean mode of road transport that present a prominent solution toward decarbonizing cities. Despite of e-motorcycles being cleaner than gasoline ones, at the moment, there is missing information whether it is feasible to replace gasoline motorcycles with e-motorcycles used for business transport purposes. This paper, therefore, presents the results comparing energy usage when using e-motorcycles and when using the gasoline motorcycles. The energy demand for driving passengers using an e-motorcycle in the precarious routes originated from Gongo la Mboto bus stop to Segerea bus stop, Buguruni Malapa, Gerezani bus stop, Kivukoni bus stop, and Buza bus stop has been estimated. In each route, the energy has been estimated in one and four round-trips. The results reveal that the brushless direct current motor (BLDC) rated 2.5 kW is suitable for driving two passengers while consuming about 0.05 kWh/km at 50 km/h for the distance of 36 km. Increase in route length exhibit the uptrend in total energy required (Etotal). The maximum Etotal for one and four round-trips are 2.5 kWh and 10.0 kWh, respectively, for a route of 36 km length. Considering the energy demand of 2.5 kWh for one round-trip of 36 km, a battery pack of 45 Ah 60 V is found suitable to power the e-motorcycle per charge without compromising the design in terms of weight and size. Consequently, this yields to a saving of about 6.4 kWh, which is around 72 % of the energy that could be used by its gasoline counterpart. This means an e-motorcycle of this power rating could save 0.18 kWh/km, equivalent to 0.02 L/km. Moreover, e-motorcycle could cost 24.3 Tsh/km compared to 754.8 Tsh/km for its gasoline counterpart, and save around 97 % of the fuel cost. These results indicate that an e-motorcycle can outperform its gasoline counterpart. These findings play vital roles in designing energy storage systems and charging infrastructure that could offer a reliable service to end-users and assist to accelerate e-motorcycle adoption.

Adopting a Bi-level Optimization Method for the Freight Transportation Problem: A Multi-objective Programming Approach

Nowadays, various companies find it a crucial task to elevate their distribution system efficiency to survive in what is an intensely competitive environment. Freight transportation via road systems may not always be a practical option for the shipper because of financial, social, and environmental aspects. So, in addition to the road system, the shipper can benefit greatly from the rail system. Thus, taking advantage of different transportation modes can help shippers to tackle, to some extent, arising issues. In this paper, we aim at investigating a freight transportation network including rail and road transportation modes in which the shipper’s choice affects the decisions deeply. Given that this problem as a bi-level programming model, the rail operator acts as a leader and the shipper is treated as a follower. Once the rail operator reveals the rail transportation price, an appropriate response is received from the shipper and this pattern is repeated until an equilibrium is achieved. From the sustainability view, a multi-objective mixed-integer programming model is developed to simulate their interactions considering a sustainable triple bottom line. Employing the Karush–Kuhn–Tucker approach, we converted the formulated bi-level programming model into a single one. Several numerical examples are investigated to evaluate the validity of the developed model and approaches. Different in-depth sensitivity analyses are carried out and the impacts of several factors, such as line and train capacity, on the rail operator and shipper’s decisions are investigated. The results reveal that the rail operator could increase their market share by a wise long-term investment in the rail infrastructure.

Persepsi Masyarakat Terhadap Sumbangan Wajib Dana Kecelakaan Lalu Lintas Jalan Dan Kebijakan Perlindungan Kecelakaan Jalan

Safety is an important part in using motor vehicles and public transportation, where in 2019 the road transport mode ranks third after the flight mode and cruise mode with a contribution of 24.9%, for that safety can be a safe culture in travel. The purpose of the study was to determine the perception of society related to SWDKLLJ and the level of community satisfaction. The research method is using qualitative descriptive approach with data collection using Gay and Diehl data collection techniques with a sample of 28 respondents, using google form. This data collection was given randomly to respondents and secondary data was obtained from literature and research results to support this study. The results showed that (1) knowledge about iruan SWDKLLJ majority of respondents do not know as much as 51.9%, (2) utilizing the mandatory donation of road traffic accident funds (SWDKLLJ) the majority of respondents are not as much as 88.9%, (3) other insurance funding as a replacement, the majority of respondents answered No 44%, (4) Officer services in making claims using SWDKLLJ, the majority of respondents answered quite satisfied 44%. Further studies are needed to reveal the public satisfaction of swdkllj contribution services and highway safety protection policies.