Dynamic stop pooling for flexible and sustainable ride sharing

Ride sharing -- the bundling of simultaneous trips of several people in one vehicle -- may help to reduce the carbon footprint of human mobility. However, the complex collective dynamics pose a challenge when predicting the efficiency and sustainability of ride-sharing systems. Standard door-to-door ride sharing services trade reduced route length for increased user travel times and come with the burden of many stops and detours to pick up individual users. Requiring some users to walk to nearby shared stops reduces detours, but could become inefficient if spatio-temporal demand patterns do not well fit the stop locations. Here, we present a simple model of dynamic stop pooling with flexible stop positions. We analyze the performance of ride sharing services with and without stop pooling by numerically and analytically evaluating the steady state dynamics of the vehicles and requests of the ride sharing service. Dynamic stop pooling does a-priori not save route length, but occupancy. Intriguingly, it also reduces the travel time, although users walk parts of their trip. Together, these insights explain how dynamic stop pooling may break the trade-off between route lengths and travel time in door-to-door ride sharing, thus enabling higher sustainability and service quality.

Route Planning of Helicopters Spraying Operations in Multiple Forest Areas

It is of great value to research the problem of forest pest and disease control. Currently, helicopters play an important role in dealing with this problem. However, the spraying route planning still depends on the pilot’s driving experience, which leads to low efficiency and less accurate coverage. For this reason, this paper attempts to use intelligent algorithms to plan the pesticide spraying route for helicopters. When the helicopter is conducting spraying operations in multiple forest areas, the routes are divided into two parts: pesticide spraying routes for individual forest areas and dispatch routes between multiple forest areas. First, the shorter spraying route with fewer turnarounds for individual forest areas was determined. Then a two-layer intelligent algorithm, a combination of a genetic algorithm (GA) and ant colony optimization algorithm (ACO), was designed to determine the dispatch route between multiple forest areas, which is referred to as GAACO-GA. The performance was evaluated in self-created multiple forest areas and compared with other two-layer intelligent algorithms. The results show that the GAACO-GA algorithm found the shortest dispatch route (5032.75 m), which was 5.60%, 5.45%, 6.54%, and 4.07% shorter than that of GA-GA algorithm, simulated annealing-GA (SA-GA) algorithm, ACO-GA algorithm, and particle swarm optimization-GA (PSO-GA) algorithm, respectively. A spraying experiment with a helicopter was conducted near Pigzui Mountain, Huai’an City, Jiangsu Province, China. It was found that the flight path obtained from the proposed algorithm was 5.43% shorter than that derived from a manual planning method. The dispatch route length was reduced by 16.93%, the number of turnarounds was reduced by 11 times, and the redundant coverage was reduced by 17.87%. Moreover, helicopter fuel consumption and pesticide consumption decreased by 10.56% and 5.43%, respectively. The proposed algorithm can shorten the application route, reduce the number of turnarounds and the cost of spraying operations, and has the potential for use in spraying operations in smart forestry and agriculture.

Modelling geographical and built environment’s attributes as predictors of human vulnerability during tsunami evacuations: a multi-case study and paths to improvement

Evacuation is the most important and effective method to save human lives during a tsunami. In this respect, challenges exist in developing quantitative analyses of the relationships between the evacuation potential and the built environment and geographical attributes of coastal locations. This paper proposes a computer-based modelling approach (including inundation, evacuation, and built environment metrics), followed by multivariate regressive analysis, to estimate how those attributes might influence the expected tsunami death ratios of seven Chilean coastal cities. We obtained, for the examined variables, their average values to different thresholds of the death ratio. Also, our statistical analysis allowed us to compare the relative importance of each metric, showing that the maximum flood, the straightness of the street network, the total route length, and the travel time can have a significant impact on the expected death ratios. Moreover, we suggest that these results could lead to spatial planning guidelines for developing new urban areas into exposed territories (if this expansion cannot be restricted or discouraged) or retrofitting existing ones, with the final aim of enhancing evacuation and therefore increasing resilience.

INFLUENCE OF ERRORS IN DETERMINATION OF TRACING SLOPE ON THE ACCURACY OF GEODETIC BASE FOR ROUTE

The purpose of this article is to study and develop a methodological approach tosolving the problem of accuracy of the geodetic base of the route. For this purpose, the followingtasks are set: mathematical substantiation the dependence of the line length on the ratio of the traceslope and the guide slope; description of the function of optimal use of the guiding slope at highspeed; determination of the impact of errors in the course of the geodetic justification on the routelength. Starting from the determined point and further to the right, artificial development of the lineis required. Because when a trace is planed using level curves, this point can be reached sooner orlater, and in some cases, this point can not be reached not at all, the line length designed accordingto the plan will be slightly different than in the case of tracing with usage the exact data. Thus, theobtained results indicate the following. If the error positions during a high-speed segment are suchthat the ordnance datum of the passage is less than the truth, the route length will be less than thetrue and vice versa. This trivial result indicates that the location of geodetic support points ondifferent sides of the pass is not recommended. It is established that due to the accumulation of errorsin the transmission of coordinates in the working substantiation networks, the conditions of the linedesign and the amount of operating costs change. It is mathematically substantiated that the linelength depends on the depth of the excavation on the pass and the height of the embankment at thepoint, and also on the difference of ordnance datum at these points. The difference between the traceslope and the guiding slope has an inversely proportional effect. In addition, the function of optimaluse of the guide slope at a high-speed segment has the form of a broken line according to its fracturesthe need for artificial development of the route can be established. The influence of errors in the course of the working justification is manifested in the discrepancy between the true and projectedroute length. If this error is not taken into account, it will lead to significant overspending duringbuilding a longer line than necessary. Further development of the problem of increasing the accuracyof tracing and reducing the impact of errors is planned in the direction of creating methods of digitalmodelling and automated programs.

Procedures of Detecting Damage to a Conveyor Belt with Use of an Inspection Legged Robot for Deep Mine Infrastructure

Conveying systems are responsible for a large part of continuous horizontal transportation in underground mines. The total length of a conveyor network can reach hundreds of kilometers, while a single conveyor usually has a route length of about 0.5–2 km. The belt is a critical and one of the most costly components of the conveyor, and damage to it can result in long unexpected stoppages of production. This is why proper monitoring of conveyor belts is crucial for continuous operation. In this article, algorithms for the detection of potential damage to a conveyor belt are described. The algorithms for analysis used video recordings of a moving belt conveyor, which, in case the of hazardous conditions of deep mines, can be collected, for example, by a legged autonomous inspection robot. The video was then analyzed frame by frame. In this article, algorithms for edge damage detection, belt deviation, and conveyor load estimation are described. The main goal of the research was to find a potential application for image recognition to detect damage to conveyor belts in mines.

Optimization Of Cutting Chicken Routes

This study has the title Optimization of Chicken Cut Retrieval Route. The existence of this study aims to reduce the distance of chicken retrieval routes from cages to slaughter mills, as well as reduce the number of deaths and chicken kesetresan when descending from the chicken carrier fleet. The method in the study used saving matrix method and vehicle routing problem. The method of data collection used is to take primary data that is taken data from the location of cut parik and chicken coop taken by the fleet so far and secondary data taken dati preentase route from the slaughter plant to the chicken coop. And obtained the maximum chicken cut and decreased the death rate and chicken kesetresan with the length of saving matrix route 219.58 Km, using 5 trucks, spent fuel Rp. 141.263, and driver's salary of Rp. 26.250.000. While using vehicle routing problem route length 209.38 Km, using 5 trucks, spent fuel Rp. 134.775, and driver's salary of Rp. 26.250.000.

Empirical Estimation of Shortest Route Length along U.S. Interstate Highways Based on Great Circle Distance

In this study, 98 regression models were specified for easily estimating shortest distances based on great circle distances along the U.S. interstate highways nationwide and for each of the continental 48 states. This allows transportation professionals to quickly generate distance, or even distance matrix, without expending significant efforts on complicated shortest path calculations. For simple usage by all professionals, all models are present in the simple linear regression form. Only one explanatory variable, the great circle distance, is considered to calculate the route distance. For each geographic scope (i.e., the national or one of the states), two different models were considered, with and without the intercept. Based on the adjusted R-squared, it was observed that models without intercepts generally have better fitness. All these models generally have good fitness with the linear regression relationship between the great circle distance and route distance. At the state level, significant variations in the slope coefficients between the state-level models were also observed. Furthermore, a preliminary analysis of the effect of highway density on this variation was conducted.

Optimization for medical logistics robot based on model of traveling salesman problems and vehicle routing problems

Fast medicine dispensing system (FMDS) as a kind of medical logistic robot can dispense many drugs for one prescription at the same time. To guarantee the sustainability of drug dispensation, it is required that FMDS replenish drugs rapidly. The traditional order picking model (OPM) is difficult to meet the demand of prompt replenishment. To solve the problems of prolonged refilling route and inefficiency of drugs replenishment, a mixed refilling model based on multiple steps traveling salesman problem model (MTSPM) and vehicle routing problem model (VRPM) is proposed, and it is deployed in two circumstances of FMDS, including temporary replenishment mode (TRM) and concentrate replenishment mode (CRM). It not only meted the demand under different circumstances of drug replenishment but also shortened the refilling route significantly. First, the new pick sets were generated. Then, the orders of pick sets were optimized and the new paths were achieved. When the number of pickings is varied no more than 20, experiment results declared that the refilling route is the shortest by utilizing MTSPM when working under the TRM condition. Comparing MTSPM with OPM, the rate of refilling route length decreased up to 32.18%. Under the CRM condition, the refilling route is the shortest by utilizing VRPM. Comparing VRPM with OPM, the rate of refilling route length decreased up to 58.32%. Comparing VRPM with MTSPM, the rate of refilling route length has dropped more than 43.26%.

Emergency Response: Navigable Networks and Optimal Routing in Hazardous Indoor Environments

The extreme importance of emergency response in complex buildings during natural and human-induced disasters has been widely acknowledged. This chapter studies algorithms for safest routes and balanced routes in buildings where an extreme event with many epicentres is occurring. In a balanced route, a trade-off between route length and hazard proximity is made. Another algorithm is proposed for finding the optimal indoor routes for search and rescue teams. This is based on a novel approach integrating the Analytic Hierarchy Process (AHP), the propagation of hazard and other techniques, and where three criteria are used: hazard proximity, distance/travel time, and route complexity. The important feature of the algorithm is its ability to generate an optimal route depending on the user’s needs. Finally, a novel automated construction of the Variable Density Network (VDN) for determining egress paths in dangerous environments is discussed.

Location flexibility in parcel delivery operations: framework and empirical analysis

In traditional parcel delivery operations, customers determine delivery locations and, hence, the performance of a transporter. We exploit this idea and show that customers can improve the efficiency of a transporter by giving the latter flexibility in choosing the delivery locations. Two possible policies to enable this flexibility are presented and evaluated. The first policy, conceptually similar to roaming vehicle routing, is related to the presence of alternative locations. The second policy is related to the possibility of aggregating/skipping some locations. We show that route optimization behind both policies can be modelled via the well-known generalized travelling salesman problem. Extensive computational experiments with real parcel delivery data are performed to evaluate the potential of the presented policies and to obtain insights for possible implementation in daily practice. The experiments show that under certain conditions, the two proposed policies can lead to 15 to 20% improvement in the route length and in extreme yet realistic cases up to 40 to 50%. Consequently, the concept of flexible delivery locations has potential for practice, especially in densely populated areas.