Risky Route Research Articles

Creative forms: booklets by the hospital senses collective

This article details the creation of a series of booklets designed to explore sensory encounters with hospitals and healthcare environments. The booklets were devised as a series of prompts or...

Taking high-stakes venture to make ends meet? Determinants and impacts of international migration of Ethiopians to the Middle East

Ethiopia is one of the major origins for international migrants to the Middle East in Africa regardless of the risks and the abuses that migrants face. The study aims to analyse the determinants of international migration of Ethiopians to the Middle East and its impact on the income of households staying behind particularly in the Dessie Zuria district of the Amhara region in Ethiopia. Data were randomly collected from 346 households and analysed using descriptive statistics, logit regression, and Propensity Score Matching (PSM) models. The logit regression analysis indicates that bigger family size, network with migrants/returnees, and the presence of peer/family pressure influence the probability of international migration positively. On the contrary, being a male household head, ownership of larger farmland and livestock, and participation in additional non-farm activities determine international migration negatively. The findings from the PSM model revealed that international migration increased the annual income of migrant-sending households by 13,079.51 ETB per year over non-migrant sending households. However, the benefits enjoyed by the families staying behind have been at the expense of migrants, whose income is hard-earned and they often take a risky route to reach the destination regions. The findings call for an integrated policy approach to control population pressure that depletes the key financial and physical assets of households in the origin and thus forces individuals to look for alternative livelihood strategies such as migration. Location-specific policy interventions are needed to create non-farm and alternative livelihoods, improve agricultural productivity, and access information to reduce exaggerated and misleading information about the destination areas.

An exact method for the combinatorial bids generation problem with uncertainty on clearing prices, bids success, and contracts materialization

We address a new variant of the Bid Construction Problem (BCP) with stochastic clearing prices in combinatorial auctions for the procurement of truckload transportation service that tackles uncertainty on bids success and auctioned contracts materialization. We propose the first exact method to generate multiple non-overlapping bids while ensuring a non-negative profit for the carrier regardless of the auction outcomes and auctioned contracts materialization. Our exact method iteratively solves a relaxed then a restricted version of the BCP with stochastic clearing prices while checking all routes generated in each optimal solution and dynamically adds cuts to forbid what we define as risky routes. Risky routes are the ones that could yield a negative profit if some bids are lost or some auctioned contracts do not materialize later. Our experimental study highlights the good performance of our exact approach and points out the potential gains in profits yielded by our new variant compared to a standard BCP.

From Three-Dimensional (3D)- to 6D-Printing Technology in Orthopedics: Science Fiction or Scientific Reality?

Over the past three decades, additive manufacturing has changed from an innovative technology to an increasingly accessible tool in all aspects of different medical practices, including orthopedics. Although 3D-printing technology offers a relatively inexpensive, rapid and less risky route of manufacturing, it is still quite limited for the fabrication of more complex objects. Over the last few years, stable 3D-printed objects have been converted to smart objects or implants using novel 4D-printing systems. Four-dimensional printing is an advanced process that creates the final object by adding smart materials. Human bones are curved along their axes, a morphological characteristic that augments the mechanical strain caused by external forces. Instead of the three axes used in 4D printing, 5D-printing technology uses five axes, creating curved and more complex objects. Nowadays, 6D-printing technology marries the concepts of 4D- and 5D-printing technology to produce objects that change shape over time in response to external stimuli. In future research, it is obvious that printing technology will include a combination of multi-dimensional printing technology and smart materials. Multi-dimensional additive manufacturing technology will drive the printing dimension to higher levels of structural freedom and printing efficacy, offering promising properties for various orthopedic applications.

Information provision and congestion pricing in a risky two-route network with heterogeneous travelers

Travel information and congestion pricing are two major approaches to relieving congestions. This paper examines travelers’ travel strategies and route choices in a road network with a risky route and a safe route, where travel information pricing are jointly implemented. We derive the equilibrium of the risk-averse travelers with heterogeneous Values of Time (VOTs) under various information regimes. We find that information regarding the risky road conditions would not necessarily improve the expected system travel time. When there is no toll, free information surprisingly makes congestion worse. When information is not free, congestion may be reduced if both toll and information are properly priced. We also examine the distributional effects of information provision across travelers with different VOTs. Travelers with low VOTs who do not use information are not affected by the price of information. Travelers with intermediate VOTs always benefit from information provision regardless of its price. Finally, travelers with high VOTs are better off when the information price exceeds a threshold.

Risky Routes, Safe Suspicions: Gender, Class, and Cabs in Hyderabad, India

Abstract A robust body of literature documents how women manage their self-presentation and perceptions of sexual risk when navigating city spaces. Yet we know less about how these strategies and tactics interact with existing class relations in society. This study investigates how, in the metropolitan city of Hyderabad in India, upwardly mobile women who commute via ride-share apps and lower-class men employed as drivers navigate the temporarily shared space of the car ride within the broader context of growing public anxiety around women’s safety in the city. Drawing on interview data and participant observation, I show two empirical patterns: 1) women commuters and men cabdrivers each view the other through the lens of suspicion as relatively more powerful than themselves; and 2) while women construct men drivers as sexually rapacious and dangerous, men understand the upwardly mobile woman commuter as entitled and abusive of her class power. I argue that competing understandings of risk exacerbate social distance and reproduce class and gender hierarchies between men drivers and women commuters. I suggest that the desire for safety vocalized by women passengers, while understandable, seems to rest on a set of processes that further pathologize and “otherize” the lower-class male subject.

Do people follow neighbors? An immersive virtual reality experimental study of social influence on individual risky decisions during evacuations

This study examined social influence on individual risk-taking decisions during evacuations through an immersive virtual reality (VR)-based experiment. Participants were asked to evacuate in the case of a virtual building fire. The results suggested that participants' route choices during evacuations were affected by their neighbors' behaviors. In particular, if a risky route was less preferred due to dense smoke, the effect of neighbor behavior was strongest when enticing participants to take the risky route. Nonetheless, the number of virtual neighbors did not significantly change the degree of social influence on participants' route choices. Moreover, an increase in smoke density significantly reduced the number of participants making risky decisions. The results also indicated that individuals had a tendency to follow others when making risky decisions, but they were not blindly following others. Individuals made their evacuation route decisions by engaging in comprehensive consideration of various types of environmental information.

The Effect of Regret-Based Risky Route Choice on the Traffic Equilibrium for Emergency Evacuation

Following the research on human decision-making under risk and uncertainty, the purpose of this paper is to analyze evacuees’ risky route decision behavior and its effect on traffic equilibrium. It examines the possibility of applying regret theory to model travellers’ regret-taking behavior and network equilibrium in emergency context. By means of modifying the utility function in expected utility theory, a regret-based evacuation traffic equilibrium model is established, accounting for the evacuee’s psychological behavior of regret aversion and risk aversion. Facing two parallel evacuation routes choice situation, the effect of evacuees’ risk aversion and regret aversion on traffic equilibrium is numerically investigated as well as the road capacity reduction from natural disaster. The findings reveal that evacuees prefer the riskless route with the lower travel time as the increase of the regret aversion degree. The equilibrium tends to be achieved when more evacuees choose the safer route jointly affected by risk aversion and regret aversion. Moreover, an optimization model for disaster occurring possibility is formulated to assess the traffic system performance for evacuation management. These findings are helpful for understanding how the regret aversion and risk aversion influence traffic equilibrium.

User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network

This paper studies travelers’ context-dependent route choice behavior in a risky trafficnetwork from a long-term perspective, focusing on the effect of travelers’ salience characteristics. In particular, a flow-dependent salience theory is proposed for this analysis, where the flow denotes the traffic flow on the risky route. In the proposed model, travelers’ attention is drawn to the salient travel utility, and the objective probabilities of the state of the world are replaced by the decision weights distorted in favor of this salient travel utility. A long-run user equilibrium will be achieved when no traveler can improve his or her salient travel utility by unilaterally changing routes, termed salient user equilibrium, which extends the scope of the Wardropian user equilibrium. Furthermore, we prove the existence and uniqueness of this salient user equilibrium. Finally, numerical studies demonstrate our theoretical findings. The equilibrium results show non-intuitive insights into travelers’ route choice behavior. (1) Travelers can be risk-seeking (the travel utility of a risky route is small with a relatively high probability), risk-neutral (in special situations), or risk-averse (the travel utility of a risky route is large with a relatively high probability), which depends on the salient state. (2) The extent of travelers’ risk-seeking or risk-averse behavior depends on their extent of salience bias, while the risk-neutral behavior is irrelative to this salience bias.

From Affects to Contentious Politics.Dis

Since 2015, the reintroduction of controls at northern Italian borders forced asylum seekers to take risky routes to reach their destinations in the European Union (EU). While several deaths have been registered since 2015 along the whole Alpine chain as a consequence of asylum seekers’ exposure to risk, some local villagers experienced unexpected encounters with migrants in distress transiting along mountain pathways. Based on six months of empirical fieldwork on the French-Italian border be...

Promoting sustainability of the integrated production-inventory-distribution system through the Physical Internet

Owing to its interconnections and open characteristics, Physical Internet (PI) has the potential to help companies meet the sustainability challenges. In this paper, to investigate the sustainability performance of the PI in an integrated production-inventory-distribution system, we propose a multi-objective mixed integer linear programming model (MOMILP) that encompasses all three dimensions of sustainability. The economic and environmental objectives are measured through the total cost and greenhouse gas (GHG) emissions, respectively. The social objective is captured by the impact of accident risk. Then, we solve the model by using the augmented ϵ-constraint method and compare the sustainability performance of the PI-enabled model with that of models enabled by the traditional (TR) and horizontal collaboration (HC) networks. The results show that the PI can not only improve the economic and environmental performance by increasing vehicle utilisation, but also alleviate the impacts of accident risks by avoiding risky routes. More interestingly, good compromise solutions featuring the PI can further improve the sustainability performance while guaranteeing the performance of the TR at the ideal point—something unachievable for the HC and TR. Moreover, sensitivity analyses demonstrate that the PI can still guarantee significant sustainability performance advantages under different common retailer quantities and network structures.

Minimizing the Risks of Highway Transport of Hazardous Materials

Many key industrial and scientific processes, such as the generation of nuclear energy, are of enormous social benefit as energy demand and consumption grow over time. However, a drawback of several such processes is the production of hazardous waste materials, which often requires transportation along highway networks to treatment or disposal facilities. This waste can represent a safety hazard to civilians located along the transportation route. Most prior literature in this domain considers risk within only a single facet, and thus several important risk factors may not be considered. In our paper, we propose a multi-objective program to allow for the analysis and selection of minimally risky routes for hazardous materials transportation. The model assesses risk factors including the length of the selected route, the total population in areas surrounding the selected route, and the likelihood of an accident occurring along the selected route. Our paper uniquely uses geographic information systems (GIS) technology to model this optimization problem. This approach allows us to model risk along multiple dimensions simultaneously. We collect empirical data to test the model and present a case study for risk mitigation using a study area located in California. We show that our multi-objective approach is effective in presenting the decision-maker with a portfolio of solutions that perform well via each factor.

“Not for Human Consumption”: A Descriptive Investigation into User Characteristics, Motives, and Consequences Associated with Bath Salt Use

ABSTRACTSynthetic cathinones, commonly referred to as “bath salts,” are recreational designer drugs that recently emerged as a drug of abuse. However, little is known about bath salt users, particularly in the United States (US). This descriptive study aims to better characterize users and user behavior, including common motives for and consequences of use. Individuals with a lifetime history of bath salt use (BSU; n = 110) completed an Internet survey. Participants (50.9% male) were aged 18 to 58 (M = 31.21, SD = 10.25) years and were from 32 US states. Most participants reported past-year BSU, via intranasal use, obtained from a friend or acquaintance. Recreational motives (e.g., to get high, experimentation) were commonly reported, as was use due to drug availability. Participants reported experiencing an average of 5.50 consequences, with both physical (e.g., rapid heartbeat) and psychological (e.g., anxiety) negative outcomes commonly reported. This descriptive information on BSU from a small but diverse sample of users may inform efforts to reduce use and negative consequences, such as eliminating riskier routes of administration (e.g., injection) and targeting specific motives for use (e.g., providing alternative methods for mood expansion).

Evaluating decision making in a multi-objective route planning-task

The present study is an initial investigation of complex decision making performance. Specifically, this work investigated how individuals make decisions involving risk and uncertainty within a spatially focused route planning task involving multiple simulated unmanned vehicles and objectives. Forty-three participants were instructed to create twenty-four route plans, half of which included a combination of risky route suggestions and enhanced icons. Given the high working memory demands of developing a route for multiple vehicles, it was expected that enhanced visualizations, which provided redundant information on target priority, uncertainty, and deadline, would reduce demands on working memory and improve performance. Additionally, it was predicted that providing risky route suggestions would negatively impact performance, yet enhanced visualizations would reduce the effect of risky route suggestions. However, findings supported neither hypothesis; there was no performance difference in providing enhanced visualizations, and risky sub-optimal route suggestions actually improved the expected value of the submitted route. These results could have occurred due to multiple factors, including the multi-objective route planning task being too complex, or the scenarios lacking sufficient variability in expected value. An additional interpretation of these findings is that humans are really poor at performing these complex multi-objective tasks, and failed to comprehend the uncertainty and risk inherent in their decisions.

Modeling Day-to-Day Dynamics of Travelers’ Risky Route Choices under the Influence of Predictive Traffic Information

In stochastic transport networks, travelers tend to reserve a “travel time budget” (TTB) for every alternative route to assure their punctual arrival with a predefined confidence level. This paper incorporates the concept of TTB into a deterministic nonlinear dynamic system to model the day-to-day evolution process of travelers’ risk-taking route choices in stochastic degradable road networks. This paper also introduces consistent traffic information prediction, which can be provided by advanced traveler information systems (ATIS), into the dynamic system to investigate its influence on travelers’ route choice behaviors and the corresponding day-to-day network flow evolutions. In the proposed dynamic model, ATIS-equipped travelers are distinguished from those not so equipped to reflect traveler heterogeneity in access to traffic information. Some theoretical analyses are further conducted to investigate the existence and uniqueness of the fixed point, and the stability of the day-to-day dynamic model. The analysis results show that consistent predictive traffic information can help to stabilize day-to-day network flow fluctuations and thus can enhance fixed-point stability of the dynamic model. In addition, this paper investigates the effects of travelers’ attitudes to risk on the network flow evolution process. An illustrative example is presented to demonstrate the characteristics of the dynamic model as well as to verify the theoretical analysis results.

FROM DOBROLYOT TO AEROFLOT

For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version). ABSTRACT Air transport arose due to man’s persistent desire to fly. It evolved from eccentricity, through experiments to regular communication between the most distant corners of the planet. Passenger air travel is a little more than 100 years old. Aeroflot, the legendary company that connects cities and villages, continents and countries, stands at the origins of civil aviation in Russia. The biography of Aeroflot is the history of development of domestic aircraft construction, development of once dangerous and risky routes, rapid technical progress and competition with the largest aviation companies in the world. The author describes some curious facts from the history of Aeroflot company. Keywords: air transport, civil aviation, history, Aeroflot, transport market, corporate culture.

Inventory routing problem for hazardous and deteriorating items in the presence of accident risk with transshipment option

In this study, we address an Inventory Routing Problem for hazardous and deteriorating pharmaceutical items in a healthcare network. Each hospital's demand is assumed to be deterministic but time varying over a finite planning horizon. Demand can be satisfied through a supply network, either from the main central pharmacy, or from other related hospitals' drugstores by allowing the transshipment option. The medicines deteriorate under a constant rate during the storage period. The proposed model is a bi-objective mixed integer mathematical programming. The first objective aims to minimize the total cost of logistics including ordering, transportation, delivery, pickup, shortage and inventory holding costs. The second objective function attempts to minimize the maximum accident loss during distribution among all periods. To consider the accident loss, for each route, two essential parameters are estimated based on historical data; the occurrence probability and severity index of accident. The model therefore attempts to utilize the best configuration of the routes and transshipment option to satisfy the demand while minimizing the costs and accident loss simultaneously. Several numerical examples are generated and solved by CPLEX and compared with the solutions of an efficient Hybrid Genetic Algorithm (HGA). The results show that the transshipment option not only can be used as a lever to increase the economic supply network performance through saving the routes, but also it can help the system to avoid risky routes.

Departure time and route choices in bottleneck equilibrium under risk and ambiguity

This paper examines commuters’ departure time and route choices in the morning commute problem when a true distribution of travel time is unknown but belongs to a bounded distributional uncertainty set. The travel preferences towards risk and ambiguity are distinguished by adopting the criterion of ambiguity-aware Constant Absolute Risk Aversion (CARA) travel time. We first examine the dynamic user equilibrium for a single-route model with a homogeneous preference towards risk and ambiguity. Compared with risk-neutral commuters, we find that departure time window is shifted earlier for the risk-averse commuters and shifted later for the risk-seeking commuters. We also study the single bottleneck with a risk-averse class and a risk-seeking class. We show that with a larger gap between the two classes’ preferences, the congestion pattern will change from one peak to two peaks. It implies that preference heterogeneity may stagger the departure time choices and thereby relieve the average congestion. Last, we examine a two-route problem with homogeneous preference. Commuters choose between a fast and risky route (highway) and a slow and safe route (local arterial). We prove the monotonicity of the traffic flow distribution between the two routes with respect to the maximum variation in travel time. Furthermore, we find that reducing the uncertainty on the highway by providing information will reduce the total system cost and the total expected congestion simultaneously for risk-averse commuters. However, it will reduce the total expected congestion but increase the total system cost for risk-seeking commuters. In the numerical section, the price of anarchy is analyzed by varying the risk preference and the ambiguity preference.

Departure Time and Route Choices with Bottleneck Congestion: User Equilibrium under Risk and Ambiguity

Abstract: This paper examines commuters’ departure time and route choices in the morning commute problem when travel time is described as a bounded distributional uncertainty set. The preferences towards risk and ambiguity are distinguished by adopting the ambiguity-aware constant absolute risk aversion travel time criteria. We first examine the dynamic user equilibrium for a single-route model with homogeneous risk/ambiguity preference. Compared with risk-neutral commuters, we find that departure time window is shifted earlier for the risk-averse commuters and shifted later for the risk-seeking commuters. We then study the single bottleneck with a risk-averse class and a risk-seeking class. It is shown that with a larger gap between the two classes’ preferences, the congestion pattern will change from one peak to two peaks. It implies that preference heterogeneity may stagger the departure time choice and thereby relieve the average congestion. At last, we examine a two-routes problem with homogeneous preference towards risk and ambiguity. The commuters will choose between a faster route (highway) and a less risky route (local arterial). We prove that the flow distribution between the two routes will monotonically change with the maximum variation in travel time. That is, the highway flow will decrease with uncertainty on the highway for risk-averse commuters. In contrast, it will increase with uncertainty on the highway for risk-seeking commuters. The price of anarchy is analyzed in the numerical section by varying the risk preference and the ambiguity preference.

Understanding cyclists’ risky route choice behavior on urban road sections

Abstract Cyclists are vulnerable road users in traffic accidents. The safety problem caused by risky behavior of cyclists is severe. This study is intended to understand cyclists’ risky route choice behavior on road sections from the view point of safety. Stated Preference survey is adopted to investigate the cyclist’ route choice on fixed origin and destination points. Three alternative routes are available: riding conforming to rules, crossing at midblock without zebra crossings, and riding in the wrong direction. A novel virtual simulation method is adopted in choice scenarios to improve presentation of the attributes of road sections and traffic conditions. Random parameter models are estimated to find out how individual characteristics, bicycle types, trip attributes and built environment will influence cyclists’ safety perception and risky behavior. The trade-offs between safety perception and travel distance are estimated in route choice model. In safety perception model, the significant attributes differ within three routes: respondents mainly pay attention to the number of motor lanes, motor volume when crossing the road; while for riding in the wrong direction, distance of wrong way and separation type are more considerable factors.