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Purpose – Urban and suburban arterials carry a large share of urban traffic and contend with a relatively large proportion of transport network crashes. Road crashes and their consequent societal costs diminish the sustainability of transportation systems, highlighting the need to identify road safety problems and their corresponding solutions. This chapter briefly outlines problems and solutions associated with crash risk on urban and suburban arterials. In addition, this chapter studies and discusses several safety countermeasures – ranging from local treatments to integral frameworks – and their effectiveness on improving traffic safety of urban and suburban arterials.

Approach – Crash occurrence on urban and suburban arterials is affected by numerous contributing factors. This chapter pays attention primarily to the effects of traffic characteristics and road design features. In this regard, several pertinent variables which have been extensively examined in the literature are reviewed and their contributions to the safety of urban and suburban arterials are discussed.

Findings – A review of the literature identifies a number of variables as influential factors of crashes on urban and suburban arterials. Although the associations of some variables (e.g., traffic volume) are consistent with expectations, others (e.g., lane width and speed) show mixed and sometimes counterintuitive results. These findings signify that additional research is needed to reveal the correct functional form and magnitude of these relationships.

Practical implications – The results show that while the general direction and magnitude of effects of some engineering and management-related treatments are known, additional research is needed to consolidate the impact and effectiveness of integrated approaches.

This paper aims to address the urban mobility and traffic congestion problem under environmental dynamics to improve mobility and reduce traffic congestion using system dynamics (SD) simulation and scenarios.

SD simulation was used to analyze urban mobility and traffic congestion. Data were collected from the Transportation Department of Surabaya City. Several scenarios to improve urban mobility and reduce traffic congestion were developed by modifying the structures and parameters of the model.

Several factors influence urban mobility, including modal split, trip frequency, delay performance and the ratio of public transport supply and demand. Urban mobility, daily traffic and road capacity are some factors that affect traffic congestion. Scenarios can be designed based on the assumptions of the proposed strategy.

The study was conducted at Surabaya City, East Java, Indonesia, which is the fourth most-congested city in the world.

By implementing several strategies (mass rapid transit and bus rapid transit development and public transport delay reduction), mobility performance is projected to be improved by 70.34-92.96%. With this increased mobility, traffic congestion is projected to decline by 52.5-65.8%.

The novel contributions of this research are: formulating relationships between several variables; modeling dynamic behavior of urban mobility and traffic congestion; and building scenario models to improve mobility and reduce traffic congestion in Surabaya. With the increase in urban mobility and the decrease in average daily traffic, traffic congestion could be reduced by a minimum of 57.6% and a maximum of 69%.

With the continuous expansion of urban scale, blindly increasing or controlling transportation infrastructure possibly creates a short board in an urban system. In this study, a macro traffic integrated system was constructed according to a city's economic size distribution and transportation infrastructure. The planning strategy of traffic, industry, space interaction and coordinated development was put forward. Through theoretical model, the evolution mechanism between transportation infrastructure and economic scale distribution was revealed. Starting from the center of the city and inter city level, China's new urbanization strategy was implemented, and a comprehensive transportation system model was built. The traffic planning in Singapore was taken as an example, and the solution to traffic problems such as congestion, traffic jam, and distance was obtained. Practice has proved that the rational and effective urban transportation infrastructure construction can effectively promote the coordinated development of economy and resources, and comprehensively enhance the level of integrated transport services.

The purpose of this paper is to expound the concept of the coordinated development of the transport system, and provide a quantitative method to support decision making in urban transportation development planning.

To analyze the organic composition of urban transport system, research the meaning and mechanism of coordinated development of transport system. On the basis of researching relations of transport and external systems and its subsystems, to research quantitative theoretical model of the coordinated development and assessment of the transport system.

Establishing models needs to analyze the coordination among the various indices of subsystem, calculate the overall coordination between indices of the subsystem and all the indices of other subsystems, then inspect the coordinated development among subsystems.

How to design the indexes of the subsystem of urban transport system is the main limitation.

Offering theoretical foundation for coordinated development of urban transport system.

Putting forward quantitative theoretical model on coordinated development of urban transport system, which lays a foundation for further study.

The density and pattern of urban parks, traffic conditions are the main factors affecting urban park accessibility. To clarify the influence of traffic mode and urban road network on urban park accessibility, we examine downtown area of Nanjing, China, and based on GIS network analysis, analyze urban park accessibility under different traffic modes in the current year (2017) and the Nanjing master planning target year (2030). The results shows: Using automobiles takes the shortest time to get to urban parks in 2017 and 2030 (if the problem of parking is ignored). Comparing the results of 2030 and 2017, by when the ground transportation network in the study area will be further improved, urban park accessibility was improved by a small margin under walking and automobile traffic modes, however, the density of rail traits increased fastest, urban park accessibility is improved most under this mode of transportation, rail transit route development becomes the dominant factor in improving park accessibility in downtown area of Nanjing. To a certain extent, this study reveals the leading factors of improving the accessibility of urban parks on the premise that the system of urban parks tends to be stable, and provides a reference for improving urban park accessibility.

This paper provides an extensive review of surveys and data-collection programmes focused on urban goods movement (UGM). Surveys investigating passenger urban travel have a decades-long tradition. The same is not true for UGM. The first specific UGM surveys appeared about 10 years ago in response to the rapid growth of car traffic, congestion, pollution and lack of space. Most of the time, these surveys have been carried out to resolve specific, local problems concerning traffic. Only a few of them have taken a global approach to urban logistics by including all logistics operators (own-account and carriers), all delivery vehicles (heavy and light vehicles), all deliveries and pickups (from express to full payload) and an entire metropolitan area and surroundings. Due to various European programmes, an inventory has been created to analyse urban goods data collection according to spatial level and methodology of capture. With this inventory, European urban freight indicators can be described, along with the units in which they are measured and their purposes. The relevance of urban goods transport surveys lies in their capacity to give decision-makers an account of urban freight transport functioning, ratios and data, so as to help in formulating planning, regulation and forecasting. It appears that focusing on the movement (delivery/pick-up), as the unit of analysis in establishment-driver surveys is the most efficient approach to describe the generation of vehicular flow in the city. This fact is revealed in the French UGM surveys, which take into account the complexity of urban logistics.

In the face of solving the urban traffic congestion problem radically, emphasis has been laid on the research on slow traffic planning of urban built environment. Hence, research on slow traffic demand forecasting can provide a basis for the planning of urban slow traffic systems. Based on land use, the overall planning of the new Guangming (GM) district, and the population prediction results, the slow traffic demand within the scope of the new district was forecasted by combining the per capita trip frequency, and the spatial distribution of the slow traffic flow of the new GM district was forecasted per the forecasted demand quantity for slow traffic. The following research conclusions were obtained. Within the new GM district, the correlation of the total demand for slow traffic with the land use functions and population distribution was high, and the cross-zone traffic was mainly decided by the land usage of this district. The cross-unit slow traffic flow was concentrated in the Gongming central, Guangming central, high-tech zone, and Yutian zones. This research provides a guideline for the layout of slow traffic facilities in the future.

This paper aims to present collection and analysis of heterogeneous urban traffic data, and integration of them through a kernel-based approach for assessing performance of urban transport network facilities. The recent development in sensing and information technology opens up opportunities for researching the use of this vast amount of new urban traffic data. This paper contributes to analysis and management of urban transport facilities.

In this paper, the data fusion algorithm are developed by using a kernel-based interpolation approach. Our objective is to reconstruct the underlying urban traffic pattern with fine spatial and temporal granularity through processing and integrating data from different sources. The fusion algorithm can work with data collected in different space-time resolution, with different level of accuracy and from different kinds of sensors. The properties and performance of the fusion algorithm is evaluated by using a virtual test bed produced by VISSIM microscopic simulation. The methodology is demonstrated through a real-world application in Central London.

The results show that the proposed algorithm is able to reconstruct accurately the underlying traffic flow pattern on transport network facilities with ordinary data sources on both virtual and real-world test beds. The data sources considered herein include loop detectors, cameras and GPS devices. The proposed data fusion algorithm does not require assumption and calibration of any underlying model. It is easy to implement and compute through advanced technique such as parallel computing.

The presented study is among the first utilizing and integrating heterogeneous urban traffic data from a major city like London. Unlike many other existing studies, the proposed method is data driven and does not require any assumption of underlying model. The formulation of the data fusion algorithm also allows it to be parallelized for large-scale applications. The study contributes to the application of Big Data analytics to infrastructure management.

Many cities implement freight traffic restriction policy (FTRP) intending to reduce traffic congestion and air pollution. At the same time, city distribution had some negative effects. The purpose of this paper is therefore to study the freight group behavior under FTRP, and to provide some recommendations for the government.

This paper establishes a city distribution system model built by a simulation method of Agent, which includes the complex adaptability of freight individual, event of restriction policy, the influence factor of freight group behavior and its changes from the perspective of restriction policy. The rules of microscopic freight group behavior to macroscopic freight group behavior, the effects on freight group behavior exerted by restriction policy and the dynamic mechanism of freight group behavior are all studied. The model is also simulated with the traffic data of Beijing in China.

Theoretical results ensure that restriction of the passport is not the sole reason that may produce illegal trucks, and other measures need to be taken to solve the traffic problems. And in the long run, increasing fines has a greater effect than strengthening supervision frequency on illegal trucks reduction.

From city distribution perspective, this paper studied freight group behavior under FTRP. This paper also applied the Agent modeling method to build a model of urban distribution system in the FTRP.