Uncovering physical activity trade-offs in transportation policy: A spatial agent-based model of Bogotá, Colombia.

BACKGROUND: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. METHODS: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. RESULTS: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. CONCLUSIONS: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Evaluation of a walking school bus program: a cluster randomized controlled trial.

BACKGROUND: The purpose of this study was to investigate the effects of a walking school bus intervention on children's active commuting to school. METHODS: We conducted a randomized controlled trial (RCT) in Houston, Texas (Year 1) and Seattle, Washington (Years 2-4) from 2012 to 2016. The study had a two-arm, cluster randomized design comparing the intervention (walking school bus and education materials) to the control (education materials) over one school year October/November - May/June). Twenty-two schools that served lower income families participated. Outcomes included percentage of days students' active commuting to school (primary, measured via survey) and moderate-to-vigorous physical activity (MVPA, measured via accelerometry). Follow-up took place in May or June. We used linear mixed-effects models to estimate the association between the intervention and outcomes of interest. RESULTS: Total sample was 418 students [Mage=9.2 (SD = 0.9) years; 46% female], 197 (47%) in the intervention group. The intervention group showed a significant increase compared with the control group over time in percentage of days active commuting (ß = 9.04; 95% CI: 1.10, 16.98; p = 0.015) and MVPA minutes/day (ß = 4.31; 95% CI: 0.70, 7.91; p = 0.02). CONCLUSIONS: These findings support implementation of walking school bus programs that are inclusive of school-age children from lower income families to support active commuting to school and improve physical activity. TRAIL REGISTRATION: This RCT is registered at clinicaltrials.gov (NCT01626807).

Ocimum gratissimum essential oil in the transport water of Brycon hilarii: implications at water quality, blood parameters and residues in tissue and plasma.

Transporting live fish is a common practice in fish farming, and is certainly one of the main problems that affect fish homeostasis. In this scenario, the use of natural additives has shown promise in improving fish resistance to adverse situations. This study aimed to assess the impact of Ocimum gratissimum L. essential oil (OGEO) on water quality, hematological parameters, and residue levels in the plasma, fillet, and liver of juvenile piraputanga (Brycon hilarii) during a two-hour transportation period. The fish were divided into plastic bags (4 L) and exposed to three different OGEO concentrations (10, 20, and 30 mg L-1), while a control group received no OGEO (three repetitions each). After the two-hour transportation, blood samples were collected, as well as portions of the fillet and liver for quantifying essential oil compounds, which were also measured in the plasma. Oxygen levels remained high throughout the transportation period, in all groups, while the pH decreased. Hemoglobin, MCHC, and MCH increased in fish exposed to OGEO concentrations of 20 and 30 mg L-1, compared to the control group. However, lymphocyte counts and the concentrations of essential oil compounds in plasma, fillet, and liver increased with higher OGEO concentrations. The use of 10 mg L-1 OGEO in the two-hour transport water is promising to ensure the survival and well-being of Brycon hilarii juveniles (weighing 16 g), showing to be safe and effective. The residual concentration of eugenol the major compound of OGEO in the fillet remains below the maximum limit of the recommended daily intake.

Public transit and crisis communication for critical populations: A content analysis of web-based communication strategies during the COVID-19 pandemic.

In the United States, selected subgroups of historically marginalized populations include people with disabilities and people in racial/ethnic minority groups ("critical populations") who have been disproportionately affected by COVID-19. These groups are also more likely to use public transit to access essential resources; thus, understanding transit agencies' communication strategies to reach these populations during crises is of utmost importance. We conducted a content analysis of 16 transit agencies' webpages and Twitter® accounts during the first 6 months of the pandemic to assess alignment of agencies' COVID-19-related communications with best practices in crisis communication across five themes: perceivability, navigability, understandability, suitability, and content. Findings suggested that transit agencies frequently communicated about schedule changes and safety, eg, masking, station sanitation, and reflected racial/ethnic diversity in images. Yet, less than half consistently used communication strategies known to enhance accessibility and uptake of messaging among critical populations, eg, alternative text, and even less reflected disability diversity in images. We offer recommendations for public transit agencies to move beyond compliance to effectively address the needs of ridership most substantially impacted by public health emergencies.

Navigating health challenges: the interplay between occupation-imposed movement restrictions, healthcare access, and community resilience.

BACKGROUND: Transportation plays a significant role in health, community resilience, and access to basic needs such as healthcare, social services, education, and job opportunities. Health and community resilience are, however, impacted by a multitude of complex and unequal factors, such as transportation restrictions exacerbated by the Israeli occupation. The goal of the research was to examine the intricate relationships that exist in Palestine between movement restrictions imposed by occupation, health outcomes, and community resilience. METHOD: A self-structured questionnaire, devised based on expert conversations and previous literature, was used in this descriptive, quantitative study to explore health and resilience outcomes. Age, gender, marital status, place of residence, and means of transportation were among the various factors that were utilized to describe the socio-demographics of the study sample (n = 202). The researchers employed stepwise multiple regression and descriptive statistics for the data analysis. RESULTS: Study findings indicated that transportation restrictions have significant direct and indirect health consequences. A significant direct effect is observed, signifying a negative correlation between restrictions and health; increased transportation restrictions are consistently correlated with a decline in health. The study emphasized how place of residence affects health outcomes, with higher scores for campers and people living in green line areas. It also underscores that public means of transportation are found to be better for health outcomes than private cars. CONCLUSION: This study emphasized that roadblocks, checkpoints, and military incursions make it difficult for Palestinians to receive medical care, which has a detrimental impact on their health and well-being. It also underscores the need for significant reforms in Palestinian health and transportation systems to enhance infrastructure and healthcare access. The Palestinian Authority should invest in public transportation and community resilience programs to address transportation-related health issues, especially in villages, due to frequent settler attacks.

Safety performance of dedicated and preferential bus lanes using multivariate negative binomial models for Bogotá, Colombia.

Public transport priority systems such as Bus Rapid Transit (BRT) and Buses with High Level of Service (BHLS) are top-rated solutions to mobility in low-income and middle-income cities. There is scientific agreement that the safety performance level of these systems depends on their functional, operational, and infrastructure characteristics. However, there needs to be more evidence on how the different characteristics of bus corridors might influence safety. This paper aims to shed some light on this area by structuring a multivariate negative binomial model comparing crash risk on arterial roads, BRT, and BHLS corridors in Bogotá, Colombia. The analyzed infrastructure includes 712.1 km of arterial roads with standard bus service, 194.1 km of BRT network, and 135.6 km of BHLS network. The study considered crashes from 2015 to 2018 -fatalities, injuries, and property damage only- and 30 operational and infrastructure variables grouped into six classes -exposure, road design, infrastructure, public means of transport, and land use. A multicriteria process was applied for model selection, including the structure and predictive power based on [i] Akaike information criteria, [ii] K-fold cross-validation, and [iii] model parsimony. Relevant findings suggest that in terms of observed and expected accident rates and their relationship with the magnitude of exposure -logarithm of average annual traffic volumes at the peak hour (LOG_AAPHT) and the percentage of motorcycles, cars, buses, and trucks- the greatest risk of fatalities, injuries, and property damage occurs in the BHLS network. BRT network provides lower crash rates in less severe collisions while increasing injuries and fatalities. When comparing the BHLS network and the standard design of arterial roads, BHLS infrastructure, despite increasing mobility benefits, provides the lowest safety performance among the three analyzed networks. Individual factors of the study could also contribute to designing safer roads related to signalized intersection density and curvature. These findings support the unique characteristics and traffic dynamics present in the context of Bogotá that could inform and guide decisions of corresponding authorities in other highly dense urban areas from developing countries.

Grain transportation and consumption reshapes the α-HCH exposure picture of China.

Socio-economic activities like food trade can increase the uncertainty of human risk of persistent organic pollutants (POPs). We compared the change in model predicted α-hexachlorocyclohexane (α-HCH) cancer risk (CR) with and without grain trade in mainland China. In scenario without grain logistics, α-HCH moved fast away from southern and southeastern China via northward atmospheric transport. However, the grain logistics from northeastern China delivers the α-HCH previously accumulated in northeastern sink back to densely populated areas in recent years, which enhance CR by >50 % in the southern seaboard of China. The northward movement of grain production center and recent grain deficiency in southern provinces induced by dietary pattern changes is identified as the major driving factors of the reversed transport of α-HCH. The finding highlights the potential of socio-economic activities that can otherwise offset the risk reduction effect of the geochemical cycle of POPs.

Transportation infrastructure upgrading and green development efficiency: Empirical analysis with double machine learning method.

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading.

Addressing transportation barriers in oncology: existing programs and new solutions.

Transportation is an underrecognized, but modifiable barrier to accessing cancer care, especially for clinical trials. Clinicians, insurers, and health systems can screen patients for transportation needs and link them to transportation. Direct transportation services (i.e., ride-sharing, insurance-provided transportation) have high rates of patient satisfaction and visit completion. Patient financial reimbursements provide necessary funds to counteract the effects of transportation barriers, which can lead to higher trial enrollment, especially for low socioeconomic status and racially and ethnically diverse patients. Expanding transportation interventions to more cancer patients, and addressing knowledge, service, and system gaps, can help more patients access needed cancer care.

Using the dead to infer about the living: Amphibian roadkill spatiotemporal dynamics suggest local populations' reduction.

Roads represent one of the main sources of wildlife mortality, population decline, and isolation, especially for low-vagility animal groups. It is still not clearly understood how wildlife populations respond to these negative effects over space and time. Most studies on wildlife road mortality do not consider the spatial and temporal components simultaneously, or the imperfect roadkill detection, both of which could lead to inaccurate assumptions and unreliable mitigation actions. In this study, we applied a multi-season occupancy model to a 14-year amphibian mortality dataset collected along 120 km of roads, combined with freely available landscape and remote sensing metrics, to identify the spatiotemporal patterns of amphibian roadkill in a Mediterranean landscape in Southern Portugal. Our models showed an explicit general decrease in amphibian roadkill. The Iberian painted frog (Discoglossus galganoi) experienced roadkill declines over time of ∼70 %, while the spiny common toad (Bufo spinosus) and the fire salamander (Salamandra salamandra) had a loss of nearly 50 %, and the Southern marbled newt (Triturus pygmaeus) had 40 %. Despite the decreasing trend in roadkill, spatial patterns seem to be rather stable from year to year. Multi-season occupancy models, when combined with relevant landscape and remote sensing predictors, as well as long-term monitoring data, can describe dynamic changes in roadkill over space and time. These patterns are valuable tools for understanding roadkill patterns and drivers in Mediterranean landscapes, enabling the differentiation of road sections with varying roadkill over time. Ultimately, this information may contribute to the development of effective conservation measures.

Examination of factors associated with the temporal stability assessment of crash severity by using generalised linear model-A case study.

Road crashes are a major public safety concern in Pakistan. Prior studies in Pakistan investigated the impact of different factors on road crashes but did not consider the temporal stability of crash data. This means that the recommendations based on these studies are not fully effective, as the impact of certain factors may change over time. To address this gap in the literature, this study aims to identify the factors contributing to crash severity in road crashes and examine how their impact varies over time. In this comprehensive study, we utilized Generalised Linear Model (GLM) on the crash data between the years 2013 to 2017, encompassing a total sample of 802 road crashes occurred on the N-5 road section in Pakistan, a 429-kilometer stretch connecting two big cities of Pakistan, i.e., Peshawar and Lahore. The purpose of the GLM was to quantify the temporal stability of the factors contributing crash severity in each year from 2013 to 2017. Within this dataset, 60% (n = 471) were fatal crashes, while the remaining 40% (n = 321) were non-fatal. The results revealed that the factors including the day of the week, the location of the crashes, weather conditions, causes of the crashes, and the types of vehicles involved, exhibited the temporal instability over time. In summary, our study provides in-depth insights aimed at reducing crash severity and potentially aiding in the development of effective crash mitigation policies in Pakistan and other nations having similar road safety problems. This research holds great promise in exploring the dynamic safety implications of emerging transportation technologies, particularly in the context of the widespread adoption of connected and autonomous vehicles.

Impacts of active mobility on individual health mediated by physical activities.

Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.

Does the priority of ambulance guarantee no delay? a MIPSSTW model of emergency vehicle routing optimization considering complex traffic conditions for highway incidents.

Globally, traffic accidents on the highway network contribute significantly to a high fatality rate, drawing considerable attention from health institutions. The efficiency of transportation plays a vital role in mitigating the severe consequences of these incidents. This study delves into the issues of emergency vehicles experiencing delays despite having priority. Therefore, we construct mixed-integer linear programming with semi-soft time windows (MIPSSTW) model for optimizing emergency vehicle routing in highway incidents. We analyze the time-varying and complex traffic situations and respectively propose corresponding estimation approaches for the travel time of road segments, intersections on the urban road network, and ramp-weave sections on the highway network. Furthermore, we developed a modified cuckoo search(MCS) algorithm to solve this combinatorial problem. Optimization strategies of Lévy flight and dynamic inertial weight strategy are introduced to strengthen the exploration capability and the diversity of solution space of the CS algorithm. Computational experiments based on the Chinese emergency medical system data are designed to validate the efficacy and effectiveness of the MIPSSTW model and MCS algorithm. The results show that our works succeed in searching for high-quality solutions for emergency vehicle routing problems and enhance the efficacy of strategic decision-making processes in the realm of incident management and emergency response systems.

Statistical estimation of fatal and serious injuries saved by iRAP protocols in 74 countries.

OBJECTIVE: Road traffic crashes cause 1.19 million deaths and millions more injuries annually. The persistently high burden has drawn attention from national and international stakeholders worldwide. Unsafe road infrastructure is one of the major risk factors for traffic safety, particularly in low- and middle-income countries. METHODS: Aiming to eliminate high-risk roads in all countries, the International Road Assessment Programme (iRAP) developed a robust and evidence-based approach to support country transportation agencies. RESULTS: Thus far, the iRAP protocols have been used to collect 1.8 million kilometers of Crash Risk Mapping and 1.5 million kilometers of Star Rating and FSI estimations in 128 countries. Deploying an observational before-and-after (or pre-post) study design, this report estimated the fatal and series injuries (FSI) saved through use of the iRAP protocols. The study is based on 441,753 kilometers of assessed roads from 1,039 projects in 74 countries. Our results show that the implementation of iRAP's proposed countermeasures saves about 159,936 FSI annually. Throughout the lifetime of the implemented countermeasures, a total of 3.2 million FSI could be saved. CONCLUSION: While quantifying the success of the iRAP protocols, our results suggest an opportunity to save many millions more lives on the roads through expanding iRAP implementation to more regions and countries.

Implementation of a realistic artificial data generator for crash data generation.

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. The crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

Analysis of current methods and Welfare concerns in the transport of 118 horses by commercial air cargo companies.

BACKGROUND: Studies on equine air transport practices and consequences are scarce. This prospective study aimed to describe horse and air journey details and practices, document how horse behavior and health changed during the air transport phases, quantify the occurrence of welfare issues, and identify possible associations between horse and journey details, air transport practices, and welfare issues. RESULTS: Data were collected from before departure to five days after arrival on 118/597 horses traveling on 32 commercial air journeys on different routes, varying in duration and conditions. Most horses were middle-aged warmblood females, 26% of which were pregnant, and being moved by air for sales. Before flying, most were quarantined (median: 18; IQR: 9-53 days), and their fitness for travel was certified by veterinarians. At the departure airports, external temperatures varied from - 6 °C to 33 °C, and horses were loaded by experienced flight grooms (median: 35; IQR: 15-40 years) into jet stalls (three-horse: 87%, two-horse: 13%). During the flights, horses were regularly watered (water intake median: 14 L) and fed ad libitum (feed consumption median: 8 kg). At the arrival airport, horses were unloaded from the jet stalls, and external temperatures ranged from - 5 °C to 32 °C. Then, all horses were transported to arrival quarantine by road. Air transport phases affected horses' health status and behavior; increased heart and respiratory rates and behaviors, such as pawing, head tossing, and vocalization, were mainly identified at departure and arrival. Horse interaction, nasal discharge, increased capillary refill time (CRT), and abnormal demeanor were observed more often one hour before landing while resting and normal capillary refill time were more often displayed five days after arrival (all P < 0.01). One hour before landing, horses with bad temperament and horses of unknown temperament were more likely to develop nasal discharge when transported in winter and autumn (P < 0.001). The likelihood of an increased CRT was associated with shorter flights in horses of unknown travel experience (P < 0.001). Ten horses were injured, and 11 developed pleuropneumonias (i.e., shipping fever). CONCLUSIONS: Air transport is a complex procedure with several different phases affecting horse health and behavior. Therefore, experienced staff should carefully manage each horse before, during, and after air journeys to minimize welfare hazards.

Community Transport's Dual Role as a Transport and a Social Scheme: Implications for Policy.

Community transport comprises diverse local, not-for-profit, and primarily volunteer-run transport schemes that operate across the United Kingdom. These schemes support the travel needs of thousands of people, most of whom are older, live in rural areas, and have few other transport options. Further, this transport sector is unique in that most schemes are designed, created, and run by older people themselves. And yet, community transport has thus far received relatively little attention in both policy and research. Using semi-structured interviews with community transport providers in Oxfordshire, this paper proposes community transport as a practice guided by phronesis and argues that it has been made to hold a dual role as both a transport and a social scheme. The transport it provides is unique in being made low-cost, flexible, and functionally accessible. It has also been made into a social scheme as it helps those with few other options, provides benefits that extend beyond the transport realm, and fosters community. Though this dual role means that community transport has many cross-sectoral benefits, this type of service provision is found to be overlooked in both national and local policy, which has enabled the constitutive role of phronesis in community transport. Given this, there are challenges ahead for the sector in both ensuring its sustainability and maintaining its ability to respond closely to users' needs.

A 17-month longitudinal surface sampling study carried out on public transport vehicles operating in England during the COVID-19 pandemic identified low levels of SARS-CoV-2 RNA contamination.

AIMS: To monitor severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA contamination in vehicles operating in England during the pandemic, to better understand transmission risk of SARS-CoV-2 on public transport. METHODS AND RESULTS: We collected 1314 surface samples between December 2020 and April 2022 on trains and buses managed by five different transport operators. The presence of SARS-CoV-2 RNA was investigated through reverse transcription polymerase chain reaction (RT-PCR). SARS-CoV-2 RNA was found on 197 (15%) of the 1314 surfaces sampled, including seat head rests, handholds, and air extract grilles, but the levels of RNA recovered on those samples (median value of 23.4, interquartile range: 14.3-35.4, N gene copies per extraction) made the presence of infectious virus at the time of sampling extremely unlikely. However, detection rates varied over time with peaks broadly coinciding with times of high community transmission, when it was more likely that people infected with SARS-CoV-2 were travelling on public transport. CONCLUSION: During the pandemic, and as in other public spaces, low levels of SARS-CoV-2 RNA were found on surfaces associated with public transport.

Identification of critical links based on the optimal reliable path in stochastic traffic networks.

In urban stochastic transportation networks, there are specific links that hold great importance. Disruptions or failures in these critical links can lead to reduced connectivity within the road network. Under this circumstance, this manuscript proposed a novel identification of critical links mathematical optimization model based on the optimal reliable path with consideration of link correlations under demand uncertainty. The method presented in this paper offers a solution to bypass the necessity of conducting a full scan of the entire road network. Due to the non-additive and non-linear properties of the proposed model, a modified heuristic algorithm based on K-shortest algorithm and inequality technical is presented. The numerical experiments are conducted to show that improve a certain road link may not necessarily improve the overall traffic conditions. Moreover, the results indicate that if the travel time reliability is not considered, it will bring errors to the identification of key links.