Research on Strategy Control of Taxi Carpooling Detour Route under Uncertain Environment

For the problem of route choice in taxi carpooling detour, considering the uncertainty of traffic and the characteristic of passengers’ noncomplete rationality, an evolutionary game model of taxi carpooling detour route is built, in which prospect theory is introduced and revenue of strategy is replaced by prospect value. The model reflects more really decision-making psychology of passengers. Then the stable strategies of the model are studied, and the influences of detour distance and traffic congestion on detour carpooling success are analyzed, respectively. The results show that when at least one route of which prospect values for two passenger sides are both positive exists, carpooling route can reach an agreement. The route is stable strategy of evolutionary game, and the passengers requiring short travel time tend to select the nondetour route. With the increase of detour distance and traffic congestion rate, the possibility of reaching an agreement decreases gradually; that is, possibility of carpooling failure increases. So taxi carpooling detour is possible under the certain condition, but some measures must be carried out such as constraints of detour distance and mitigation of traffic congestion to improve carpooling success probability. These conclusions have a certain guiding significance to the formulation of taxi carpooling policy

Modulation of Preactivation of PPAR- β

The aim of this study is to investigate the neuroprotective effects and relevant mechanism of GW0742, an agonist of PPAR-β, after global cerebral ischemia-reperfusion injury (GCIRI) in rats. The rats showed memory and cognitive impairment and cytomorphological change in the hippocampus neurons following GCIRI. These effects were significantly improved by pretreatment with GW0742 in the dose-dependent manner. The expressions of IL-1β, IL-6, and TNF-α were increased after GCIRI, while the increases in these proinflammatory cytokines by GCIRI were inhibited by GW0742 pretreatment. Similarly, GW0742 pretreatment also improved the GCIRI-induced decrease in the expression of IL-10, which can act as an inhibitory cytokine to reduce cerebral ischemic injury. For another, NF-κB p65 expression was significantly increased in hippocampal neurons with apparent nuclear translocation after global cerebral IRI, and these phenomena were also largely attenuated by GW0742 pretreatment. Moreover, the mRNA and protein expressions of PPAR-β were significantly decreased in GCIRI + GW0742 groups when compared with those in GCIRI group. Our data suggests that the PPAR-β agonist GW0742 can exert significant neuroprotective effect against GCIRI in rats via PPAR-β activation and its anti-inflammation effect mediated by the inhibition of expression and activation of NF-κB in the hippocampus

Road traffic flow forewarning and control model with the slope of the change rate

Zadnjih je godina točno i učinkovito kratkoročno predviđanje toka prometa u realnom vremenu jedna od ključnih tehnologija u ostvarenju upravljanja i reguliranja tokom cestovnog prometa iz ITS područja (Intelligent Transport System). Analizirajući postojeći model predviđanja toka prometa, predlaže se model za reguliranje cestovnog toka prometa, Model može pronaći nenormalnu točku analizom vremenskih serija toka prometa primjenom pada promjene brzine (slope change rate), i može analizirati taj trend promjena toka prometa u svrhu reguliranja toka prometa. Rezultati pokazuju da je algoritam pogodan za problem reguliranja vršnog cestovnog opterećenja prometa , a može biti učinkovit u reguliranju cestovnog prometa.Real-time, accurate and efficiency short term traffic flow prediction is one of the key technologies to realize traffic flow guidance and traffic control, which has been widely concerned in the domain of ITS (Intelligent Transport System) during recent years. Through the study of the existing traffic flow prediction model, road traffic flow control model with the slope of the change rate is proposed. The model can find out abnormal point from the traffic flow time series by the use of the slope change rate, and it can analyse this trend of traffic flow changes for control purposes of traffic flow. The achieved results indicate that the algorithm is suitable for road traffic flow peak control problem and could be effective for road traffic flow control

An Improved Genetic Algorithm for the Large-Scale Rural Highway Network Layout

For the layout problem of rural highway network, which is often characterized by a cluster of geographically dispersed nodes, neither the Prim algorithm nor the Kruskal algorithm can be readily applied, because the calculating speed and accuracy are by no means satisfactory. Rather than these two polynomial algorithms and the traditional genetic algorithm, this paper proposes an improved genetic algorithm. It encodes the minimum spanning trees of large-scale rural highway network layout with Prufer array, a method which can reduce the length of chromosome; it decodes Prufer array by using an efficient algorithm with time complexity o(n) and adopting the single transposition method and orthoposition exchange method, substitutes for traditional crossover and mutation operations, which can effectively overcome the prematurity of genetic algorithm. Computer simulation tests and case study confirm that the improved genetic algorithm is better than the traditional one

Path optimization of taxi carpooling.

The problem that passengers are hard to take taxis while empty driving rate is high widely exists under the traditional taxi operation mode. The implementation of taxi carpooling mode can alleviate the problem in a certain extent. The objective of this study is to optimize the taxi carpooling path. Firstly, the taxi carpooling path optimization model with single objective and its extended model with multiple objectives are built respectively. Then, the single objective path optimization model of taxi carpooling is solved based on the improved single objective genetic algorithm, and the multiple-objective path optimization model of taxi carpooling is solved based on the improved multiple-objective genetic algorithm. Finally, a case study is carried out based on a road network with 24 nodes. The case study results show the path optimization models and algorithms of taxi carpooling proposed in the paper can quickly get the taxi carpooling path, and can increase the income of taxi driver while reduce the cost for passengers

An Extended Car-Following Model at Signalised Intersections

An extended car-following model is proposed on the basis of experimental analysis to improve the performance of the traditional car-following model and simulate a microscopic car-following behaviour at signalised intersections. The new car-following model considers vehicle gather and dissipation. Firstly, the parameters of optimal velocity, generalised force and full velocity difference models are calibrated by measured data, and the problems and causes of the three models are analysed with a realistic trajectory simulation as an evaluation criterion. Secondly, an extended car-following model based on the full optimal velocity model is proposed by considering the vehicle gather and dissipation. The parameters of the new car-following model are calibrated by the measured data, and the model is compared with comparative models on the basis of isolated point data and the entire car-following process. Simulation results show that the optimal velocity, generalised force, and full velocity difference models cannot effectively simulate a microscopic car-following behaviour at signalised intersections, whereas the new car-following model can avoid a collision and has a high fit degree for simulating the measured data of the car-following behaviour at signalised intersections

Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model

A signalized intersection is a high fuel consumption and high emission node of a traffic network. It is necessary to study the emission characteristics of vehicles at signalized intersections in order to reduce vehicle emissions. In this study, the combination of a car-following model and the vehicle specific power emission model was used to estimate the vehicle emissions, including the CO2, CO, HC, and nitric oxide (NOX) emissions, at unsaturated signalized intersections. The results of simulations show that, under the influence of the signal light, the substantial changes in a vehicle’s trajectory increase the CO2, CO, HC, and NOX emissions. The CO2, CO, HC, and NOX emissions from vehicles at signalized intersections were further analyzed in terms of signal timing, vehicle arrival rate, traffic interference, and road section speed. The results show that an increase in the signal cycle, the vehicle arrival rate, and the traffic interference amplitude result in increases in the CO2, CO, HC, and NOX emissions per vehicle at the intersection inbound approach, and an increase in the green signal ratio and the vehicle road section speed within a specified range has a positive significance for reducing the CO2, CO, HC, and NOX emissions of vehicles in the study range. The proposed method can be flexibly applied to the analysis of vehicle emissions at unsaturated signalized intersections. The obtained results provide a reference for the control and management of signalized intersections