Incorporating vehicle mix in stimulus-response car-following models

The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three submodels were developed for different pairs of following vehicles including ＂automobile following automobile,＂ ＂automobile following truck,＂ and ＂truck following automobile.＂ The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers＇ behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

The dynamic response of forest vegetation to hydro- thermal conditions in the Funiu Mountains of western Henan Province

This paper uses HJ-1 satellite multi-spectral and multi-temporal data to extract forest vegetation information in the Funiu Mountain region. The S-G filtering algorithm was employed to reconstruct the MODIS EVI（Enhanced Vegetation Index） time-series data for the period of 2000–2013, and these data were correlated with air temperature and precipitation data to explore the responses of forest vegetation to hydrothermal conditions. The results showed that：（1） the Funiu Mountain region has relatively high and increasing forest coverage with an average EVI of 0.48 over the study period, and the EVI first shows a decreasing trend with increased elevation below 200 m, then an increasing trend from 200–1700 m, and finally a decreasing trend above 1700 m. However, obvious differences could be identified in the responses of different forest vegetation types to climate change. Broad-leaf deciduous forest, being the dominant forest type in the region, had the most significant EVI increase.（2） Temperature in the region showed an increasing trend over the 14 years of the study with an anomaly increasing rate of 0.27℃/10a; a fluctuating yet increasing trend could be identified for the precipitation anomaly percentage.（3） Among all vegetation types, the evergreen broad-leaf forest has the closest EVI-temperature correlation, whereas the mixed evergreen and deciduous forest has the weakest. Almost all forest types showed a weak negative EVI-precipitation correlation, except the mixed evergreen and deciduous forest with a weak positive correlation.（4） There is a slight delay in forest vegetation responses to air temperature and precipitation, with half a month only for limited areas of the mixed evergreen and deciduous forest.