OBJECTIVE: The surge in popularity of electric kick scooters (e-scooters) poses new challenges for traffic planning, demanding a comprehensive understanding of route choice behavior to see how e-scooters are used, how they affect traffic flow, and where improvements can be made to the road infrastructure. Therefore, this study aimed to analyze route choices and preferences of e-scooter riders and cyclists in a quasi-experimental setup with both user groups having the same trip destinations.
METHODS: Two groups of participants (n = 52) completed a ride with either a shared e-scooter or bicycle to reach four predefined destinations in Dresden, Germany. The riders were supposed to choose their routes and subsequently reported the difficulty of decision-making and the importance of several route choice factors related to the ride.
RESULTS: E-scooter riders rated road surface and safety as significantly more important for route choice than cyclists and tended to perceive the decision-making as more difficult. Riding data revealed broad comparability between the groups, with e-scooter riders tendentially having longer routes for complex decisions (unknown destinations, scenic routes, more turns required).
CONCLUSIONS: The study suggests that the route preferences of e-scooter riders may be influenced by a combination of road surface and safety considerations, highlighting the need for high-quality cycling infrastructure. Limitations exist regarding the naturally occurring differences in riding experience in e-scooter riding versus cycling. Practical implications indicate that planning for e-scooter riders can benefit from insights drawn from activities designed for cyclists. The provision of real-time road quality information is proposed, considering its potential impact on overall road safety.
CONCLUSIONS: This study contributes to a better understanding of how e-scooter riders navigate through cities and delivers a valuable foundation for transport planners and engineers considering the rise in cycling and micro-mobility use.

The surface condition of roadways has direct consequences on a wide range of processes related to the transportation technology, quality of road facilities, road safety, and traffic noise emissions. Methods developed for detection of road surface condition are crucial for maintenance and rehabilitation plans, also relevant for driving environment detection for autonomous transportation systems and e-mobility solutions. In this paper, the clustering of the tire-road noise emission features is proposed to detect the condition of the wheel tracks regions during naturalistic driving events. This acoustic-based methodology was applied in urban areas under nonstop real-life traffic conditions. Using the proposed method, it was possible to identify at least two groups of surface status on the inspected routes over the wheel-path interaction zone. The detection rate on urban zone reaches 75% for renewed lanes and 72% for distressed lanes.

On the basis of road tests, the authors assessed the feasibility of the vehicle body acceleration values for the purposes of assessing road surface characteristics in terms of its roughness. Short-term Fourier Transform (STFT) was used for the analysis of the recorded signal. The spectra obtained in successive frequency bands demonstrate the amplitudes originating from the natural vibrations of the rolling wheel and forces resulting from the interaction with the road roughness. The article focuses on the relationships between the road roughness and the ratios of individual amplitudes in a specific frequency band of the vehicle body acceleration values. Amplitude values derived on the basis of successive windows were averaged for analogous, arbitrarily assumed local frequency bands. The value characterizing the road surface condition provided the information regarding the mean amplitude value in specific frequency ranges depending on the instantaneous velocity of the car body and the condition of the road surface on which it was moving. In cases where the road was free of any visible roughness, the obtained mean amplitude value in the analyzed spectrum window, for the adopted vehicle velocity range from 50 km h to 100 km/h, did not exceed 0.02 m/s2. It was also demonstrated that the road surface roughness leads to an increase in the mean amplitude value from 0.07 m/s2 to 0.16 m/s2.

As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model.

The Semi-Flexible Water Retaining Pavement (SFWRP) has the capability to cool down the temperature of the road surface through its evaporation behavior, including absorbing and evaporating water; this is an efficient approach to relieve the heat island effect in a big city. The temperature feedback from different material surface were investigated in this paper in the same test condition, it has been proved that the SFWRP material can remarkably cool down the temperature of the road surface. The mechanism of the material evaporation behavior, including flux calculation formula of the water vapor inside the air void, were studied by inter-phase continuous function, in which the structural properties of the SFWRP material was taken into account. Furthermore, the function calculating the evaporation of the water vapor was then developed in this research through heat and mass transfer analogy. Besides, the calculating results can be captured by the self-coding program in Finite Element Modeling (FEM) for water evaporation simulation. Also, the results of laboratory tests were adopted to validate the calculating model. Finally, it has been proved that the mortar was recommended to be used in semi-flexible water retaining pavement to serve as material with permeable and water retaining property, and the semi-flexible water retaining pavement material is recommended to applied in the surface layer of the permeable pavement.

UNASSIGNED: Road traffic accidents are one of the serious disasters that cause public injury, fatality and great economic loss. They are a growing public health problem around the world.
UNASSIGNED: The aim of this study was to determine epidemiological characteristics, tendency and possible influencing factors of road traffic injuries (RTIs) in China, so as to give target suggestions on preventative measures.
UNASSIGNED: Road traffic accident data were obtained from National Bureau of Statistics of China and Ministry of Transport of the People\'s Republic of China. Descriptive statistic such as RTIs frequency, trends of different accident types from 2007 to 2016; the RTIs difference between different regions and road surfaces were compared; and the possible influencing factors of RTIs were also explored.
UNASSIGNED: Over the past decade, with the mileage of constructed highway increased, the frequency of road traffic accidents have declined substantially in China, and the death toll from road traffic accidents with motor vehicles has declined from 2007 to 2015, Conversely, the number of deaths from non-motor vehicle accidents has risen rapidly since 2012. Our study showed that the traffic accident related mortality in Guizhou province was different from the level of the whole nation, and the Eastern, Central and Western areas of China were all significantly different (P < 0.001). Linear regression suggested a significant affected of gross domestic product (GDP)-per-capita, education level, the number of health institutions, populations, and car ownership status on traffic accident death tolls (P < 0.001). Moreover, cement concrete pavement roads were associated with the highest occurrence rates of RTI, and RTIs was statistically significant (P < 0.001) on different road surfaces.
UNASSIGNED: Even though the frequency of road traffic accidents has declined, RTIs remain an urgent public health problem in China. Thus, the government should give some target preventative measures to reduce RTIs, aiming at different regions, the increasing trend of the death toll related to non-motor vehicles and the highest occurrence on cement concrete pavement roads.

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.

Road tunnels act like large laboratories; they provide an excellent environment to quantify atmospheric particles emission factors from exhaust and non-exhaust sources due to their known boundary conditions. Current work compares the High Volume, Dichotomous Stacked Filter Unit and Partisol Air Sampler for coarse, PM10 and PM2.5 particle concentration measurement and found that they do not differ significantly (p = 95%). PM2.5 fraction contributes 66% of PM10 proportions and significantly influenced by traffic (turbulence) and meteorological conditions. Mass emission factors for PM10 varies from 21.3 ± 1.9 to 28.8 ± 3.4 mg/vkm and composed of Motorcycle (0.0003-0.001 mg/vkm), Cars (26.1-33.4 mg/vkm), LDVs (2.4-3.0 mg/vkm), HDVs (2.2-2.8 mg/vkm) and Buses (0.1 mg/vkm). Based on Lawrence et al. (2013), source apportionment modelling, the PM10 emission of brake wear (3.8-4.4 mg/vkm), petrol exhaust (3.9-4.5 mg/vkm), diesel exhaust (7.2-8.3 mg/vkm), re-suspension (9-10.4 mg/vkm), road surface wear (3.9-4.5 mg/vkm), and unexplained (7.2 mg/vkm) were also calculated. The current study determined that the combined non-exhaust fleet PM10 emission factor (16.7-19.3 mg/vkm) are higher than the combined exhaust emission factor (11.1-12.8 mg/vkm). Thus, highlight the significance of non-exhaust emissions and the need for legislation and abatement strategies to reduce their contributions to ambient PM concentrations.