Simulation Model For Pedestrian Flow At Signalized Crosswalk And Its Application

Walking is the oldest and most fundamental mode of trip, and serves as the origination and end of every trip. Recently, the pedestrian traffic at signalized intersection is a challenging subject and has attracted a lot of attentions from transportation professionals and engineers. When pedestrians cross the signalized intersection, they are protected from the vehicular flow with the pedestrian traffic signal and signs. However, the pedestrian-vehicle conflict can’t be totally resolved due to the permitted turning right/left phase. Moreover, generally, pedestrians assemble in platoons at each side of the crosswalk during the red time and will conflict with each other when crossing. The prime objective of this paper is to develop a reliable simulation model for pedestrian flow at signalized crosswalks and further to provide its application on the proper design of the crosswalk geometry and pedestrian signal time setting. To achieve it, this study investigated the characteristic of pedestrian crossing traffic with an abundant of field data. A reliable microscopic simulation model for pedestrian flow at signalized intersection was proposed, calibrated and validated with real-world data, which has the potential to serve as a practical tool for assessing safety performance and traffic operations at existing facilities.As an initial step, it is very critical to understand the characteristics of pedestrian traffic at signalized intersection. An innovative methodology to obtain and extract the pedestrian crossing characteristics from pedestrian trajectory data is proposed. With the application of developed pedestrian tracking software, the time stamp, location information of every pedestrian can be output automatically. The algorithm for crossing time, speed and delay calculation is then used to analyze the pedestrian crossing characteristics. The Jingxiahe Road-Xuefu Road, Dashiqiao Street-Danfeng Street, Dashiqiao Street-Zhongshan Road, Wenshu East Road-Xueheng Road are selected for investigation sites. It turns out that the bi-direction pedestrian flow is unbalanced and the pedestrian arrival pattern follows passion distribution. What’s more, the crossing time data exhibit strong positive skew and long upper tail and follow the buff distribution. Meanwhile, the crossing speed data owns the similar pattern. The pedestrian delay data demonstrate the extreme positive skew and long tail and obey the GPD distribution. Also, the pedestrian will experience about 2.23-4.74s delay when conflicting with vehicles.Based on the analysis of pedestrian crossing characteristics, a simulation model for pedestrian flow at signalized intersection is proposed in Chapter 4. The improved cellular automaton simulation model incorporates social forces which are driven force, the pedestrian interaction force and repulsive force from boundary to describe the local rule of pedestrian movement. The model is calibrated with field data. Comparisons about the crossing time, the crossing time distribution, the pedestrian local density level obtained from the simulation and real-world are conducted to demonstrate the validity of the simulation model. Additionally, the simulation results indicate that pedestrian crossing procedure can be mainly divided into four stages according to the state of pedestrian flow operation. First stage:the waiting pedestrians in the platoons start to walk from the front to the rear in a sequential way and the pedestrian platoons are elongated; Second stage: pedestrian platoons have stretched out completely and the headways between pedestrians are large enough to allow people walking at a free speed; Third stage:the dominant and the opposite pedestrian platoons encounter in the crosswalk, then keep going and departure away from each other; Fourth stage:the two separated pedestrian platoons walk to the destined side of the crosswalk. Correspondingly, the speed evolution curves share four fluctuation intervals corresponding to the four stages defined above. Further, it is found that the speed evolution curve is correlated to the pedestrian platoon size and crosswalk width.With the consideration that pedestrian will interact with vehicles when the right or left turning phase is permitted, a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at signalized crosswalks in a realistic way is developed in Chapter 5. The model is calibrated with detailed behavioral data collected and extracted from field observations. Data from three field-observation sites in the city of Nanjing, China are applied to illustrate the calibration process. With the calibrated model, we are able to demonstrate the capability of the model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the model is applicable and valuable for pedestrian, safety evaluation. In these contexts, the developed simulation model has the potential to serve as a practical tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing. With parameter sensitivity analysis, it turns out that the conflict rate is correlated to vehicle volume yielding rate. Moreover, the average pedestrian crossing delay incured by pedestrian-vehicle conflict is relative small. The spatiotemporal diagrams for vehicle flow under various pedestrian volumes illustrate that when pedestrian volume exceed 1290ped/h, the queue of turning vehicles will formulate before the crosswalk.Finally, Chapter 5 presents a new approach for specifying the design of the signalized crosswalk width. Based on the analysis of the characteristics of bi-direction pedestrian flows at the subject signalized crosswalk, a crossing time (CT) estimation model is proposed and developed by taking the time lag of pedestrian platoons as well as bi-direction effects into consideration. Subsequently, two important indicators (proportion of delay in the crossing time, i.e. PDC, and local density level, i.e. LDL) are introduced into the evaluation of pedestrian crossing efficiency and comfort level respectively. It is shown in our work that CT, PDC, and LDL can be successfully obtained with the implementation of cellular automaton into the pedestrian simulation model by incorporating social forces (SFCA). Moreover, the relationships among CT, PDC, and LDL as well as the crosswalk width and pedestrian demand are modeled and illustrated. By synthesizing all indicators, a method is introduced to determine the recommended maximum and minimum widths for signalized crosswalks under different pedestrian demand volumes. Our methodologies demonstrate that they may help traffic engineers and specialists make a sensible choice of the crosswalk width. The outcome of our work will further give traffic engineers and practitioners new insights for the design and planning of signalized pedestrian crosswalks and constitute an important contribution to the understanding and evaluation of pedestrian movements in this aspect. To facility application, the proposed simulation model is embedded into the MATLAB GUI platform. The pedestrian simulation software can output the figures of pedestrian flow operation and local density level in real-time as well as the indicators for efficiency, comfortable and safety of pedestrian crossing traffic. At last, a case study of the crosswalk at Hongwu road-Huaihai road intersection is presented to illustrate the application of the software on crosswalk width design and phase time setting.