Model and algorithm of optimizing alternate traffic restriction scheme in urban traffic network

An optimization model and its solution algorithm for alternate traffic restriction(ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover,practical processing approaches were suggested, which may improve the operability of the model-based solutions.

Traffic Modeling and Analysis of Cellular Networks with Dynamic Channel Allocation

Dynamic channel allocation can reduce the blocking probability of cellular networks. This paper aims atestimating the blocking probability for cellular networki with dynamic channel allocation. Traffic analysis modelsare presented to evaluate performance of cellular networkS, The blocking probabilities versus traffic offered to eachcell are analyzed and simulated Comparisons between analysis and simulation results are made.

Use of Hi-resolution data for evaluating accuracy of traffic volume counts collected by microwave sensors

Over the past few years, the Utah Department of Transportation has developed the signal performance metrics （SPMs） system to evaluate the performance of signalized in- tersections dynamically. This system currently provides data summaries for several per- formance measures, one of them being turning movement counts collected by microwave sensors. As this system became public, there was a need to evaluate the accuracy of the data placed on the SPMs. A large-scale data collection was carried out to meet this need. Vehicles in the Hi-resolution data from microwave sensors were matched with the vehicles by ground-truth volume count data. Matching vehicles from the microwave sensor data and the ground-truth data manually collected required significant effort, A spreadsheet- based data analysis procedure was developed to carry out the task. A mixed model analysis of variance was used to analyze the effects of the factors considered on turning volume count accuracy. The analysis found that approach volume level and number of approach lanes would have significant effect on the accuracy of turning volume counts but the location of the sensors did not significantly affect the accuracy of turning volume counts. In addition, it was found that the location of lanes in relation to the sensor did not significantly affect the accuracy of lane-by-lane volume counts. This indicated that accu- racy analysis could be performed by using total approach volumes without comparing specific turning counts, that is, left-turn, through and right-turn movements. In general, the accuracy of approach volume counts collected by microwave sensors were within the margin of error that traffic engineers could accept. The procedure taken to perform the analysis and a summary of accuracy of volume counts for the factor combinations considered are presented in this paper.