This paper studies a frequent violation at multi-phase signal intersection of Beijing, that large number of pedestrians twice crossing street in the left-turn phase. Based on a large number of measured data, the influence of this violation on intersection safety is analyzed by using the theory of traffic conflict. To solve the violation, some strategy and methods have also been summarized. As an important link in City Road system and a crucial section of the whole road net, the intersections in the city act as the nodes connecting the crossing roads and control the vehicle volume. Due to the complexity of traffic participants and the high concentration of traffic flow, traffic accidents are very liable to occur in the crossings. According to the traffic accident statistics in China (2008), there are 46148 traffic accidents in crossings, taking account of 17.40% of the total number of the traffic accidents and leading to 9549 death. (Ministry of Public Security, 2009) Therefore the studies on the influence factors of crossings safety have been considered as an urgent need. Multi-phase signal has been adopted in increasing amount as an effective method to improve the traffic safety. In this system, the left-turn phase is put forward to separate the straight flow and left-turn flow to different time sections, thus to decrease the traffic confliction points. However, the implementation of left-turn phrase will to some extent extend the waiting time for the pedestrians passing through the streets. The pedestrians are likely to break the traffic rules and cross the roads regardless of the traffic signal if the waiting time is too long or the waiting crowd has reached saturation. Normally they no longer cross the road along with straight flow, but first move to the side-sections of left-turn lanes, then go across the intersection by taking the gaps between left-turn flow and wait until left-turn phase finishes. (Shown in Figure.1) The violation of signal will lead to more conflicts between vehicles and pedestrians hence have a negative influence on the whole safety issues.
Acceleration of the urbanization process and sustained development of the economy have brought tremendous pressure on today's road transportation system. The road capacity of cities has not been able to meet the increasing traffic demand. In order to solve the problem of urban traffic congestion, the study of the impact of community opening on the surrounding road traffic flow has a profound impact on the solution of this problem and the significance of the research. In this paper, the traffic flow evaluation system is established using the analytic hierarchy process to analyze the changes of surrounding road traffic flow before and after the opening of the community. The circle extrapolation method is used to redistribute the surrounding road traffic flow after opening. Through the systematic analysis of the evaluation system, it is concluded that the opening of the community has a positive mitigation effect on the surrounding road traffic flow.
The operational efficiency of urban expressways significantly impacts citywide transportation flow. During morning and evening rush hours, the limited capacity of feeder roads to handle high traffic volumes leads to congestion on expressway exit ramps. This often results in queuing and, in severe cases, ramp spillback, causing traffic bottlenecks on the expressway lanes and substantial losses in traffic travel. This study utilizes deep reinforcement learning algorithms for traffic signal control optimization at exit ramps associated with intersection crossings. Traffic signals are treated as intelligent agents, and real-time traffic conditions of the expressway ramps and intersections are fed into the system using detectors. A dynamic reward function is introduced, adjusted based on the ratio of the remaining traffic capacity between the feeder roads and the exit ramps. The objective is to enhance ramp traffic efficiency while optimizing intersection signals. The methodology is applied to an expressway on East Third Ring Road, Beijing, and a related intersection, which utilizing the simulation of urban mobility (SUMO) traffic simulation platform and the Traci library to create a simulated environment. The results indicate that the signal control method, based on an improved advantage actor critic (A2C) algorithm, outperforms traditional signal controls and those based on the deep Q-network (DQN) algorithm. Especially during peak travel times, it effectively reduces the probability of ramp spillback and enhances the traffic efficiency of the interconnected feeder road intersections.
Abstract Vehicle driving conditions at high altitudes are quite different from those in plain areas. Accurately predicting the speed of vehicles traveling at high altitudes is of great significance for the development of vehicle safety assisted driving. In order to study the vehicles’ speed of highways in high-altitude areas, and predict the speed of vehicles accurately, more than 30 000 data were collected by a medium-sized SUV in Qinghai under typical adverse environmental conditions. The real-time vehicle status data (engine speed, engine torque, transmission gear, throttle opening), road alignment data, and historical vehicle speed data was denoised by wavelet method. The collecting data is time-varying and nonlinear characteristics. A nonlinear auto-regression with exogenous inputs (NARX) dynamic neural network prediction model was established in this paper to fit travel speed. The network model after training has small error and high fitting degree. The accuracy of vehicle speed prediction in the next five seconds is 96.01%. The root mean square error of prediction is less than 2.21 km/h, which can achieve better prediction effect. At the same time, the transplantability of the model is enhanced by taking altitude and road alignment as variables.
Models,which employ panel data analysis to model highway crashes,can identify fixed differences and other unobserved factors in real world.This paper introduces process of individual fixed-effects and random-effects models and related tests.These models are applied to Jingjintang highway.Pool data regression,models of fixed effects and random effects are established respectively.Hausman results show that fixed-effect model is better than others when describing the relationship between accidents and other factors.
With the number of motor vehicles rapidly increasing, urban parking has become an intolerable problem in major cities in China. Parking facility service evaluations play an important role in urban transportation planning and operation. This paper introduces a level of service (LOS) concept based on a comprehensive parking study in Beijing, China. The LOS methodology developed by an integrated evaluation model reflects the user's perception of the quality of service. The method combines four important service variables, namely the ratio of peak-hour demand to capacity, average parking space occupying rate, parking cost, and circulation time, into one single index to quantitatively evaluate a parking facility's performance.
It is difficult to analyze operating speed on freeways using current vehicle classification schemes because of less maneuverability and ambiguous boundaries.Based on the relationship between speed and wheelbase on the investigated sections,a new vehicle classification scheme is presented in this paper,using cluster analysis method by the wheelbase.All vehicles are separated into 3 categories depending on wheelbase: small vehicles,the wheelbases of which are not more than 5 meters;medium vehicles,more than 5 meters and less than or equal to 10.5 meters;and large vehicles,more than 10.5 meters.In this vehicle classification scheme,the 3 categories have distinct speed distributions which can describe the operating speed better.
Mixed traffic is a significant feature of Chinese traffic flow on urban street network, which is also a major cause of traffic congestion and frequent traffic accidents. In sections where motor vehicles and non-motor vehicles moving in same direction without separation, they would interfere with each other. This interference has serious impact on the capacity of sections, and simultaneously increases the accident risk. This paper analyzed the data through the method of probability theory and statistics, and got the result that "the number of non-motor vehicles and the lateral distant between motor vehicles and non-motor vehicles are both interference factors aroused by non-motor vehicles". Finally, non-motor vehicles' disturbance model to the motor vehicles were set up based on data analysis and proved to be correctly. The research provided a theoretical and basis to the traffic safety management under the mixed traffic environment.
In recent years,speed reduction markings have been widely used in urban roads and expressway in China.The current criterion has not owned a uniform standard of design and application,so setting speed reduction markings is hard to reach the object of management control and safety guarantee.This article explores the practical application of speed reduction markings both drivers and detecting datas,it may provide some references for traffic managers and engineer designers to set speed reduction markings.
Understanding parking choice behaviour is important in parking facility design and service evaluation. Lack of sufficient studies on parking choice behaviour investigation has been an issue in parking facility planning in China. Using six parking facilities in Beijing Lama Temple as an example, this paper investigates the parking behaviour at the tourist site. Based on the data collected at these six parking facilities through a stated-preference survey, a multinomial logit model was developed, which reveals the relationship between parking decision and influential factors.
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