Effect evaluation of traffic guidance in urban underground road diverging and merging areas: A simulator study.

Traffic accidents occur frequently in urban underground road diverging and merging areas due to the limited vision and complex traffic. Well-designed traffic visual guidance is one of the effective measures to alleviate the traffic safety problems in the diverging and merging areas of urban underground roads. In this study, four different integrated traffic guidance schemes (including signs, marking lines and sidewall guidance) were proposed and their effects on drivers' behaviour were investigated through driving simulator experiments and questionnaire survey. To investigate the influence of different schemes, eight variables about driving behaviour and guidance efficiency were assessed for analysis. Finally, a fuzzy comprehensive evaluation model based on analytic hierarchy process (FCE + AHP) was constructed to evaluate the effect of guidance schemes. Vehicle running state, driver operation behaviour and guidance efficiency were mainly considered. The guidance evaluation results obtained by the model were consistent with the conclusions of the driver subjective questionnaire. The results show that reasonable setting of white dotted lines and colour guidance can help drivers find exits quickly and improve driving stability. However, excessive combination of traffic guidance leads to information overload and produces the opposite effect. This study can provide a generic framework for the design and evaluation of traffic guidance facilities of urban underground roads.

Analysis of Car-Following Behaviors under Different Conditions on the Entrance Section of Cross-River and Cross-Sea Tunnels: A Case Study of Shanghai Yangtze River Tunnel.

Compared to highway road tunnels, the entrance section of cross-river and cross-sea tunnels feature long and steep slopes. Along with a complicated traffic environment and harmful weather conditions, traffic congestion and rear-end crashes occur frequently during car-following in cross-river and cross-sea tunnels. It is necessary to examine the impact of traffic flow and weather conditions on car-following behavior at the entrance section of cross-river and cross-sea tunnels. To this end, this paper first extracted the vehicle speed data based surveillance video at the entrance of the Shanghai Yangtze River Tunnel. Moreover, the actual average speed under different traffic flow conditions was obtained through the clustering algorithm, which was used as the basis for setting the experimental parameters. Then, in the driving simulation experiment, three traffic flow conditions (free flow, congested flow, and jam flow) were set up in three weather conditions (sunny, rainy, and snowy), and a risk situation was set up in each condition. Distance headway, time headway, acceleration, lateral offset, and driver's emergency response time were collected. Moreover, seven slopes of 2% to 5% were set, and the relationship of slope on longitudinal speed and lateral offset was analyzed. ANOVA and post-hoc analyses were applied. The result indicates that traffic flow conditions have a significant effect on the car-following behavior, while weather conditions mainly influence the time headway. Moreover, drivers tend to adopt more cautious driving behavior as the distance between the vehicle and the tunnel entrance decreases. The results also show that the slope of the cross-river and cross-sea tunnel entrance section has a major influence on vehicle speed.

A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions.

Social and economic burdens caused by truck-involved rear-end collisions are of great concern to public health and the environment. However, few efforts focused on identifying the difference of impacting factors on injury severity between car-strike-truck and truck-strike-car in rear-end collisions. In light of the above, this study focuses on illustrating the impact of variables associated with injury severity in truck-related rear-end crashes. To this end, truck involved rear-end crashes between 2006 and 2015 in the U.S. were obtained. Three random parameters ordered probit models were developed: two separate models for the car-strike-truck crashes and the truck-strike-car crashes, respectively, and one for the combined dataset. The likelihood ratio test was conducted to evaluate the significance of the difference between the models. The results show that there is a significant difference between car-strike-truck and truck-strike-car crashes in terms of contributing factors towards injury severity. In addition, indicators reflecting male, truck, starting or stopped in the road before a crash, and other vehicles stopped in lane show a mixed impact on injury severity. Corresponding implications were discussed according to the findings to reduce the possibility of severe injury in truck-involved rear-end collisions.

Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model.

The existing studies on drivers' injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers' injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

Focusing giga-electronvolt heavy ions to micrometers at the Institute of Modern Physics.

To study the radiation effect of cosmic heavy ions of low fluxes in electronics and living samples, a focusing heavy ion microbeam facility, for ions with energies of several MeV/u up to 100 MeV/u, was constructed in the Institute of Modern Physics of the Chinese Academy of Sciences. This facility has a vertical design and an experiment platform for both in-vacuum analysis and in-air irradiation. Recently, microbeam of (12)C(6+) with energy of 80.55 MeV/u was successfully achieved at this interdisciplinary microbeam facility with a full beam spot size of 3 µm × 5 µm on target in air. Different from ions with energy of several MeV/u, the very high ion energy of hundred MeV/u level induces problems in beam micro-collimation, online beam spot diagnosis, radiation protection, etc. This paper presents the microbeam setup, difficulties in microbeam formation, and the preliminary experiments performed with the facility.