Journal articles on the topic 'Travel time (Traffic engineering) – Toronto – Case studies'

In populated cities with high traffic congestion, traffic information may play a key role in choosing the fastest route between origins and destinations, thus saving travel time. Several research studies investigated the effect of traffic information on travel time. However, little attention has been given to the effect of traffic information on travel time according to trip distance. This paper aims to investigate the relation between real-time traffic information dissemination and travel time reduction for medium-distance trips. To examine this relation, a methodology is applied to compare travel times of two types of vehicle, with and without traffic information, travelling between an origin and a destination employing probe vehicles. A real case study in the metropolitan city of Tehran, the capital of Iran, is applied to test the methodology. There is no significant statistical evidence to prove that traffic information would have a significant impact on travel time reduction in a medium-distance trip according to the case study.

Due to increasing traffic demand, many metropolitan areas are experiencing extensive traffic congestion, which demands for efficient traffic signal timing and optimization. However, conventional efficiency measure-based signal optimization cannot handle the ubiquitous uncertainty in the road networks, demanding for the incorporation of reliability measures into signal optimization, which is still in its early stage. Therefore, targeting this issue, based on the recent studies on recognizing travel time reliability (TRR) as an important reliability measure of road networks, a travel time reliability-based urban road traffic network signal timing optimization model is proposed in this paper, with the objective function to optimize a TTR measure, i.e., buffer time index. The proposed optimization model is solved using the heuristic particle swarm optimization approach. A case study is conducted using microscopic traffic simulation for a road network in the City of Nanjing, China. Results demonstrate that the proposed optimization model can improve travel time reliability of the road traffic network and the efficiency of the road traffic network as well. Future studies are recommended to expand the integration of travel time reliability into traffic signal timing optimization.

Traffic congestion costs drivers an average of $1,200 a year in wasted fuel and time, with most travelers becoming less tolerant of unexpected delays. Substantial efforts have been made to account for the impact of non-recurring sources of congestion on travel time reliability. The 6th edition of the Highway Capacity Manual (HCM) provides a structured guidance on a step-by-step analysis to estimate reliability performance measures on freeway facilities. However, practical implementation of these methods poses its own challenges. Performing these analyses requires assimilation of data scattered in different platforms, and this assimilation is complicated further by the fact that data and data platforms differ from state to state. This paper focuses on practical calibration and validation methods of the core and reliability analyses described in the HCM. The main objective is to provide HCM users with guidance on collecting data for freeway reliability analysis as well as validating the reliability performance measures predictions of the HCM methodology. A real-world case study on three routes on Interstate 40 in the Raleigh-Durham area in North Carolina is used to describe the steps required for conducting this analysis. The travel time index (TTI) distribution, reported by the HCM models, was found to match those from probe-based travel time data closely up to the 80th percentile values. However, because of a mismatch between the actual and HCM estimated incident allocation patterns both spatially and temporally, and the fact that traffic demands in the HCM methods are by default insensitive to the occurrence of major incidents, the HCM approach tended to generate larger travel time values in the upper regions of the travel time distribution.

Bluetooth (BT) time-stamped media access control (MAC) address data have been used for traffic studies worldwide. Although Bluetooth (BT) technology has been widely recognised as an effective, low-cost traffic data source in freeway traffic contexts, it is still unclear whether BT technology can provide accurate travel time (TT) information in complex urban traffic environments. Therefore, this empirical study aims to systematically evaluate the accuracy of BT travel time estimates in urban arterial contexts. There are two major hurdles to deriving accurate TT information for arterial roads: the multiple detection problem and noise in BT estimates. To date, they have not been fully investigated, nor have well-accepted solutions been found. Using approximately two million records of BT time-stamped MAC address data from twenty weekdays, this study uses five different BT TT-matching methods to investigate and quantify the impact of multiple detection problems and the noise in BT TT estimates on the accuracy of average BT travel times. Our work shows that accurate Bluetooth-based travel time information on signalised arterial roads can be derived if an appropriate matching method can be selected to smooth out the remaining noise in the filtered travel time estimates. Overall, average-to-average and last-to-last matching methods are best for long (>1 km) and short (≤1 km) signalised arterial road segments, respectively. Furthermore, our results show that the differences between BT and ground truth average TTs or speeds are systematic, and adding a calibration is a pragmatic method to correct inaccurate BT average TTs or speeds. The results of this research can help researchers and road operators to better understand BT technology for TT analysis and consequently to optimise the deployment location and configuration of BT MAC address scanners.

Performance measurement refers to attempts to quantify some aspect of the performance of an organization. A study was conducted to analyze needs, opportunities, and techniques for measuring performance of transportation management centers (TMCs). Opportunities and needs were identified by analyzing the interrelationships among performance measurement objectives, objects, and study designs. This analysis suggests that before-and-after evaluation studies of traffic management actions and monitoring of traffic data to detect system changes are the most appropriate forms of performance measurement for TMCs. Important potential measures of effectiveness for traffic management systems include travel time and related measures, ramp delay, traffic volumes, accident rates, traffic information accuracy, incident duration, and equipment status. Techniques are available for quantifying these measures, although there are a number of concerns with data accuracy, especially where travel times are estimated from loop-detector data. Case studies of two California TMCs suggest that, although sophisticated data collection systems are available or planned, the institutional infrastructure to carry out performance measurement may be lacking.

Small cities with less than 200,000 inhabitants do not usually suffer from chronic congestion problems. However, private vehicles are used excessively, making it necessary to implement measures to encourage further use of public transport and pedestrian mobility to make it more sustainable. Bypasses improve level of service (LOS) by removing cars from the city center, leading to significant reductions in overall travel time. Most studies so far have been conducted in large cities suffering chronic congestion problems, so the aim of this research is to analyze the effects of bypasses in small and non-congested cities through the construction of a traffic model in Badajoz (Spain), starting with the allocation of the origin-destination travel matrix derived from surveys and traffic counts conducted at the southern and eastern accesses. The traffic model describes the mobility in potentially-capturable future southern traffic relationships and allows insights into different alternatives in the construction of a new high LOS road. This research concludes that small cities with no chronic congestion problems should plan bypasses as close as possible to the city, since they are the most economical, produce greater traffic capture, greater time savings, and eliminate the largest number of CO2 emissions from the urban center. The more distant alternatives have a higher LOS, however, these are longer and more expensive solutions that also capture less traffic and thus eliminate less CO2 emissions.

This study presents a stochastic model based on the link performance function of the Bureau of Public Roads to assess the reliability of travel time in the transportation network. Empirical studies have verified that the variability of travel time can be ascribed to demand fluctuation and the degradation of the capacity of the stochastic network. The mean-variance approach in previous research presented the budget model of travel time, with the capacity of the stochastic network and elastic demand as the sources of uncertainty of travel time. Previous research was devoted to the study of estimation of travel time considering a single factor or a factor independent of these two sources. Meanwhile, this study introduces the current degeneration coefficient of capacity (CDC) and the density distribution function of road section saturation (DDFS) with simultaneous network capacity and traffic demand. Sensitivity analysis method for the parameters of the proposed model is investigated theoretically using the sensitivity model of traffic capacity degradation. Results of case analysis show that the DDFS and CDC have an effect on the decision of travelers regarding the choice of route. The empirical analysis also illustrates the effectiveness of the computational approach and the proposed model.

Accurate travel time information not only is valuable for travelers but is critical to transportation agencies for quantifying the performance of their systems. Interest has been increasing in the development of reliable approaches for estimating travel time from various sensor data. Unlike the extensively studied estimation approaches based on point sensor measurements, the use of probe data from closed highway systems has been limited. To complement current understanding, this study developed an approach that used probe data from an electronic toll collection (ETC) system on closed freeways to estimate travel time. This approach differs from studies relying on automatic vehicle identification systems deployed on main lines as well as those estimated from point detectors. The proposed approach breaks down individual journey time into section travel time and fuses the probe data from vehicles that have used the links. The results, which are based on real-world case studies, illustrate the potential of mining ETC data for travel time estimation for both incident-free and incident conditions. In addition, the estimated results capture traffic dynamics better than instantaneous travel time estimates based on point sensor data. More accurate information is thus provided for deriving reliable performance measures to depict travel time reliability.

Providing accurate and reliable travel time information to travellers is essential to improve the quality of public transit systems. With the availability of the latest technologies, it has become possible to collect a large amount of traffic data to analyze and understand these systems better. Traffic in India is characterized by lack of lane discipline and the presence of vehicles of varying static and dynamic characteristics, which makes prediction of bus travel time especially challenging. The aim of this study is to identify both a prediction algorithm that can handle high variability and suitable inputs or regressors to be used. Earlier studies performed offline manual grouping considering the patterns observed, which leads to limitations for automated field implementations. The present study explores the use of data-driven approaches, primarily clustering, to address the challenges for the prediction of bus travel time trends. Discrete wavelet transform (DWT) was used to extract trends from the travel time measurements. Three popular clustering algorithms— k-means, hierarchical, and self organizing maps (SOM)—were used to identify patterns. Travel time trends were then predicted by searching for similar cluster patterns within the historical database using pattern sequence-based forecasting (PSF). A comparison of the performance of these algorithms was carried out based on prediction errors. The clustering +prediction framework developed was also compared with the case when no clustering was done on the regressor dataset.

This paper presents a method to estimate vehicle speed automatically, including cars and motorcycles under mixed traffic conditions from video sequences acquired with stationary cameras in Hanoi City of Vietnam. The motion of the vehicle is detected and tracked along the frames of the video sequences using YOLOv4 and SORT algorithms with a custom dataset. In the method, the distance traveled by the vehicle is the length of virtual point-detectors, and the travel time of the vehicle is calculated using the movement of the centroid over the entrance and exit of virtual point-detectors (i.e., region of interest), and then the speed is also estimated based on the traveled distance and the travel time. The results of two experimental studies showed that the proposed method had small values of MAPE (within 3%), proving that the proposed method is reliable and accurate for application in real-world mixed traffic environments like Hanoi, Vietnam.

The thrust of a recently published transportation vision for Toronto is focused largely on reducing automobile dependence via a number of interacting strategies, including the wide application of transit priority policies to improve transit competitiveness. This paper reports on quantifying the impacts of several transit priority schemes, with the streetcar operation along King Street in the heart of Toronto as a case study. Four scenarios were modelled in a micro simulation framework. They include the status quo (involving unconditional transit signal priority, already in operation), turning off existing transit signal priority, prohibiting all left turns, and finally prohibiting traffic from King Street. To quantify the impacts of any of the above scenarios, a set of common measures of effectiveness was used, including transit travel time and speed, effective headway, service frequency and person throughput, bunching, fleet size implications, and overall traffic and transit average speeds. The results show the relative merits of the four scenarios and two strategies for improving streetcar service along the King route are recommended. The first is to prohibit all left turns along the route, while the second, admittedly more aggressive, is to potentially transform the arterial into a transit mall accessible only to streetcars.Key words: transit signal priority, transit priority, signal control, microsimulation, streetcars.

Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network.

To encourage low-carbon travel, reduce car trips, and improve the urban traffic system, an understanding of travel mode choice for escorting children to and from school is important. Previous studies have focused mostly on walking and bicycling. However, the electric bicycle (e-bike—a mainstream escorting mode in China) rarely has been investigated. The factors that affect travel mode choice (walking, e-bike, or car) for escorting children to and from school are explored at the household level in a case study from Kunming, China. Intrahousehold interactions and parental space–time constraints are represented by the comparative working hours of the parents and space–time coordination in joint parent–child trips, respectively. A multinomial logit model was applied in mode analysis. The results reveal interesting phenomena in travel mode choices for escorting children to school. When the mother’s working hours are longer than the father’s, the travel mode choice for escorting a child to and from school is less likely to be walking or e-bike; in other words, a car is the preferred choice in mother-dominated households. The distance deviation between parents and children is a significant factor in choosing between a car or an e-bike. Children are more likely to be escorted by e-bikes as a result of distance deviations, and walking or e-bike is less likely to be chosen when the school is far from home. Results could be valuable for traffic demand management to reduce car use for trips to and from school. In addition, e-bike development should be considered seriously for the future development of China.

This paper presents a real-time simulation-based control framework to determine dynamic toll rates to optimize an operator's objective subject to various operational and contractual constraints, such as smooth toll rate changes and maintenance of prescribed levels of service on the toll lane. The toll-setting system incorporates models to predict both the vehicle arrival process upstream of the toll lane facility and drivers’ choice whether to use the toll lanes as a function of the toll rate and travel times presented to drivers within the information system. A macroscopic traffic simulation model is used to predict the flow conditions within the prediction horizon. The travel times provided to users as information and the travel times predicted by the traffic flow model are iterated until consistency between them is obtained. The whole process is embedded within an optimization algorithm that sets tolls to optimize a given objective function. Several case studies demonstrate the use of this framework and its potential to provide useful toll settings.

This paper proposes an improved impedance function for roads with mixed traffic. It is known that only limited studies consider the impact of nonmotorized traffic on travel impedance of a road segment, and a comparison of the impedance considering nonmotorized traffic with the classic BPR function, which does not consider the former, is scarce. Most of the previous studies targeted road conditions in developed countries, where the presence of nonmotorized traffic is negligible, and therefore limited efforts have been invested to develop improved impedance function considering mixed traffic. To overcome this limitation, this paper develops an improved impedance function and carries out a case study for a road in the city of Wuhan, China. The improved impedance function explicitly considers the interaction between motorized and nonmotorized traffic. Taxi GPS data from the case study road is used to extract and analyze the travel time of the “probe vehicles” running through the sampled segment at any time during a sampling day. The capacity of the road segment is measured, and the traffic flow of motorized vehicles and nonmotorized vehicles on the segment is counted. Based on the above data, the classic BPR function and the improved one proposed in this paper are calibrated. After comparing and analyzing the observed road impedance based on both analytical and simulation results, the classic BPR function and the proposed impedance function, the proposed impedance function is found to be more accurate to simulate the observed road impedance, with the error reducing from 14.83 s with the classic BPR impedance function to 6.50 s with the improved function. The proposed impedance function possesses a simple structure and high flexibility, and the parameters calibrated in this paper can be applied to similar roads to provide more realistic impedance than the previous ones based on the classic BPR function. The calibrated improved impedance function’s transferability to other similar roads is validated by applying it to another road and the results show that the percentage error between the predicted travel times and the observed ones is only 3.8%.

The relevance of accessibility in shaping transport planning has often been neglected, hampering on decisions to improve transport efficiency. This is increasingly becoming problematic, as they often impede on economic and technological developments. Many studies on accessibility assert that it is easier for public transport to reach an activity centre than it is for private transport. For this reason, the research compares travel time forecast and accessibility levels with private and public transports en route to commercial centres. The research involves a 21-day transport survey for private cars and public shuttles in Oforikrom district using Global Positioning System (GPS) probe to record the traffic performance indicators to be analyzed in a GIS environment. The results of the study display on a map the level of accessibility via the modes, and a comparative line plot of travel time with private and public transport. The study reveals that private cars in the district generally perform better than public shuttles on the level of accessibility, and travel time. The execution of the research shows that the convergence of choice of transport mode and travel time dynamics is crucial for policymakers to implement diverse transport modes and commuters to choose a mode that has low accessibility cost.

The purpose of this study is to analyze the impact of lowering speed limit on an urban transportation network. A microscopic traffic simulation model, Vissim was utilized to measure the impact. Also, various traffic inputs were tested with different signal coordination scenarios to investigate the impact in different traffic conditions. It was found that during early morning hours with very light traffic, the impact of lowering speed limit was significant. During congested time periods, including level of service E and F, the travel speed reduction from lowering speed limit was not significant. As suggested in other studies, the results demonstrated that lowering the speed limit does not have a significant impact on average travel speed in congested traffic networks. Also, different signal coordination was tested. As expected, signal coordination based on the lowered speed limit performed better than the case with signal coordination based on the previous higher speed limit. The results of this study are expected to provide insights when considering lowering speed limit for existing traffic networks.

Selected results are presented of the Traffic Study, one of 12 studies conducted by San Diego State University for the I-15 Congestion (Value) Pricing Project in San Diego, a 3-year demonstration. The focus is on the project's impact on travel times and their distribution on both the main lanes and the express lanes of I-15 for both ExpressPass and FasTrak phases of the project. Specifically addressed is the issue of reliability of on-time arrival enjoyed by the FasTrak subscribers and the high variability of travel times for the I-15 travelers who use only main lanes of I-15 for their commute. Examination of the ramp and freeway delays shows that in the worst-case scenario, FasTrak subscribers who use express lanes can save up to 20 min avoiding delay on the I-15 main lanes. This finding agrees with the drivers’ perceptions about their time savings when using FasTrak. Travel-time changes during the duration of the project also are examined. There were substantial year-to-year changes in travel times along the I-15 main lanes and the I-8 lanes used as control. The travel-time profile along the I-15 main lanes differed significantly from the profile along I-8, the control corridor, in both a.m. and p.m. peak periods.

This paper describes research sponsored by the Texas Department of Transportation to investigate the operational and safety impact of raised medians and driveway consolidation. Operational effects (travel time, speed, and delay) were investigated through microsimulation on three field test corridors and three theoretical corridors. Safety effects were investigated along 11 test corridors to estimate relationships between crash rates and access point densities as well as the presence of raised medians or two-way left-turn lanes (TWLTLs). The research demonstrates that access management effects are case specific and that microsimulation can assess these unique operational effects. For the case studies investigated, replacing a TWLTL with a raised median resulted in an increase in travel time on two test corridors and a decrease on one test corridor. Small increases in travel time were found with the theoretical corridors as well. The travel time differences are based on the traffic level and location and number of the raised median openings. When present, the relatively small increases in travel time, and subsequent speed and delay, appear to be outweighed by the reduction in the number of conflict points and increased safety. Detailed crash analysis on 11 test corridors indicated that as access point density increases, crash rates increase. This trend holds regardless of the median type. For test corridors in which crash data were investigated before and after the raised median installation, a reduction in the crash rate was always found. Finally, future research needs are identified, including the need to investigate operational and safety impact over a broader range of geometric conditions and longer corridors than investigated here.

Traditionally, routing decisions have been based on minimizing travel time as the associated cost. Eco-routing considers the environmental aspects (e.g., emissions and fuel) as part of the travel cost to mitigate the undesirable impact of transportation systems on the environment. Unlike the existing eco-routing review papers, this research work is aimed at providing a three-factor taxonomy at a more disaggregated level from the optimization perspective and map eco-routing studies to the proposed taxonomy. Furthermore, the strengths and weaknesses of the presented models are summarized. Our main findings include (a) a majority of studies optimized one objective at a time; (b) the microscopic level of aggregation of the flow and emission/fuel models was rarely employed for large case studies, due to the associated complexity; and (c) all of the reviewed studies were applied in a centralized routing system environment. In the near future, when intelligent vehicles will be on the roads, a multi-objective distributed routing framework can be employed with a microscopic level of aggregation for both traffic and emission models, which is capable of operating on largescale networks in real time. Additionally, short-term spatiotemporal prediction of GHG cost is a crucial aspect to be tackled.

In recent years, a growing number of cities in China have successively rolled out bicycle-sharing systems to facilitate bicycle use, including not only metropolises but also some underdeveloped cities with populations of less than 1 million. One of those underdeveloped cities, Xuchang, launched its bicycle-sharing system in 2014. This service provides a convenient way for members to cycle for some of their short trips. Interest in the bicycle-sharing systems of metropolises is growing rapidly; however, studies on underdeveloped cities are still limited. This study investigated the factors influencing the adoption of a bicycle-sharing system in Xuchang, by analyzing massive smart card data from July 2014 to mid-April 2015 and 500 intercept survey questionnaires in April 2015. Different questions were ready for members and nonmembers in the questionnaires and the statistical results show the characteristics of users of the Xuchang bicycle-sharing system, including demographic characteristics, travel habits, and degree of satisfaction. Moreover, the space–time distribution characteristics of the Xuchang bicycle-sharing system were analyzed by dividing a massive data set into three groups: weekdays, weekends, and holidays. Results showed that compared with the clearly defined role of “resolve the last-kilometer problem” in a metropolis, bicycle-sharing in underdeveloped cities acts as an alternative way of transportation rather than a transfer traffic mode. Results also showed that bicycle-sharing systems gained more popularity in underdeveloped cities than in metropolises because of the smaller extent of egression, resident travel habits, the traffic environment, and so on.

Adaptive signal control (ASC) is a well-researched topic that offers an efficient way for traffic management. It possesses a powerful ability to accommodate complex and constantly changing urban transportation networks. With the development of vehicular communication, CV-based ASC shows remarkable advantages compared with the traditional ASC system. Though the existing CV-based ASC strategies were proposed in the past few years, however, there are still issues to overcome. Most of the studies on CV-based ASC are based on the assumption of high CV penetration rate, which often result in poor performance when applied to low CV penetration environments. Besides, the lack of consideration for mixed traffic flow, which is in terms of both the vehicle types and CV penetration of different types of vehicles. To solve these issues, this paper developed an Occupancy-Based ASC strategy for a congested signalized intersection to optimize signal timing and reduce total passenger delay in the low CV penetration environment. Focused on the issues existing in the low CV penetration environment, a Maximum Likelihood Estimation (MLE) model was proposed to estimate vehicle arrivals, and two traffic models, MicroDM and MacroDM, were developed to model the mixed traffic flow and estimate passenger delay. With the purpose of offering fair treatment to passengers approaching the intersection, we proposed an Occupancy-Based Adaptive Signal Control strategy. By transforming the complex signal control problem into a mixed-integer linear programming problem, we found the optimal solution for minimizing total passenger delay. We then evaluated the proposed Occupancy-Based ASC strategy using simulation case studies. The results show that changing traffic status could be captured and estimated with the real-time CV trajectory data as input. Applying the Occupancy-Based ASC control strategy, phases with HOVs or more vehicles will be allocated more travel time. In particular, optimization results show that the proposed Occupancy-Based ASC strategy effectively balances passenger travel demands during peak volume periods.

Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes’ expansion in the freeway network in the future.

Prioritizing traffic signals for trams crossing intersections without stops can increase the service punctuality and travel speed of trams, but it may also increase the delays of other vehicles at intersections. This paper presents a model on coordinated control of traffic signals among successive intersections along the tramline, taking into account driving characteristics of trams and vehicles. The objective is maximizing the valid bandwidth of vehicle green wave to reduce vehicle delays, while the trams cross intersections without stops. Linear Interactive and General Optimizer (LINGO) is applied to solve the proposed model and VISSIM simulation software is adopted to assess the solutions attained by the proposed model and the previous TRAMBAND model. Case studies show that the solutions given by the proposed model facilitate trams to go through all intersections along the tramline without stops. In comparison with the TRAMBAND model, the proposed model reduces tram delay by 13.14 s/pcu and increases the throughput of vehicles at intersections by 4.45% and reduces vehicle delays by 2.22%. Extensive simulations have verified that the performance of the proposed model is stable under different tram headways, dwell time, and traffic volumes. It is also found that the tram headway must be multiple of traffic signal cycle time to completely realize green wave control of all trams at all intersections along the tramline.

Parking is a cumbersome part of auto travel because travelers have to search for a spot and walk from that spot to their final destination. This conventional method of parking will change with the arrival of autonomous vehicles (AV). In the near future, users of AVs get dropped off at their final destination and the occupant-free AVs search for the nearest and most convenient parking spot. Hence, individuals no longer bear the discomfort of cruising for parking while sitting in their vehicle. This paper quantifies the impact of AVs on parking occupancy and traffic flow on a corridor that connects a home zone to a downtown zone. The model considers a heterogeneous group of AVs and conventional vehicles (CV) and captures their parking behavior as they try to minimize their generalized travel costs. Insights are obtained from applying the model to two case studies with uniform and linear parking supply along the corridor. We show that (i) CVs park closer to the downtown zone in order to minimize their walking distance, whereas AVs park farther away from the downtown zone to minimize their parking search time, (ii) AVs experience a lower search time than CVs, and (iii) higher AV penetration rates reduce travel costs for both AVs and CVs.

Urban transport traffic surveillance is of great importance for public traffic control and personal travel path planning. Effective and efficient traffic flow prediction is helpful to optimize these real applications. The main challenge of traffic flow prediction is the data sparsity problem, meaning that traffic flow on some roads or of certain periods cannot be monitored. This paper presents a transport traffic prediction method that leverages the spatial and temporal correlation of transportation traffic to tackle this problem. We first propose to model the traffic flow using a fourth-order tensor, which incorporates the location, the time of day, the day of the week, and the week of the month. Based on the constructed traffic flow tensor, we either propose a model to estimate the correlation in each dimension of the tensor. Furthermore, we utilize the gradient descent strategy to design a traffic flow prediction algorithm that is capable of tackling the data sparsity problem from the spatial and temporal perspectives of the traffic pattern. To validate the proposed traffic prediction method, case studies using real-work datasets are constructed, and the results demonstrate that the prediction accuracy of our proposed method outperforms the baselines. The accuracy decreases the least with the percentage of missing data increasing, including the situation of data being missing on neighboring roads in one or continuous multi-days. This certifies that the proposed prediction method can be utilized for sparse data-based transportation traffic surveillance.

Today's traffic environment is not well adapted to the needs of the older pedestrian. Unfortunately, except in the case of children, little is known about the characteristics and behavior of pedestrians. Although the simple fact that older pedestrians walk more slowly than younger ones is easily supported by field data, existing data on walking speeds and start-up time (i.e., the time from the onset of a Walk signal until the pedestrian steps off the curb) have many shortcomings. A series of field studies was conducted to quantify the walking speed and start-up time of pedestrians of various ages under different conditions. Sixteen crosswalks in four urban areas were studied. Data were collected on walking speeds and start-up times relative to site and environmental factors, including street width, posted speed, curb height, grade, number of vehicle travel lanes, signal cycle length, pedestrian-signal type, street functional classification, crosswalk type, and channelization. Data on a subject group of pedestrians who appeared to be 65 years of age or older and a control group of pedestrians under age 65 were collected. Results indicate a broad range of walking speeds among pedestrians. The 15th-percentile walking speed for younger pedestrians (ages 14 to 64) was 1.25 m/sec (4.09 ft/sec); for older pedestrians (ages 65 and over) it was 0.97 m/sec (3.19 ft/sec). For design purposes values of 1.22 m/sec (4 ft/sec) for younger pedestrians and 0.91 m/sec (3 ft/sec) for older pedestrians are appropriate. Results also indicated that walking rates are influenced by a variety of factors, including the functional classification and vehicle volumes on the street being crossed, the street width, weather conditions, the number of pedestrians crossing in a group, the signal cycle length, the timing of the various pedestrian-signal phases, whether right turn on red is allowed, pedestrian signals, medians, curb cuts, crosswalk markings, stop lines, and on-street parking. However, for each of these factors, the effect on crossing speeds, although statistically significant, is not meaningful for design.

Queue length is a critical performance measure for assessing and managing transportation network performance. Two new methods that integrate data from point traffic detectors and automatic vehicle identification (AVI) readers to estimate the queue length of freeway segments for both off-line and real-time applications are developed in this study. One method estimates the queue length between two detectors by using linear interpolation between the travel time measurement based on AVI data when the link is fully queued and when no queue is present. In the second method, a segment with a partial queue is divided into two subsegments: the first is assumed to be similar to upstream traffic conditions and the second to downstream traffic conditions. Then, the length of each part is calculated from AVI speed data. The performance of these methods is assessed and compared in two case studies that are based on simulation data and real-world data. The results show that using a combination of point detector data and AVI data produces accurate estimates of queue length. The queue estimation method based on cumulative volumes collected with point detectors alone also produces reasonably good estimates but requires additional ramp detection and assumptions regarding moving queue density. The two combination methods produce results that are close to each other based on simulation data and real-world data. The segmentation method produces better results based on real-world data.

Transportation research projects are a vital element for transportation agencies to accumulate new technology and knowledge to improve the efficiency and safety of transportation infrastructure. The purpose of this paper is to develop benefit cost analysis (BCA) tools to assist transportation agencies in evaluating transportation research projects. The BCA tools provide analysis methods for estimating the benefits for changes in the level of service (LOS) of a roadway, reductions in the vehicle travel time, changes in vehicle operating costs and reductions in the number of crashes. Three case studies were investigated to illustrate the usage of the BCA tools. The first case study evaluated the effectiveness of variable speed limit systems implemented along I-80 in southern Wyoming. The BCA tools estimated a benefit cost ratio of 6.64 indicating that the implementation of the project was economically justifiable. The second case study was a recent study investigating and developing mitigation strategies for the effects of truck traffic along the I-80 in southern Wyoming resulting in a benefit cost ratio of a 9.23 indicating that the project had the potential to be economically viable upon implementation. The final case study evaluated the effect of wildlife overpass and underpass crossings on the migrations of pronghorn and mule deer. The benefit cost ratio for the research project was 0.42 indicating that the project was not economically beneficial after the first year of implementation. The case studies indicated that the BCA tools are a beneficial tool for quantifying the economic benefits of a transportation research project.

Transportation Network Companies (TNCs) have been steadily increasing the share of total trips in metropolitan areas across the world. Micro-modeling TNC operation is essential for large-scale transportation systems simulation. In this study, an agent-based approach for analyzing supply and demand aspects of ride-sourcing operation is done using POLARIS, a high-performance simulation tool. On the demand side, a mode-choice model for the agent and a vehicle-ownership model that informs this choice are developed. On the supply side, TNC vehicle-assignment strategies, pick-up and drop-off operations, and vehicle repositioning are modeled with congestion feedback, an outcome of the mesoscopic traffic simulation. Two case studies of Bloomington and Chicago in Illinois are used to study the framework’s computational speed for large-scale operations and the effect of TNC fleets on a region’s congestion patterns. Simulation results show that a zone-based vehicle-assignment strategy scales better than relying on matching closest vehicles to requests. For large regions like Chicago, large fleets are seen to be detrimental to congestion, especially in a future in which more travelers will use TNCs. From an operational point of view, an efficient relocation strategy is critical for large regions with concentrated demand, but not regulating repositioning can worsen empty travel and, consequently, congestion. The TNC simulation framework developed in this study is of special interest to cities and regions, since it can be used to model both demand and supply aspects for large regions at scale, and in reasonably low computational time.

<p class="VARAbstract">Rivers form major traffic arteries in pre-modern Central Europe and accurate regional to supra-regional network models of inland navigation are crucial for economic history. However, navigation distances have hitherto been based on modern flow distances, which could be a significant source of error due to modern changes in flow distance and channel pattern. Here, we use a systematic comparison of vectorized old maps, which enlighten the fluvial landscape before most of the large-scale river engineering took place, and modern opensource geodata to deduce change ratios of flow distance and channel patterns. The river courses have been vectorised, edited and divided into comparable grid units. Based on the thalweg, meandering and braided/anabranching river sections have been identified and various ratios have been calculated in order to detect changes in length and channel patterns. Our large-scale analytical approach and Geographic Information System (GIS) workflow are transferable to other rivers in order to deduce change ratios on a European scale. The 19^th century flow distance is suitable to model pre-modern navigation distances. As a case study, we have used our approach to reconstruct changes of flow pattern, flow distance and subsequent changes in navigation distance and transportation time for the rivers Altmühl, Danube, Main, Regnitz, Rednitz, Franconian and Swabian Rezat (Southern Germany). The change ratio is rather heterogeneous with length and travel time changes of the main channel up to 24% and an extensive transformation of channel morphology in many river sections. Based on published travel time data, we have modelled the effect of our change ratios. Shipping between the commercial hubs Ulm and Regensburg, to give an example, was up to 5 days longer based on pre-modern distances. This is highly significant and underlines the necessity for river-specific correction values to model supra-regional networks of pre-modern inland waterways and navigation with higher precision.</p><p>Highlights:</p><ul><li><p>Systematic comparison of old maps and modern geodata to deduce river-specific length correction values to improve supra-regional network models of pre-modern inland navigation.</p></li><li><p>Large-scale analytical approach and transferable GIS workflow for flow distance reconstruction with case studies in Southern Germany.</p></li><li><p>Length changes of navigated fairways result in pre-modern period travel times up to 24% higher in corrected models.</p></li></ul>

Exclusive bus lane (EBL) is one of the most common transit prioritization strategies implemented to improve transit speed. However, one major drawback of implementing EBLs is the associated reduction in road capacity left for other road users. In corridors with EBLs and infrequent bus service, the lanes are underutilized for extended periods of time. Dynamic bus lane (DBL), a new priority strategy enabled by vehicle connectivity, can provide buses with priority while allowing the general traffic to access the bus lane when buses are not present. Although the DBL concept is promising, a limited number of studies have explored its effectiveness under various conditions. Thus, this paper investigates the impacts of DBLs through a comparison with EBLs and mixed traffic operation under different levels of traffic demand and transit frequency. As a case study, the Eglinton East corridor in Toronto, Canada, was simulated using Aimsun Next, and different scenarios of behavioral impacts were considered in the analysis. The results reveal that DBL is a promising strategy with potential to improve the overall corridor performance over a wide range of traffic and transit service conditions, especially under intermediate traffic demand levels. On the other hand, EBL can be an efficient prioritization strategy that improves the overall corridor performance under high traffic demand and high transit frequency levels, but only if accompanied by a major mode shift from auto to transit.

Departure time choice models play a crucial role in determining the traffic load in transportation systems. Most studies that consider departure time user equilibrium (DTUE) problems make assumptions on the user characteristics (e.g., distribution of desired arrival time and trip length) or dynamic traffic model (e.g., classic bathtub or point queue models) in order to analyze the problem. This paper relaxes these assumptions and introduces a new framework to model and analyze the DTUE problem based on the so-called mean field games (MFGs) theory. MFGs allow us to define players at the microscopic level similar to classical game theory models, translating the effect of players’ decisions to macroscopic models. In this paper, we first present a continuous departure time choice model and investigate the equilibria of the system. Specifically, we demonstrate the existence of the equilibrium and characterize the DTUE. Then, a discrete approximation of the system is provided based on deterministic differential game models to numerically obtain the equilibrium of the system. To examine the efficiency of the proposed model, we compare it with the departure time choice models in the literature. We apply our framework to a standard test case and observe that the solutions obtained based on our model are 5.6% better in terms of relative cost compared with the solutions determined based on previous studies. Moreover, our proposed model converges with fewer iterations than the reference solution method in the literature. Finally, the model is scaled up to the real test case corresponding to the whole Lyon metropolis with a real demand pattern. The results show that the proposed framework is able to tackle a much larger test case than usual to include multiple preferred travel times and heterogeneous trip lengths more accurately than existing models.

Efficient utilization of a private car is achieved when it is used to transport many travelers. A single-occupancy vehicle (SOV) is a private vehicle whose only occupant is the driver. The existence of SOVs in the traffic stream leads to unjustified congestion and shortage of available parking spaces, especially in megacities. Microcars can be beneficial for cities where it is infeasible to construct new roads or upgrade the existing ones because of limited space. Microcars offer many advantages compared with motorcycles and bicycles as they provide shelter from adverse weather conditions, allow for personal storage space, and are more culturally accepted in eastern societies like Egypt. This research investigates the operational impacts of using microcars on roads by using microsimulation. VISSIM was used to model two case studies: a hypothetical urban corridor and a suburban expressway in Greater Cairo. Mixed and exclusive lane scenarios were analyzed using different modal shares for microcars. The results showed that replacing a portion of private cars by microcars increased the throughput volume and reduced the overall travel time. Exclusive lanes for microcars showed better results than mixed lanes on an urban corridor. On the suburban expressway, however, average travel time was shown to be lower for mixed lane usage compared with exclusive lanes. The results of this research support the idea of promoting microcars as a potential mitigation measure to relieve congestion, especially in urban areas.

In the summer of 1999, four ships carrying 599 Fujianese people arrived on the west coast of Canada. They survived a desperate and dangerous journey only for the Canadian Government to put them in prison. After numerous deportations, there are still about 40 of these people in Canadian prisons as of January 2001. They have been in jail for over a year and a half under mere suspicion of flight risk. About 24 people have been granted refugee status. Most people deported to China have been placed in Chinese prisons and fined. It is worth remembering that these migrants may have been undocumented but they are not "illegal" in that they have mobility rights. The Universal Declaration of Human Rights recognizes everyone's right to leave any country and to seek asylum. It can be argued that it is not the migrants who are illegal, but the unjust laws that criminalize their freedom of movement. In considering people's rights, we need to keep in mind not only the civil and political rights that the West tends to privilege, but equally important social and economic rights as well. As a local response to a global phenomenon, Direct Action Against Refugee Exploitation (DAARE) formed in Vancouver to support the rights of the Fujianese women, eleven of whom at the time of writing are still being held in the Burnaby Correctional Centre for Women (BCCW). In DAARE’s view, Immigration Canada's decision to detain all these people is based on a racialized group-profiling policy which violates basic human rights and ignores Canadian responsibility in the creation of the global economic and societal conditions which give rise to widespread migration. In light of the Canadian government's plans to implement even more punitive immigration legislation, DAARE endorses the Coalition for a Just Immigration and Refugee Policy's "Position Paper on Bill C31." They call for humanitarian review and release for the remaining Fujianese people. This review would include a few released refugee claimants who are still in Canada, children, women who were past victims of family planning, people facing religious persecution and, of course, those who are still in prison after 18 months and who have never been charged with any crime. Suspicion of flight risk is not a valid reason to incarcerate people for such a long time. Who Is a Migrant? The lines between "voluntary" and "forced" migration are no longer adequate to explain the complexities of population movements today. Motives for forced displacement include political, economic, social and environmental factors. This spectrum runs from the immediate threats to life, safety and freedom due to war or persecution, to situations where economic conditions make the prospects of survival marginal and non-existent. (Moussa 2000). Terms like "economic migrant" and "bogus refugee" have been used in the media to discredit migrants such as the Fujianese and to foster hostility against them. This scapegoating process oversimplifies the situation, for all refugees and all migrants are entitled to the basic respect due all human beings as enshrined in the UN Declaration of Human Rights. There can be multiple reasons for an individual to migrate—ranging from family reunification to economic pressures to personal survival; to fear of government corruption and of political persecution, to name just a few. The reduction of everything to merely the economic does not allow one to understand why migration is occurring and likely to increase in the future. Most immigrants to Canada could also be described as economic migrants. Conrad Black is an economic migrant. The privileging of rich migrants over poor ones romanticizes globalization as corporate progress and ignores the immense human suffering it entails for the majority of the world's population as the gap between the wealthy and the poor rapidly increases. Hundreds of years ago, when migrants came to this aboriginal territory we now call Canada, they came in order to survive—in short, they too were "economic migrants." Many of those migrants who came from Europe would not qualify to enter Canada today under its current immigration admissions guidelines. Indeed, over 50% of Canadians would not be able to independently immigrate to Canada given its current elitist restrictions. One of the major reasons for an increase in migration is the destruction of rural economies in Asia and elsewhere in the world. Millions of people have been displaced by changes in agriculture that separate people from the land. These waves of internal migration also result in the movement of peoples across national borders in order to survive. Chinese provinces such as Fujian and Guangdong, whose people have a long history of overseas travel, are particularly common sources of out-migration. In discussing migration, we need to be wary of how we can inadvertently reinforce the colonization of First Nations people unless we consciously work against that by actively supporting aboriginal self-determination. For example, some First Nations people have been accused of "smuggling" people across borders—this subjects them to the same process of criminalization which the migrants have experienced, and ignores the sovereign rights of First Nations people. We need ways of relating to one another which do not reenact domination, but which work in solidarity with First Nations' struggles. This requires an understanding of the ways in which racism, colonialism, classism, and other tactics through which "dividing and conquering" take place. For those of us who are first, second, third, fourth, fifth generation migrants to this land, our survival and liberation are intimately connected to that of aboriginal people. History Repeating Itself? The arrival of the Fujianese people met with a racist media hysteria reminiscent of earlier episodes of Canadian history. Front page newspaper headlines such as "Go Home" increased hostility against these people. In Victoria, people were offering to adopt the dog on one of the ships at the same time that they were calling to deport the Chinese. From the corporate media accounts of the situation, one would think that most Canadians did not care about the dangerous voyage these people had endured, a voyage during which two people from the second ship died. Accusations that people were trying to enter the country "illegally" overlooked how historically, the Chinese, like other people of colour, have had to find ways to compensate for racist and classist biases in Canada's immigration system. For example, from 1960 to 1973, Canada granted amnesty to over 12,000 "paper sons," that is, people who had immigrated under names other than their own. The granting of "legal" status to the "paper sons" who arrived before 1960 finally recognized that Canada's legislation had unfairly excluded Chinese people for decades. From 1923 to 1947, Canada's Chinese Exclusion Act had basically prevented Chinese people from entering this country. The xenophobic attitudes that gave rise to the Chinese Exclusion Act and the head tax occurred within a colonial context that privileged British migrants. Today, colonialism may no longer be as rhetorically attached to the British empire, but its patterns—particularly the globally inequitable distribution of wealth and resources—continue to accelerate through the mechanism of transnational corporations, for example. As Helene Moussa has pointed out, "the interconnections of globalisation with racist and colonialist ideology are only too clear when all evidence shows that globalisation '¼ legitimise[s] and sustain[s] an international system that tolerates an unbelievable divide not only between the North and the South but also inside them'" (2000). Moreover, according to the United Nations Development Programme, the income gap between people in the world's wealthiest nations and the poorest nations has shifted from 30:1 in 1960 to 60:1 in 1990 and to 74:1 in 1997. (Moussa 2000) As capital or electronic money moves across borders faster than ever before in what some have called the casino economy (Mander and Goldsmith), change and instability are rapidly increasing for the majority of the world's population. People are justifiably anxious about their well-being in the face of growing transnational corporate power; however, "protecting" national borders through enforcement and detention of displaced people is a form of reactive, violent, and often racist, nationalism which scapegoats the vulnerable without truly addressing the root causes of instability and migration. In short, reactive nationalism is ineffective in safe-guarding people's survival. Asserting solidarity with those who are most immediately displaced and impoverished by globalization is strategically a better way to work towards our common survival. Substantive freedom requires equitable economic relations; that is, fairly shared wealth. Canadian Response Abilities The Canadian government should take responsibility for its role in creating the conditions that displace people and force them to migrate within their countries and across borders. As a major sponsor of efforts to privatize economies and undertake environmentally devastating projects such as hydro-electric dams, Canada has played a significant role in the creation of an unemployed "floating population" in China which is estimated to reach 200 million people this year. Punitive tactics will not stop the movement of people, who migrate to survive. According to Peter Kwong, "The well-publicized Chinese government's market reforms have practically eliminated all labor laws, labour benefits and protections. In the "free enterprise zones" workers live virtually on the factory floor, laboring fourteen hours a day for a mere two dollars—that is, about 20 cents an hour" (136). As Sunera Thobani has phrased it, "What makes it alright for us to buy a t-shirt on the streets of Vancouver for $3, which was made in China, then stand up all outraged as Canadian citizens when the woman who made that t-shirt tries to come here and live with us on a basis of equality?" Canada should respond to the urgent situations which cause people to move—not only on the grounds upon which Convention refugees were defined in 1949 (race, religion, nationality, social group, political opinion) which continue to be valid—but also to strengthen Canada's system to include a contemporary understanding that all people have basic economic and environmental survival rights. Some migrants have lives that fit into the narrow definition of a UN Convention refugee and some may not. Those who do not fit this definition have nonetheless urgent needs that deserve attention. The Canadian Centre for Policy Alternatives has pointed out that there are at least 18 million people working in 124 export zones in China. A living wage in China is estimated to be 87 cents per hour. Canadians benefit from these conditions of cheap labour, yet when the producers of these goods come to our shores, we hypocritically disavow any relationship with them. Responsibility in this context need not refer so much to some stern sense of duty, obligation or altruism as to a full "response"—intellectual, emotional, physical, and spiritual—that such a situation provokes in relations between those who "benefit"—materially at least—from such a system and those who do not. References Anderson, Sarah, et al. Field Guide to the Global Economy. New York: New Press, 2000. Canadian Council of Refugees. "Migrant Smuggling and Trafficking in Persons." February 20, 2000. Canadian Woman Studies: Immigrant and Refugee Women. 19.3 (Fall 1999). Chin, Ko-lin. Smuggled Chinese. Philadelphia: Temple University Press, 1999. Coalition for a Just Immigration and Refugee Policy. "Position Paper on Bill C31." 2000. Davis, Angela. The Angela Davis Reader. Malden, MA: Blackwell Publishers, 1998. Global Alliance Against Traffic in Women, Foundation Against Trafficking in Women, and International Human Rights Law Group. "Human Rights Standards for the Treatment of Trafficked Persons." January 1999. Henry, Frances and Tator, Carol. Racist Discourses in Canada's English Print Media. Toronto: Canadian Foundation for Race Relations, 2000. Jameson, Fredric and Miyoshi, Masao, Eds. The Cultures of Globalization. Durham: Duke University Press, 1998. Kwong, Peter. Forbidden Workers. New York: New Press, 1997. Mander, Jerry and Goldsmith, Edward, Eds. The Case Against the Global Economy. San Francisco: Sierra Club Books, 1996. Moussa, Helene. "The Interconnections of Globalisation and Migration with Racism and Colonialism: Tracing Complicity." 2000. ---. "Violence against Refugee Women: Gender Oppression, Canadian Policy, and the International Struggle for Human Rights." Resources for Feminist Research 26 (3-4). 1998 Migrant Forum statement (from Asia Pacific People's Assembly on APEC) 'Occasional Paper Migration: an economic and social analysis.' Pizarro, Gabriela Rodriguez. "Human Rights of Migrants." United Nations Report. Seabrook, Jeremy. "The Migrant in the Mirror." New Internationalist 327 (September 2000): 34-5. Sharma, Nandita. "The Real Snakeheads: Canadian government and corporations." Kinesis. October/November (1999): 11. Spivak, Gayatri. "Diasporas Old and New: Women in the Transnational World." Class Issues. Ed. Amitava Kumar. New York: New York University Press, 1997. States of Disarray: The Social Effects of Globalization. London: United Nations Research Institute for Social Development (UN RISD), 1995. Thobani, Sunera. "The Creation of a ‘Crisis’." Kinesis October/November (1999): 12-13. Whores, Maids and Wives: Making Links. Proceedings of the North American Regional Consultative Forum on Trafficking in Women, 1997.

The World Health Organization (WHO) declared a COVID-19 pandemic last March 11, 2020.1,2 According to the WHO Director General, “In the past two weeks, the number of cases of COVID-19 outside China has increased 13-fold, and the number of affected countries has tripled. There are now more than 118,000 cases in 114 countries, and 4,291 people have lost their lives. Thousands more are fighting for their lives in hospitals.” Soon after, Metro Manila was placed on a complete lockdown which started on March 15, 2020 and continues up to the time of this writing.2 So, what exactly is this COVID-19 pandemic? Will it be changing how we live our lives as healthcare professionals? What will be our role in taking care of patients with COVID-19? These and many other related questions require immediate answers as we face the threat of COVID-19. The WHO was first informed of cases of pneumonia of unknown cause in Wuhan City, China near the end of 2019. A novel coronavirus was identified as the cause by Chinese authorities and was initially named 2019-nCoV.3,4 This was later revised to COVID-19 (coronavirus disease of 2019) and the virus that causes it called SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2). In the first global epidemic caused by the “first” SARS coronavirus in 2003, the Philippines had a total of only eight confirmed patients. All the cases had contact with a nurse aide who had returned from Toronto, Canada where she got it. The index case and her father eventually died from SARS while the rest recovered.5 But, with COVID-19, at the time of writing this editorial, there were approximately 1,611 weekly cases with 112 weekly deaths in the Philippines and appears to be an increasing trend.6,7 By mid-March 2020, the WHO European Region had become the epicenter of the epidemic, reporting over 40% of globally confirmed cases. As of 28 April 2020, 63% of global mortality from the virus was from the Region, according to the WHO.3 There is much that we need to know about SARS-CoV-2, the virus that causes COVID-19. It belongs to the same family of coronavirus that causes SARS, MERS (Middle East Respiratory Syndrome), and even the common cold.3 Early studies report that SARS-CoV-2 was most often detected in respiratory samples from patients in China. However, live virus was also found in feces.8 It is thought that transmission mainly occurs through the respiratory route, probably as droplets, but extra respiratory sources may also be important. Risk factors for severe illness remain uncertain but old age and comorbidities such as cardiovascular disease, liver disease, kidney disease or malignant tumors, have emerged as likely important factors. There are no proven effective specific treatment strategies, and the risk-benefit ratio for commonly used treatments such as corticosteroids is not clear.7,8 COVID-19 may also cause damage to other organs such as the heart, the liver, and the kidneys, as well as to organ systems such as the blood and the immune system. Patients die of multiple organ failure, shock, acute respiratory distress syndrome, heart failure, arrhythmias, and renal failure.9,10 Among the WHO’s current recommendations, people with mild respiratory symptoms should be encouraged to isolate themselves, and social distancing is emphasized, and these recommendations apply even to countries with no reported cases.3,11 However, such measures could drastically affect the economy with impact on work practices as well as commercial establishments which depend on people’s patronage.12,13 Moreover, the psychological and mental burden that isolation and quarantine can bring about should also be considered. 14,15 For those in the academe, adjustments and quick transition to online learning strategies will need to be made.16 This will also affect how scientific research is done, particularly as we try to learn more about COVID-19.17 The longer the pandemic lasts, and the longer these measures need to be implemented, the more significant will the effects be on the economic and mental well-being of the people. There has certainly been a rush to get more information about COVID-19.18 Although well-intended in most cases, this has resulted into an “infodemic” with some erroneous or unscientific information about COVID-19. 19-21 Even mainstream scientific publications have not been spared by such faulty information. 22,23 Health professionals, therefore, who will be using the information found in these publications will need to be more vigilant in making sure that the data are properly collected and interpreted. We need to constantly update ourselves as new information becomes available.24-26 As in many viral diseases, the best way to combat COVID-19 could be vaccination. Based on the experience with developing vaccines for the other coronaviruses such as the ones causing SARS, MERS and even the common colds, the development of an effective vaccine against COVID-19 may be challenging.27-30 Even if one were to be quickly developed, having the resources needed to make enough vaccines for potentially all inhabitants of our planet are also staggering. And then of course, once a vaccine is available, each country would have to device its own vaccination strategy and all of its accompanying logistic considerations. And then there is the cost of such a vaccine. As a third world country, would the Philippines be able to afford enough vaccines for its citizens? Pending availability of an effective vaccine, one would need to look at actual treatment of COVID-19 patients. In the short-term, it may be possible to repurpose some of the currently available drugs we use for treating other viruses.31-33 In order to help address these, some wide-ranging initiatives have been set up. In March 2020, the UK Research and Innovation (UKRI) Medical Research Council and the UK National Institute of Health Research (NIHR) started the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial.34,35 It is the world’s largest clinical trial into treatments for COVID-19, with more than 40,000 participants across 185 trials sites in the UK. It is led by the University of Oxford. At about the same time, the WHO also announced the start of an international randomized and adaptive clinical trial SOLIDARITY which will also be looking at potential treatments for COVID-19. 36,37 The Philippines is set to participate in the SOLIDARITY trial.38 Use of personal protective equipment (PPEs) similar to how we have used them against Ebola and other viruses could also be beneficial.39 But similar to developing capacity for making enough vaccines, the ability to make enough PPEs, especially the disposable ones and bring these to where they are needed could also be additional challenges. In the Philippines, as in many other parts of the world, many healthcare workers report insufficient availability of PPEs which puts them at risk of getting COVID-19 from their patients.40,41 There are many more questions needing answers that we will need to deal with as we confront COVID-19. And, most likely, there will also be new challenges that can arise as the pandemic evolves. The combined efforts of the scientific and political communities will need to be engaged if we hope to successfully deal with this emergency. Joven Jeremius Q. Tanchuco, MD, MHA Professor, Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines Manila Clinical Professor, Division of Pulmonary Medicine, Department of Medicine, College of Medicine and Philippine General Hospital, University of the Philippines Manila REFERENCES WHO Director-General's opening remarks at the media briefing on COVID-19 [Internet]. 11 March 2020 [cited 2020 Apr 15]. Available from: https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020. Metro Manila to be placed on 'lockdown' due to COVID-19 [Internet]. [cited 2020 Apr 15]. Available from: https://cnnphilippines.com/news/2020/3/12/COVID-19-Metro-Manila-restrictions-Philippines.html Cucinotta D, Vanelli M. WHO Declares COVID-19 a Pandemic. Acta Biomed. 2020;91(1):157-160. doi:10.23750/abm. v91i1.9397 Coronavirus disease (COVID-19) pandemic [Internet]. [cited 2020 Apr 15]. Available from: https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov World Health Organization. SARS outbreak in the Philippines = Flambée de SRAS aux Philippines. Weekly Epidemiological Record = Relevé épidémiologique hebdomadaire. 2003;78(22):189-192. https://apps.who.int/iris/handle/10665/232177 COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University ( JHU) [Internet]. [cited 2020 Apr 19]. Available from: https://www.arcgis. com/apps/dashboards/bda7594740fd40299423467b48e9ecf6. Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time [published correction appears in Lancet Infect Dis. 2020;20(9):e215]. Lancet Infect Dis. 2020;20(5):533-534. doi:10.1016/S1473-3099(20)30120-1 Murthy S, Gomersall CD, Fowler RA. Critically Ill Patients With COVID-19. JAMA. 2020;323(15):1499-1500. doi:10.1001/JAMA.2020.3633. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223):497-506. Woelfel R, Corman VM, Guggemos W, Seilmaier M, Zange S, Mueller MA, et al. Clinical presentation and virological assessment of hospitalized cases of coronavirus disease 2019 in a travel-associated transmission cluster. medRXiv. March 8, 2020. Schmidt B, Davids EL, Malinga T. Quarantine alone or in combination with other public health measures to control COVID-19: A rapid Cochrane review. S Afr Med J. 2020;110(6):476-477. doi:10.7196/SAMJ. 2020.v110i6.14847 Tandon PN. COVID-19: Impact on health of people & wealth of nations. Indian J Med Res.2020;151(2 & 3):121-123. doi: 10.4103/ijmr.IJMR_664_20 Zouari A. 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