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A new car-following model considering velocity anticipation

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Chinese Physics B 2010年第1期19卷 197-203页

作者：田钧方贾斌李新刚高自友 MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University

The full velocity difference model proposed by Jiang et al. [2001 Phys. Rev. E 64 017101] has been improved by introducing velocity anticipation. Velocity anticipation means the follower estimates the future velocity of the leader. The stability condition of the new model is obtained by using the linear stability theory. Theoretical results show that the stability region increases when we increase the anticipation time interval. The mKdV equation is derived to describe the kink-antikink soliton wave and obtain the coexisting stability line. The delay time of car motion and kinematic wave speed at jam density are obtained in this modeh Numerical simulations exhibit that when we increase the anticipation time interval enough, the new model could avoid accidents under urgent braking cases. Also, the traffic jam could be suppressed by considering the anticipation velocity. All results demonstrate that this model is an improvement on the full velocity difference model.

关键词： car-following traffic flow velocity anticipation

Driving decision-making analysis of car-following for autonomous vehicle under complex urban environment

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Journal of Central South University 2017年第6期24卷 1476-1482页

作者：陈雪梅金敏苗一松张强 School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

The decision-making under complex urban environment become one of the key issues that restricts the rapid development of the autonomous vehicles. The difficulty in making timely and accurate decisions like human beings under highly dynamic traffic environment is a major challenge for autonomous driving. car-following has been regarded as the simplest but essential driving behavior among driving tasks and has received extensive attention from researchers around the world. This work addresses this problem and proposes a novel method RSAN(rough-set artificial neural network) to learn the decisions from excellent human drivers. A virtual urban traffic environment was built by Pre Scan and driving simulation was conducted to obtain a broad set of relevant data such as experienced drivers' behavior data and surrounding vehicles' motion data. Then, rough set was used to preprocess these data to extract the key influential factors on decision and reduce the impact of uncertain data and noise data. And the car-following decision was learned by neural network in which key factor was the input and acceleration was the output. The result shows the better convergence speed and the better decision accuracy of RSAN than ANN. Findings of this work contributes to the empirical understanding of driver's decision-making process and it provides a theoretical basis for the study of car-following decision-making under complex and dynamic environment.

关键词： autonomous vehicle car-following decision-making rough set (RS) artificial neural network (ANN) PreScan

Numerical Simulation of Motor Vehicles’ Courtesy Behavior on Crosswalk Based on car-following Model

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Journal of Beijing Institute of Technology 2019年第3期28卷 570-576页

作者： Baojie Wang Xiangbei Xue Xiaoli Xie School of Highway Chang’an University

In observing driver courtesy towards pedestrians at unsignalized crosswalks, a behavioral model was adopted in a simulation based on the GM car-following Model. The SIMI Motion Software was used to extract the vehicle operation data from Wenyi South Road and Hanyuan Road in Xi'an City. The parameters of the GM car-following Model were calibrated by genetic algorithm. The road simulation environment based on the car-following Model was constructed by MATLAB. In the case of no stopping, uniform deceleration avoidance with advance notice, emergency brake avoidance without advance notice, changes such as the displacement of the car-following queue, headway, speed, acceleration, and deceleration were analyzed by numerical simulation. The results show that when there is advance notice before the crosswalk, the minimum headway distances of car1-car2, car2-car3, car3-car4 and car4-car5 are 7.09 m, 7.38 m, 7.65 m, 7.91 m, and the average rates of change of the headway during deceleration are 0.78 m/s, 0.74 m/s, 0.71 m/s, 0.68 m/s respectively;in the absence of advance notice before the crosswalk, the minimum headway distances of car1-car2, car2-car3, car3-car4 and car4-car5 are 7.28 m, 7.75 m, 8.19 m, 8.59 m, and the average rates of change of the headway during deceleration are 1.57 m/s, 1.25 m/s, 1.04 m/s, 0.96 m/s, respectively. Therefore, in order to effectively prevent the occurrence of vehicle rear-end events, it's necessary to set traffic signs and markings on the preceding section of the intersection or road exhibiting behavioral comity.

关键词： car-following Model crosswalk numerical simulation behavioral comity

Incorporating vehicle mix in stimulus-response car-following models

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Journal of Traffic and Transportation Engineering(English Edition) 2016年第3期3卷 226-235页

作者： Saidi Siuhi Mohamed Kaseko Department of Civil Engineering Abu Dhabi University Department of Civil and Environmental Engineering University of Nevada

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.

关键词： car-following Stimulus-response Acceleration/deceleration Vehicle mix Driver response time lag

car-following MODEL BASED ON DRIVING BEHAVIOR AND RESEARCH ON THE STABILITY OF THE MODEL

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CAR-FOLLOWING MODEL BASED ON DRIVING BEHAVIOR AND RESEARCH O...

Impact of next-nearest leading vehicles on followers’ driving behaviours and traffic stability in mixed traffic

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作者： Hao-Ran Zhang1 2 Wei Wang3 and Gang Ren4 1School of Transportation Southeast University Postcode: 210096 Nanjing Jiangsu China 2China Highway Planning and Design Institute (HPDI) Consultants INC. Postcode:100010 Beijing China 3School of Transportation Southeast University Postcode: 210096 Nanjing Jiangsu China 4School of Transportation Southeast University Postcode: 210096 Nanjing Jiangsu China

Established car-following model based on driving behavior, and look forward to be applied in traffic simulation, traffic safety and intelligent transport control. Researched on different driving behavior and established car-following model correspondingly. By analyzing the model, determined the reasonable value range of the parameters and simulated various car-following processes. The car-following model established based on driving behavior can simulate actual driving behavior precisely. The value range of parameters of car-following models established according to different driving behavior is different. Different driving behavior requires different safe headway. When the values of the parameter exceed the rational range, the corresponding car-following behavior is unsafely. We drew the conclusion by simulation of car-following motorcade: taking safe time headway as definition of safe headway is superior to using safe space headway;vehicles in fluctuant motorcade must keep longer safe headway than in stable motorcade;the accelerating or decelerating performance of vehicles has small influence to safe headway;vehicles have better accelerating performance must keep longer safe headway, and vehicle has worse decelerating performance requires longer safe headway.

关键词： traffic safety traffic simulation driving behavior car-following car-following model safe headway

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Journal of Traffic and Transportation Engineering(English Edition) 2020年第1期7卷 42-51页

作者： Akihito Nagahama Daichi Yanagisawa Katsuhiro Nishinari Ritsumeikan Global Innovation Research Organization Ritsumeikan UniversityKusatsu 525-8577Japan Research Center for Advanced Science and Technology The University of TokyoTokyo 153-8904Japan

There has been an increase in the number of on-road vehicles of all types,especially in some developing countries.The rise of traffic heterogeneity causes larger mixed traffic conge stion.This study examines the impact of next-nearest leading vehicles on the driving of following drivers in mixed traffic.Although previous studies reported that traffic stability can be improved with the introduction of followers’anticipatory driving that refers to multiple leaders,the effect of anticipatory driving on mixed traffic has not yet been examined.Using data collected from experiments conducted with groups of two and three vehicles,we found that operational delay,maximum acceleration and deceleration of the followers were affected by the presence of next-nearest leaders.In addition,we developed regression models of the affected followers’behaviours with respect to the next-nearest leaders and identified the factors affecting these behaviours.For example,the followers’deceleration is directly affected by the height of the next-nearest leading vehicles.Hence,the model parameters for determining the deceleration of following vehicles should take the height of the next-nearest leading vehicle into consideration.Finally,based on the regression models,we estimated values of parameters in the intelligent driver model when the type of the next-nearest leader was changed.Stability analysis based on these estimated parameters implied that a tall or short next-nearest leader with a large engine power would stabilise traffic when anticipatory driving of followers is possible.

关键词： Transportation engineering Mixed traffic car-following behaviour Next-nearest leader Traffic stability Intelligent driver model

Simulating bicycle traffic by the intelligent-driver model-Reproducing the traffic-wave characteristics observed in a bicycle-following experiment

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Journal of Traffic and Transportation Engineering(English Edition) 2020年第1期7卷 19-29页

作者： Valentina Kurtc Martin Treiber Institute of Applied Mathematics and Mechanics Peter the Great St.Petersburg Polytechnic UniversitySt.Petersburg 195251Russia Institute for Transport and Economics Technische Universitat DresdenDresden 01062Germany

Bicycle traffic operations become increasingly important and yet are largely ignored in the traffic flow community,until recently.We hypothesize that there is no qualitative difference between vehicular and bicycle traffic flow dynamics in single-file case,so the latter can be described by reparameterized car-following models.To test this proposition,we reproduce German(Andresen et al.,2014)and Chinese(Jiang et al.,2016)bicycle experiments on a ring with the intelligent-driver model(IDM)and compare its fit quality(calibration)and predictive power(validation)with that of the necessary-deceleration-model(NDM),which is specifically designed for bike traffic.We find similar quality metrics for both models,so the above hypothesis of a qualitative equivalence cannot be rejected.Moreover,calibration errors of the IDM turn up to be slightly smaller compared to the NDM ones.The NDM represents significant calibration errors for high flow densities,which correspond to flow states,when stop-and-go wave emerge.According to validation tests,the IDM outperforms the NDM as well.Performing two types of validation techniques we discover that inter-driver variation is much higher than the intra-driver variation for bicycle traffic.It coincides with the results obtained from vehicular traffic experiments(NGSIM trajectory data).In addition,we suggest the measure for quantitative comparison of two microscopic fundamental diagrams,which are derived from experimental data and simulated trajectories.The analysis of speed-density relations provides more or less the same results for both models.

关键词： Bicycle traffic car-following model Stop-and-go waves Calibration Validation Fundamental diagram

A new dynamics model for traffic flow

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Chinese Science Bulletin 2001年第4期46卷 345-349页

作者： Rui Jiang Qingsong Wu Zuojin Zhu Univ Sci & Technol China Inst Engn Sci Hefei 230026 Peoples R China

As a study method of traffic flow, dynamics models were developed and applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using car-following theory and the usual connection method of micro-macro variables, which can overcome some ubiquitous problems in the existing models. Numerical results show that the new model can very well simulate traffic flow conditions, such as congestion, evacuation of congestion, stop-and-go phenomena and phantom jam.

关键词： traffic flow dynamics model car-following model.

Deep Reinforcement Learning Based Truck Eco-Driving in Mixed Traffic Utilizing Terrain Information

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Deep Reinforcement Learning Based Truck Eco-Driving in Mixed...