A note on the square root law for urban police travel times

The classical Square Root Law formula for emergency travel times consists of one observable component, the density of patrol coverage, and one unknown component that must be estimated empirically, the effective travel speed. The effective travel speed is typically assumed to be an empirical constant. We test whether this simplifying assumption is justified empirically. We propose a modern machine-learning approach and a Least Absolute Shrinkage and Selection Operator regression to incorporate into a travel speed model various exogenous factors such as call type, incident location, weather conditions and traffic congestion. The value of the proposed analytical approach and some practical implications are demonstrated using operational data from a large urban police jurisdiction based in British Columbia, Canada. Although the analysis is framed within the context of urban emergency police operations, the proposed approach has the potential to be useful for other emergency services or roving business units that deal with unscheduled service calls.     

Queueing models for police-fire merger analysis

Cities with under 100,000 in population expend a significant portion of their budgets on emergency services. One option that a number of these cities have considered for improving service and cutting costs is training personnel to handle both police and fire roles. In this paper we describe a hierarchy of models that we have used to assess the performance viability of a merger as well as to design specific deployment plans. The modeling environment is more complex than a traditional police or fire system. We need to model the response pattern of four or more patrol units along with the simultaneous dispatch of fire equipment from one or more fire stations. The major contribution of the paper is the manner in which a series of models is linked together to forecast a wide range of performance measures under differing dispatch assumptions. We use a queueing model of police patrol to calculate steady state probabilities and expected delays without preemption. We then model two types of preemptive dispatch strategies utilized in responding initially to a major fire by superimposing a binomial distribution on the basic queueing model. There is also a travel time simulation model to calculate conditional expected response time statistics. The queueing models and the travel time simulation are then combined to estimate unconditional expected values. Lastly, we describe a simulation model used to address transient performance issues that are of concern during a major fire.     

Un modelo de difusión anisótropa para el estudio del tráfico urbano

In order to design or redesign urban transportation networks, the employment of mathematical models is very useful for predicting the effects of possible modifications of implementing. Such models allow the determination of vehicular flows and travel times for every link of the network from the knowledge of its inherent features and the corresponding traffic demand. They are based on a phenomenological law of the social collective behavior of the drivers called Wardrop principle. It is an optimization problem, in general, very demanding from the computational point of view.In order to accelerate the computation process, in this paper, a continuum model for the urban traffic is proposed. The fundamental assumption behind this theory is that the variation of network properties is small in close regions when compared with the full system. Accordingly, it is possible to use continuous functions for representing travel times or vehicular flows. Essentially, the problem is formulated as a system of non-linear anisotropic diffusion (differential) equations that can be conveniently solved by means of the finite element method. The efficiency of the proposed model is studied by means of a comparison with results obtained with the classical optimization approach. As shown, the results are similar although the computation times are significantly reduced.     

A matheuristic algorithm for stochastic home health care planning

Efficient human resource planning is the cornerstone of designing an effective home health care system. Human resource planning in home health care system consists of decisions on districting/zoning, staff dimensioning, resource assignment, scheduling, and routing. In this study, a two-stage stochastic mixed integer model is proposed that considers these decisions simultaneously. In the planning phase of a home health care system, the main uncertain parameters are travel and service times. Hence, the proposed model takes into account the uncertainty in travel and service times. Districting and staff dimensioning are defined as the first stage decisions, and assignment, scheduling, and routing are considered as the second stage decisions. A novel algorithm is developed for solving the proposed model. The algorithm consists of four phases and relies on a matheuristic-based method that calls on various mixed integer models. In addition, an algorithm based on the progressive hedging and Frank and Wolf algorithms is developed to reduce the computational time of the second phase of the proposed matheuristic algorithm. The efficiency and accuracy of the proposed algorithm are tested through several numerical experiments. The results prove the ability of the algorithm to solve large instances.     

多方式弹性需求下公交定价双层规划模型

为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。     

Estimation of Travel Times in Multiple Mode Systems<Superscript>†</Superscript>

This paper describes a procedure for generating estimates of the minimum travel times (shortest distances, least cost routes) between pairs of points on a standard map. The procedure exhibits substantial improvements in accuracy over the traditional generation methods involving simple orthogonal and vector-directed distance metrics. These improvements are achieved by combining the traditional methods with algorithms which find shortest routes in networks. The new procedure is particularly appropriate to the analysis of transportation or distribution systems which entail "multiple-mode travel", e.g. surface road vs. expressway travel, or railway vs. air travel. The advantages of the procedure are illustrated with empirical evidence from a simulation study of travel times in a large urban area. Finally, the generality of this procedure to a wide class of problems is discussed.     

An anisotropic continuum model for traffic assignment in mixed transportation networks

This work deals with a two-dimensional continuum model for the problem of congested traffic assignment in an urban transportation system consisting of a set of freeways superimposed over a dense street network. The formulation leads to a system of non-linear differential equations whose unknowns are given by the travel times from arbitrary points of the network to the corresponding destinations. The governing equations are appropriately solved by means of the Finite Element Method. Then, traffic flow on every link of the network can be obtained. Numerical examples are given in order to demonstrate the efficiency of the developed model.     

The Queueing Maximal availability location problem: A model for the siting of emergency vehicles

The Maximal Availability Location Problem (MALP) has been recently formulated as a probabilistic version of the maximal covering location problem. The added feature in MALP is that randomness into the availability of servers is considered. In MALP, though, it is assumed that the probabilities of different servers being busy are independent. In this paper, we utilize results from queuing theory to relax this assumption, obtaining a more realistic model for emergency systems: the Queueing MALP or Q-MALP. We also consider in this model that travel times or distances along arcs of the network are random variables. We show here how to site limited numbers of emergency vehicles, such as ambulances, in such a way as to maximize the calls for service which have an ambulance available within a time or distance standard with reliability α — using a queueing theory model for server availability. We also propose some extensions to the basic model. Formulations are presented and computational experience is offered.     

A study of travel time prediction using universal kriging

This study describes an approach for predicting travel time by kriging. The kriging method, which is a means of spatial prediction, is used as prediction measure for car travel time in an imaginary four-dimensional space. Each point in the space represents a single journey: the coordinates of a point are the coordinates of the origin and destination on a plane. The travel time can then be viewed as a function over this four-dimensional space. The prediction relies on the feature that nearby points (in the four-dimensional space) will have almost the same travel time. In this approach, it is not necessary to break down travel times from origin to destination into link travel times. The approach will also allow us to use information from “probe vehicles” for travel time prediction in the near future. The feasibility of this approach is demonstrated through a case study in London and its environs. The case study uses 200 observations for verification. The multiple correlation coefficient of estimated travel time and the verification data is 0.9045. The results indicate that 95% prediction limits are between ±10 minutes and ±30 minutes for travel between two arbitrary points. This prediction method is effective for urban districts with links having changeable travel time owing to congestion.     

Optimizing State Patrol Manpower Allocation

One of the most difficult tasks of state highway patrol administrators is allocation of manpower; i.e. determining the most effective level of operational manpower for patrol tasks. Typically, administrators resolve the allocation problem by relying on prior statistical data and by employing subjective analysis. In general, only limited systematic analyses have been applied to the problem. This paper presents an integer goal programming model for allocating highway patrolmen to road segments within a patrol region. The model is demonstrated via a case example of the Nebraska State Patrol. The results of the model are valuable to the patrol administrator for considering departmental goals and priority structure, in addition to available historical data, in the assignment of state patrol manpower.     

A literature review on police patrolling problems

Annals of Operations Research - Police patrol is an effective crime prevention tool and boosts public confidence in urban security. Many interesting decision making problems appear in route design,...     

Bi-criteria dynamic location-routing problem for patrol coverage

In this paper, we address the problem of dynamic patrol routing for state troopers for effective coverage of highways. Specifically, a number of state troopers start their routes at temporary stations (TS), patrol critical locations with high crash frequencies, and end their shifts at other (or the same) TS so the starting points for the next period are also optimized. We determine the number of state troopers, their assigned routes, and the locations of the TS where they start and end their routes. The TS are selected from a given set of potential locations. The problem, therefore, is a multi-period dynamic location-routing problem in the context of public service. Our objective is to maximize the critical location coverage benefit while minimizing the costs of TS selections, vehicle utilizations, and routing/travel. The multi-objective nature of the problem is handled using an ?-constraint approach. We formulate the problem as a mixed integer linear programming model and solve it using both off-the-shelf optimization software and a custom-built, efficient heuristic algorithm. The heuristic, utilizing the hierarchical structure of the problem, is built on the decomposition of location and routing problems. By allowing routing to start from multiple locations, our model improves the coverage by as much as 12% compared with the single-depot coverage model.     

Locating emergency services with different priorities: the priority queuing covering location problem

Previous covering models for emergency service consider all the calls to be of the same importance and impose the same waiting time constraints independently of the service's priority. This type of constraint is clearly inappropriate in many contexts. For example, in urban medical emergency services, calls that involve danger to human life deserve higher priority over calls for more routine incidents. A realistic model in such a context should allow prioritizing the calls for service. In this paper, a covering model which considers different priority levels is formulated and solved. The model heritages its formulation from previous research on Maximum Coverage Models and incorporates results from Queuing Theory, in particular Priority Queuing. The additional complexity incorporated in the model justifies the use of a heuristic procedure.     

农村人口城市化中的时间配置决策研究

在Becker时间配置模型基础上,构建农村居民在城镇化进程中的行为决策模型,农村入口时间资源分配在农村活动、城市活动、教育活动和闲暇上,根据福利水平最大化的基本原则,分析农村人口城市化决策中影响因素.解释了农村人口城镇化和逆城镇化现象,发现城乡差异、教育影响、时间间接成本等因素是影响人们时间效率的主要因素,为提高全民福利水平,政府的农村政策应以增加农民收入为主,城市政策集中于城市基础设施和公共服务布局合理性方面.     

我国城乡居民消费与经济增长区域差异性的实证分析

遴选1996-2012年我国(除重庆、港、澳、台外)30个省(市)城镇和农村居民消费支出及国内生产总值的面板数据,基于非参数核估计方法,建立固定效应半参数面板数据模型,对我国东、中、西部城乡居民消费与经济增长关系的区域差异性进行实证分析.计算显示,运用半参数面板数据模型显著提高了估计的精度.分析结果表明,不论是城镇居民消费还是农村居民消费,对经济增长的促进作用均是东部高于中部、中部高于西部;且农村居民消费对经济增长的促进作用又大于城镇居民消费.     

Transportation systems and residential location

An optimization model for the spatial allocation of residents in an urban region is presented. The model allocates an exogenously given population on the basis of travel time (to workplaces) and population density criteria and subject to local and subregional capacity constraints. A way of calibrating the ‘value’ parameters of the model on a short-term plan proposal is outlined. Some applications of the model to planning problems of the Stockholm region are reported. These include sensitivity analyses of the population distribution of an adopted plan with respect to its exogenous assumptions (particularly those describing the transportation system). When evaluating investments with long life times, there is a strong need for long-term land use scenarios. Some long-range applications in the field of traffic and energy planning are reported. They can be seen as ‘prolongations’ of the adopted regional plan based on the preferences ‘revealed’ by the calibration procedure. Further extensions of the model to cover cost and energy considerations of urban developments are also outlined.     

基于消费函数模型的居民消费能力与趋势的实证分析

对浙江省城乡居民消费能力的重要指标应用计量经济学,建立城乡居民的消费函数模型,并用定性分析与定量研究相结合的方法,就城乡居民消费能力与趋势进行计量经济的实证分析.进而探讨城乡居民消费水平的差距,寻求持续稳定提高城乡居民消费水平的主要途径.研究表明所建消费函数模型具有较高的拟合精度,且很好的反映了城乡居民消费能力的发展现状和趋势.对促进城乡居民消费能力的协调发展,缩小城乡居民消费水平差距等具有一定的现实意义.     

面向突发事件的安保巡逻选址-路径优化研究

安保巡逻任务要求以中心会场为保卫目标,进行指挥中心的选址、巡逻线路的规划。考虑区域环境、安保主体及突发事件对巡逻线路优化的影响,依据警方安保任务的规划流程,建立了多约束条件下安保指挥中心选址-巡逻路径规划的优化模型。设计了基于真实安保区域特征的安保中心模拟试验,各区域由专家依据CPTED理论进行评定分级,利用遗传算法求解并对结果进行了模拟检验,提出了基于整体应急水平最优的安保巡逻策略。     

User equilibrium traffic network assignment with stochastic travel times and late arrival penalty

The classical Wardrop User Equilibrium (UE) assignment model assumes traveller choices are based on fixed, known travel times, yet these times are known to be rather variable between trips, both within and between days; typically, then, only mean travel times are represented. Classical Stochastic User Equilibrium (SUE) methods allow the mean travel times to be differentially perceived across the population, yet in a conventional application neither the UE or SUE approach recognises the travel times to be inherently variable. That is to say, there is no recognition that drivers risk arriving late at their destinations, and that this risk may vary across different paths of the network and according to the arrival time flexibility of the traveller. Recent work on incorporating risky elements into the choice process is seen either to neglect the link to the arrival constraints of the traveller, or to apply only to restricted problems with parallel alternatives and inflexible travel time distributions. In the paper, an alternative approach is described based on the ‘schedule delay’ paradigm, penalising late arrival under fixed departure times. The approach allows flexible travel time densities, which can be fitted to actual surveillance data, to be incorporated. A generalised formulation of UE is proposed, termed a Late Arrival Penalised UE (LAPUE). Conditions for the existence and uniqueness of LAPUE solutions are considered, as well as methods for their computation. Two specific travel time models are then considered, one based on multivariate Normal arc travel times, and an extended model to represent arc incidents, based on mixture distributions of multivariate Normals. Several illustrative examples are used to examine the sensitivity of LAPUE solutions to various input parameters, and in particular its comparison with UE predictions. Finally, paths for further research are discussed, including the extension of the model to include elements such as distributed arrival time constraints and penalties.     

A decision support simulation model for design of fast patrol boats

This paper gives an outline of a simulation model that will provide decision support in the complex process of designing a new generation fast patrol boats. Decision support in this context implies evaluating the effectiveness of different concepts for fast patrol boats in their primary role. The model addresses effectiveness issues at the tactical level, emphasizing a realistic and flexible representation of operations of a fast patrol boat squadron rather than individual boat operations. Main elements of the model are presented in some detail.