Optimization of pedestrian phase patterns at signalized intersections: a multi‐objective approach

This paper presents a multi‐objective optimization model and its solution algorithm for optimization of pedestrian phase patterns, including the exclusive pedestrian phase (EPP) and the conventional two‐way crossing (TWC) at an intersection. The proposed model will determine the optimal pedestrian phase pattern and the corresponding signal timings at an intersection to best accommodate both vehicular traffic and pedestrian movements. The proposed model is unique with respect to the following three critical features: (1) proposing an unbiased performance index for comparison of EPP and TWC by explicitly modeling the pedestrian delay under the control of TWC and EPP; (2) developing a multi‐objective model to maximize the utilization of the available green time by vehicular traffic and pedestrian under both EPP or TWC; and (3) designing a genetic algorithm based heuristic algorithm to solve the model. Case study and sensitivity analysis results have shown the promising property of the proposed model to assist traffic practitioners, researchers, and authorities in properly selecting pedestrian phase patterns at signalized intersections. Copyright © 2013 John Wiley & Sons, Ltd.     

The use of gait parameters to evaluate pedestrian behavior at scramble phase signalized intersections

Pedestrian scramble phasing is usually implemented to reduce pedestrian‐vehicle conflicts and therefore increase the safety of the intersection. However, to adequately determine the benefits of scramble phasing, it is necessary to understand how pedestrians react to such an unconventional design. This study investigates changes in pedestrian crossing behavior following the implementation of a scramble phase by examining the spatiotemporal gait parameters (step length and step frequency). This detailed microscopic‐level analysis provides insight into changes in pedestrian walking mechanisms as well as the effect of various pedestrian and intersection characteristics. The study uses video data collected at a scramble phase signalized intersection in Oakland, California. Gait parameters were found to be influenced by pedestrian gender, age, group size, crosswalk length, and pedestrian signal indications. Both average step length and walking speed were significantly higher for diagonally crossing pedestrians compared with pedestrians crossing on the conventional crosswalks. Pedestrians were found to have the tendency to increase their step length more than their step frequency to increase walking speed. It was also found that, compared with men, women generally increase their walking speed by increasing their step frequency more than step length. However, when in non‐compliance with signal indications, women increase their walking speed by increasing their step length more than step frequency. It was also found that older pedestrians do not significantly change their walking behavior when in non‐compliance with signal indications. Copyright © 2014 John Wiley & Sons, Ltd.     

基于神经网络的无信号路口人车交通行为预测分析

以无信号灯路口人车交通行为为研究对象,对行人和机动车辆在无信号灯路口的整体交通行为进行分类预测。在对路口现场交通情况进行拍摄后,用电脑的分帧技术对所需要的数据进行提取和分类,而后建立BP神经网络模型,确定神经网络的输入变量与输出变量。将样本数据导入神经网络并进行训练和测试后,得出行人和车辆过街类型的分类准确率,并且通过准确率所达到的标准来证明了BP神经网络模型的可行性。     

Developing evasive action‐based indicators for identifying pedestrian conflicts in less organized traffic environments

There has been a growing interest in using surrogate safety measures such as traffic conflicts to analyse road safety from a broader perspective than collision data alone. This growing interest has been aided by recent advances in automated video‐based traffic conflict analysis. The automation enables accurate calculation of various conflict indicators such as time‐to‐collision and post‐encroachment time. These indicators rely on road users getting within specific temporal and spatial proximity from each other and therefore assume that proximity is a surrogate for conflict severity. However, this assumption may not be valid in many driving environments where close interactions between road users are common. The objective of this paper is to investigate the applicability of time proximity conflict indicators for evaluating pedestrian safety in less‐organized traffic environments with a high mix of road users. Several alternative behavioural conflict indicators based on detecting pedestrian evasive actions are recommended to better measure traffic conflicts in such traffic environments. These indicators represent variations in the spatio‐temporal gait parameters (step length, step frequency and walk ratio) immediately before the conflict point. A highly congested shared intersection in Shanghai, China, with frequent pedestrian conflicts is used as a case study. Traffic conflicts are analysed with the use of automated video‐based analysis techniques. The results showed that evasive action‐based indicators have higher potential to identify pedestrian conflicts and measure their severity in high mix less organized traffic environments than time proximity measures such as time‐to‐collision and post‐encroachment time. Copyright © 2016 John Wiley & Sons, Ltd.     

Microscopic modeling of large‐scale pedestrian–vehicle conflicts in the city of Madinah,Saudi Arabia

This paper presents a micro‐simulation modeling framework for evaluating pedestrian–vehicle conflicts in crowded crossing areas. The framework adopts a simulation approach that models vehicles and pedestrians at the microscopic level while satisfying two sets of constraints: (1) flow constraints and (2) non‐collision constraints. Pedestrians move across two‐directional cells as opposed to one‐dimensional lanes as in the case of vehicles; therefore, extra caution is considered when modeling the shared space between vehicles and pedestrians. The framework is used to assess large‐scale pedestrian–vehicle conflicts in a highly congested ring road in the City of Madinah that carries 20 000 vehicles/hour and crossed by 140 000 pedestrians/hour after a major congregational prayer. The quantitative and visual results of the simulation exhibits serious conflicts between pedestrians and vehicles, resulting in considerable delays for pedestrians crossing the road (9 minutes average delay) and slow traffic conditions (average speed <10 km/hour). The model is then used to evaluate the following three mitigating strategies: (1) pedestrian‐only phase; (2) grade separation; and (3) pedestrian mall. A matrix of operational measures of effectiveness for network‐wide performance (e.g., average travel time, average speed) and for pedestrian‐specific performance (e.g., mean speed, mean density, mean delay, mean moving time) is used to assess the effectiveness of the proposed strategies. Copyright © 2012 John Wiley & Sons, Ltd.     

Survey of pedestrians' crossing time at non‐signalized mid‐block street crossing

At non‐signalized mid‐block street crossings in China's cities, pedestrians often weave between motor vehicle flows. This paper investigated the influence patterns of the gender and age of pedestrians, the presence of a pedestrian group, vehicles' interference and the crossing direction on the crossing time at non‐signalized mid‐block street crossings in Changsha, China. The results show that the crossing speed is approximately 1–1.1 m/s; the crossing time increases with increasing age, and the crossing speed of a pedestrian will be quicker when the time gap between the pedestrian and the oncoming vehicle is smaller if he/she decides to cross. This paper also analyzed the crossing time pattern when pedestrians cross lane by lane and found that pedestrians spend the most time crossing the first lane and the least time crossing the middle lane, regardless of whether they are crossing from the curb to the central island or from the central island to the curb. The crossing speed is an important input to the design of pedestrian facilities, so these findings can be applied to the assessment of pedestrian crossing safety in China's cities and can provide a basis for the design of pedestrian crossing facilities. Copyright © 2017 John Wiley & Sons, Ltd.     

A real-time adaptive signal control in a connected vehicle environment

The state of the practice traffic signal control strategies mainly rely on infrastructure based vehicle detector data as the input for the control logic. The infrastructure based detectors are generally point detectors which cannot directly provide measurement of vehicle location and speed. With the advances in wireless communication technology, vehicles are able to communicate with each other and with the infrastructure in the emerging connected vehicle system. Data collected from connected vehicles provides a much more complete picture of the traffic states near an intersection and can be utilized for signal control. This paper presents a real-time adaptive signal phase allocation algorithm using connected vehicle data. The proposed algorithm optimizes the phase sequence and duration by solving a two-level optimization problem. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicle based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Results with a variety of connected vehicle market penetration rates and demand levels are compared to well-tuned fully actuated control. In general, the proposed control algorithm outperforms actuated control by reducing total delay by as much as 16.33% in a high penetration rate case and similar delay in a low penetration rate case. Different objective functions result in different behaviors of signal timing. The minimization of total vehicle delay usually generates lower total vehicle delay, while minimization of queue length serves all phases in a more balanced way.     

Severity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model

The present study intended to (1) investigate the injury risk of pedestrian casualties involved in traffic crashes at signalized intersections in Hong Kong; (2) determine the effect of pedestrian volumes on the severity levels of pedestrian injuries; and (3) explore the role of spatial correlation in econometric crash‐severity models. The data from 1889 pedestrian‐related crashes at 318 signalized intersections between 2008 and 2012 were elaborately collected from the Traffic Accident Database System maintained by the Hong Kong Transport Department. To account for the cross‐intersection heterogeneity, a Bayesian hierarchical logit model with uncorrelated and spatially correlated random effects was developed. An intrinsic conditional autoregressive prior was specified for the spatial correlation term. Results revealed that (1) signalized intersections with greater pedestrian volumes generally exhibited a lower injury risk; (2) ignoring the spatial correlation potentially results in reduced model goodness‐of‐fit, an underestimation of variability and standard error of parameter estimates, as well as inconsistent, biased, and erroneous inference; (3) special attention should be paid to the following factors, which led to a significantly higher probability of pedestrians being killed or sustaining severe injury: pedestrian age greater than 65 years, casualties with head injuries, crashes that occurred on footpaths that were not obstructed/overcrowded, heedless or inattentive crossing, crashes on the two‐way carriageway, and those that occurred near tram or light‐rail transit stops. Copyright © 2017 John Wiley & Sons, Ltd.     

Pedestrian gap acceptance for mid-block street crossing

Abstract

This paper investigates pedestrians' traffic gap acceptance for mid-block street crossing in urban areas. A field survey was carried out at an uncontrolled mid-block location in Athens, Greece. Pedestrians' decisions and traffic conditions were videotaped in terms of the size of traffic gaps rejected or accepted, waiting times and crossing attempts and vehicle speeds. A lognormal regression model was developed to examine pedestrian gap acceptance. It was found that gap acceptance was better explained by the distance from the incoming vehicle, rather than its speed. Other significant effects included illegal parking, presence of other pedestrians and incoming vehicles’ size. A binary logistic regression model was developed to examine the effect of traffic gaps and other parameters on pedestrians' decisions to cross the street or not. The results reveal that this decision is affected by the distance from the incoming vehicles and the waiting times of pedestrians.     

Real-time estimation of turning movement counts at signalized intersections using signal phase information

A variety of sensor technologies, such as loop detectors, traffic cameras, and radar have been developed for real-time traffic monitoring at intersections most of which are limited to providing link traffic information with few being capable of detecting turning movements. Accurate real-time information on turning movement counts at signalized intersections is a critical requirement for applications such as adaptive traffic signal control. Several attempts have been made in the past to develop algorithms for inferring turning movements at intersections from entry and exit counts; however, the estimation quality of these algorithms varies considerably. This paper introduces a method to improve accuracy and robustness of turning movement estimation at signalized intersections. The new algorithm makes use of signal phase status to minimize the underlying estimation ambiguity. A case study was conducted based on turning movement data obtained from a four-leg signalized intersection to evaluate the performance of the proposed method and compare it with two other existing well-known estimation methods. The results show that the algorithm is accurate, robust and fairly straightforward for real world implementation.     

Field implementation feasibility study of cumulative travel‐time responsive (CTR) traffic signal control algorithm

The cumulative travel‐time responsive (CTR) algorithm determines optimal green split for the next time interval by identifying the maximum cumulative travel time (CTT) estimated under the connected vehicle environment. This paper enhanced the CTR algorithm and evaluated its performance to verify a feasibility of field implementation in a near future. Standard Kalman filter (SKF) and adaptive Kalman filter (AKF) were applied to estimate CTT for each phase in the CTR algorithm. In addition, traffic demand, market penetration rate (MPR), and data availability were considered to evaluate the CTR algorithm's performance. An intersection in the Northern Virginia connected vehicle test bed is selected for a case study and evaluated within vissim and hardware in the loop simulations. As expected, the CTR algorithm's performance depends on MPR because the information collected from connected vehicle is a key enabling factor of the CTR algorithm. However, this paper found that the MPR requirement of the CTR algorithm could be addressed (i) when the data are collected from both connected vehicle and the infrastructure sensors and (ii) when the AKF is adopted. The minimum required MPRs to outperform the actuated traffic signal control were empirically found for each prediction technique (i.e., 30% for the SKF and 20% for the AKF) and data availability. Even without the infrastructure sensors, the CTR algorithm could be implemented at an intersection with high traffic demand and 50–60% MPR. The findings of this study are expected to contribute to the field implementation of the CTR algorithm to improve the traffic network performance. Copyright © 2017 John Wiley & Sons, Ltd.     

Accidents involving pedestrians with their backs to traffic or facing traffic: an evaluation of crash characteristics and injuries

This paper examines pedestrian anatomical injuries and crash characteristics in back‐to‐traffic and facing‐traffic crashes. Pedestrian crashes involving pedestrians walking along streets (i.e. with their backs to traffic or facing traffic) have been overlooked in literature. Although this is not the most frequent type of crash, the crash consequence to pedestrians is a safety concern. Combining Taiwan A1A2 police‐reported accident data and data from the National Health Insurance Database from years 2003–2013, this paper examines anatomical injuries and crash characteristics in back‐to‐traffic and facing‐traffic crashes. There were a total of 830 and 2267 pedestrian casualties in back‐to‐traffic and facing‐traffic crashes respectively. The injuries sustained by pedestrians and crash characteristics of these two crash types were compared with those of other crossing types of crashes (nearside crash, nearside dart‐out crash, offside crash, and offside dart‐out crash). Odds of various injuries to body regions were estimated using logistic regressions. Key findings include that the percentage of fatalities in back‐to‐traffic crashes is the highest; logistic models reveal that pedestrians in back‐to‐traffic crashes sustained more head, neck, and spinal injuries than did pedestrians in other crash types, and unlit darkness and non‐built‐up roadways were associated with an increased risk of pedestrian head injuries. Several crash features (e.g. unlit darkness, overtaking manoeuvres, phone use by pedestrians and drivers, and intoxicated drivers) are more frequently evident in back‐to‐traffic crashes than in other types of crashes. The current research suggests that in terms of crash consequence, facing traffic is safer than back to traffic. Copyright © 2016 John Wiley & Sons, Ltd.     

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Vehicle actuated signal performance under general traffic at an isolated intersection

We study green extension of a two-phased vehicle actuated signal at an isolated intersection between two one-way streets. The green phase is extended by a preset time interval, referred to as critical gap, from the time of a vehicle actuation at an advance detector. The green phase switches if there is no arrival during the critical gap. We develop an exact model to study the intersection performance with traffic following Poisson processes. We further extend the model to approximate the case of general traffic. Our model in the general case works well compared with Monte Carlo simulation. A few major observations include: (1) The optimal critical gap decreases with the traffic; (2) The optimal critical gap can be much larger (up to 5 s) than the common presumption of 2–3 s; (3) Queue clearance policy is not nearly optimal in general even in the case of heavy traffic.     

Prohibited–permitted right-turn phasing strategy based on capacity analysis of right-turn movements

In traffic-crowded metropolitan areas, such as Shanghai and Beijing in China, right-turn vehicles that operate with a permitted phase at signalized intersections are normally permitted to filter through large numbers of pedestrians and bicycles. To alleviate such conflicts and improve safety, traffic engineers in Shanghai introduced a prohibited–permitted right-turn operation, adding a subphase to the permitted phase in which right-turns are prohibited. Unfortunately, the prohibited subphase would reduce the capacity of right-turn movements when it prohibits right turns even if there are few pedestrians and bicycles crossing the street. This paper aims at quantifying the impact of both non-vehicular flows and the prohibited subphase on the right-turn capacity, and then proposes a strategy to determine appropriate prohibited–permitted right-turn operation that minimizes the capacity reduction caused by the prohibited subphase. To achieve this goal, we improved the pedestrian and bicycle adjustment factor described in the Highway Capacity Manual by taking into account: (1) the variety in space competition between pedestrians and bicycles, and (2) the effect of two conflict zones in each phase on right-turn operation. In addition, we revised the capacity estimation model in the Highway Capacity Manual, and developed a model based on bicycle/pedestrian volume fluctuation to describe the capacity reduction due to both non-vehicular flows and the prohibited subphase. Furthermore, we proposed a timing strategy for the onset and duration of appropriate prohibited subphase. When bicycle and pedestrian volumes are low, the actuated strategy turns to the permitted phase. When these volumes are moderate, the strategy turns to the prohibited–permitted operation. With the volumes increasing, the prohibited subphase onset advances and duration increases. In these two scenarios, the new strategy has higher right-turn capacity than the current pretimed prohibited–permitted operation. Unfortunately, when bicycle and pedestrian volumes are high, the strategy yields similar right-turn capacity. However, the new prohibited subphase has less potential vehicle–bicycle and vehicle–pedestrian conflicts.     

A model of pedestrians’ intended waiting times for street crossings at signalized intersections

For the purposes of both traffic-light control and the design of roadway layouts, it is important to understand pedestrian street-crossing behavior because it is not only crucial for improving pedestrian safety but also helps to optimize vehicle flow. This paper explores the mechanism of pedestrian street crossings during the red-man phase of traffic light signals and proposes a model for pedestrians’ waiting times at signalized intersections. We start from a simplified scenario for a particular pedestrian under specific traffic conditions. Then we take into account the interaction between vehicles and pedestrians via statistical unconditioning. We show that this in general leads to a U-shaped distribution of the pedestrians’ intended waiting time. This U-shaped distribution characterizes the nature of pedestrian street-crossing behavior, showing that in general there are a large proportion of pedestrians who cross the street immediately after arriving at the crossing point, and a large proportion of pedestrians who are willing to wait for the entire red-man phase. The U-shaped distribution is shown to reduce to a J-shaped or L-shaped distribution for certain traffic scenarios. The proposed statistical model was applied to analyze real field data.     

Modeling pedestrians’ road crossing behavior in traffic system micro-simulation in China

In many Chinese cities, pedestrian’s road crossing behavior is different from that of pedestrians in developed countries. This paper presents a pedestrian model for traffic system micro-simulation in China. Considering the high rate of signal non-compliance, we classify pedestrians into two types: law-obeying ones and opportunistic ones. Opportunistic ones decide whether to violate traffic signal during red man, depending on the states of some external factors (like policeman, vehicle flow and other pedestrians’ behaviors). Questionnaires were used to determine the proportions of these two types of pedestrians under different circumstances. In addition, a time gap distribution extracted from videotape were used to determine the criterion for pedestrians to decide whether to walk or wait when they conflict with vehicle flows. However, simulation results deviate from the data extracted from videotape in some degree. By adjusting the parameters on the basis of analyzing the occurrence of the deviations, the simulation results agree with the field results better. This model has represented the high rate of pedestrians’ red light running and the mixed characteristics of traffic flows in Chinese cities, and it may be applicable in the micro-simulation of traffic system in other developing cities.     

Driver's braking behavior approaching pedestrian crossings: a parametric duration model of the speed reduction times

The driver's braking behavior while approaching zebra crossings under different safety measures (curb extensions, parking restrictions, and advance yield markings) and without treatment (baseline condition) was examined. The speed reduction time was the variable used to describe the driver's behavior. Forty‐two drivers drove a driving simulator on an urban scenario in which the baseline condition and the safety measures were implemented. The speed reduction time was modeled with a parametric duration model to compare the effects on driver's braking behavior of vehicle dynamic variables and different countermeasures. The parametric accelerated failure time duration model with a Weibull distribution identified that the vehicle dynamic variables and only the countermeasure curb extensions affected, in a statistically significant way, the driver's speed reduction time in response to a pedestrian crossing. This result shows that the driver, because of the improved visibility of the pedestrian allowed by the curb extensions, was able to receive a clear information and better to adapt his approaching speed to yield to the pedestrian, avoiding abrupt maneuvers. This also means a reduction of likelihood of rear‐end collision due to less aggressive braking. Copyright © 2016 John Wiley & Sons, Ltd.     

Modeling the effect of electric vehicle adoption on pedestrian traffic safety: An agent-based approach

When operated at low speeds, electric and hybrid vehicles have created pedestrian safety concerns in congested areas of various city centers, because these vehicles have relatively silent engines compared to those of internal combustion engine vehicles, resulting in safety issues for pedestrians and cyclists due to the lack of engine noise to warn them of an oncoming electric or hybrid vehicle. However, the driver behavior characteristics have also been considered in many studies, and the high end-prices of electric vehicles indicate that electric vehicle drivers tend to have a higher prosperity index and are more likely to receive a better education, making them more alert while driving and more likely to obey traffic rules. In this paper, the positive and negative factors associated with electric vehicle adoption and the subsequent effects on pedestrian traffic safety are investigated using an agent-based modeling approach, in which a traffic micro-simulation of a real intersection is simulated in 3D using AnyLogic software. First, the interacting agents and dynamic parameters are defined in the agent-based model. Next, a 3D intersection environment is created to integrate the agent-based model into a visual simulation, where the simulation records the number of near-crashes occurring in certain pedestrian crossings throughout the virtual time duration of a year. A sensitivity analysis is also carried out with 9000 subsequent simulations performed in a supercomputer to account for the variation in dynamic parameters (ambient sound level, vehicle sound level, and ambient illumination). According to the analysis, electric vehicles have a 30% higher pedestrian traffic safety risk than internal combustion engine vehicles under high ambient sound levels. At low ambient sound levels, however, electric vehicles have only a 10% higher safety risk for pedestrians. Low levels of ambient illumination also increase the number of pedestrians involved in near-crashes for both electric vehicles and combustion engine vehicles.     

Optimal control strategies with an extended cell transmission model for massive vehicular‐pedestrian mixed flows in the evacuation zone

This paper presents an integrated model to design routing and signal plans for massive mixed pedestrian‐vehicle flows within the evacuation zone. The proposed model, with its embedded formulations for pedestrians and vehicles in the same evacuation network, can effectively take their potential conflicts into account and generate the optimal routing strategies to guide evacuees toward either the pickup locations or their parking areas during an evacuation. The proposed model, enhancing the cell transmission model with the notion of sub‐cells, mainly captures the complex movements in the vehicle‐pedestrian flows and can concurrently optimizes both the signals for pedestrian‐vehicle flows and the movement paths for evacuees. An illustrating example concerning the evacuation around the M&T Bank Stadium area has been used to demonstrate the application potential of the proposed model. Copyright © 2013 John Wiley & Sons, Ltd.