Transportation - Spatiotemporal data, and more specifically origin–destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes.... 相似文献
Transportation - Traffic congestion is a common phenomenon in road transportation networks, especially during peak hours. More accurate prediction of dynamic traffic flows is very important for... 相似文献
Transportation - This study examines to what extent travel information can be used to direct travelers to system-optimal routes that may be sub-optimal for them personally, but contribute to... 相似文献
People’s behavior is governed by extremely complex, multidimensional processes. This fact is well-established in the transportation research community, which has been working on travel behavior (travel demand) models for many years. The number of degrees of freedom in a person’s activity schedule is enormous. However, the frequency of occurrence of day-long activity schedules obeys a remarkably simple, scale-free distribution. This particular distribution has been observed in many natural and social processes and is commonly referred to as Zipf’s law, a power law distribution. This research provides evidence that activity schedules from various study areas exhibit a universal power law distribution. To this end, an elaborate analysis using 13 household travel surveys from diverse study areas discusses the effect of proportional outlier removal on the power law’s exponent value. Statistical evidence is provided for the hypothesis that activity schedules in all these datasets exhibit a power law distribution with a common exponent value. The study proposes that a Zipf power law could be used as an additional dimension within a travel demand model’s validation process. Contrary to other validation methods, no new data is required. The observation of a Zipf power law distribution in the generated schedules appears to be a necessary condition. Additionally, the universal activity schedule distribution might enable the full integration of activity schedules in models based on universal mobility patterns.
A grid based modelling approach akin to cellular automata (CA) is adopted for heterogeneous traffic flow simulation. The road space is divided into a grid of equally sized cells. Moreover, each vehicle type occupies one or more cell as per its size unlike CA traffic flow model where each vehicle is represented by a single cell. Model needs inputs such as vehicle size, its maximum speed, acceleration, deceleration, probability constants, and arrival pattern. The position and speed of the vehicles are assumed to be discrete. The speed of each vehicle changes according to its interactions with other vehicles, following some stochastic rules depending on the circumstances. The model is calibrated and validated using real data and VISSIM. The results indicate that grid based model can reasonably well simulate complex heterogeneous traffic as well as offers higher computational efficiency needed for real time application. 相似文献
Most of the information necessary for driving a vehicle is regarded as visual information. In spite of its importance, visibility conditions at the time of a crash are often not documented at a high level of detail. Past studies have not examined the quantified values of visibility and its association with crashes. The current study merged data collected from the National Oceanic and Atmospheric Administration (NOAA) with 2010–2012 Florida crash data. From the thousands of logged weather events compiled by the NOAA, the researchers isolated periods of normal visibility and comparable periods of reduced visibility in a matched-pairs study. The NOAA data provided real visibility score based on the spatiotemporal data of the crashes. Additionally, the crash data, obtained from Roadway Information Database (RID), contains several geometric and traffic variables that allow for effects of factors and visibility. The study aims to associate crash occurrence under different levels of visibility with factors included in the crash database by developing ordinal logistic regression. The intent is to observe how different visibility conditions contribute to a crash occurrence. The findings indicate that the likelihood of a crash increase during periods of low visibility, despite the tendency for less traffic and for lower speeds to prevail during these times. The findings of this study will add valuable knowledge to the realm of the impact of visibility in the way of using and designing appropriate countermeasures. 相似文献
This paper evaluates the pros and cons of implementing parking pricing to reduce auto use and traffic through parking taxes. Taxes on parkers and the providers are evaluated in terms of effectiveness in influencing auto use, operations of the tax, and the legality as well as acceptability of the options. The intent is to help local governments evaluate parking tax approaches.Abbreviation TDM
Transportation Demand Management 相似文献
