An integrated model of facility location and transportation network design

Network location models have been used extensively for siting public and private facilities. In this paper, we investigate a model that simultaneously optimizes facility locations and the design of the underlying transportation network. Motivated by the simple observation that changing the network topology is often more cost-effective than adding facilities to improve service levels, the model has a number of applications in regional planning, distribution, energy management, and other areas. The model generalizes the classical simple plant location problem. We show how the model can be solved effectively. We then use the model to analyze two potential transportation planning scenarios. The fundamental question of resource allocation between facilities and links is investigated, and a detailed sensitivity analysis provides insight into the model's usefulness for aiding budgeting and planning decisions. We conclude by identifying promising research directions.     

The development of a prescreening model to identify failed and gross polluting vehicles

The California State Bureau of Automotive Repair uses a high-emitter profile model to direct, or screen a fraction of the vehicle fleet in for inspection and maintenance testing at test-only facilities. Reviews by the California Inspection/Maintenance Review Committee showed the high-emitter profile to be inefficient and in need of improvement. In this study, using in-use vehicle emissions data from California’s statewide smog check program, we specified a new multinomial logit model designed to improve the screening efficiency for targeting potential failed and gross polluting vehicles. Modeling results show that factors such as odometer reading, model year, vehicle make, as well as the presence of emissions control systems are significant factors in predicting the likelihood that a screened vehicle will test as a failed or a gross polluting vehicle. Comparisons indicate that the new multinomial logit model specification can predict various inspection/maintenance test outcomes more accurately than the existing high-emitter profile model.     

城市轨道交通路网性车辆基地功能特点分析

城市轨道交通网络化运营要求整合车辆运用检修资源,提高设施设备利用率,实现资源共享。路网性车辆基地的建设是提升网络化运营效益的重要措施。本文以上海北翟路车辆基地为案例,从建设规模、建设选址、共享条件、主要工艺方案等方面,分析路网性车辆基地功能设计需求,可供类似工程借鉴与参考。     

What is the market potential of plug-in electric vehicles as commercial passenger cars? A case study from Germany

Commercial passenger cars are a possible early market segment for plug-in electric vehicles (PEVs). Compared to privately owned vehicles, the commercial vehicle segment is characterized by higher mileage and a higher share of vehicle sales in Germany. To this point, there are only few studies which analyze the commercial passenger car sector and arrive at contradictory results due to insufficient driving profile data with an observation period of only one day. Here, we calculate the market potential of PEVs for the German commercial passenger car sector by determining the technical and economical potential for PEVs in 2020 from multi-day driving profiles. We find that commercial vehicles are better suited for PEVs than private ones since they show higher average annual mileage and drive more regularly. About 87% of the analyzed three-week vehicle profiles can technically be fulfilled by battery electric vehicles (BEVs) with an electric driving range of about 110 km while plug-in hybrid electric vehicles (PHEVs) with an electric range of 40 km could obtain an electric driving share of 60% on average. In moderate energy price scenarios, PEVs can reach a market share of 2–4% in the German commercial passenger car sales by 2020 and especially the large commercial branches (Trade, Manufacturing, Administrative services and Other services) are important. However, our analysis shows a high sensitivity of results to energy and battery prices as well as electric consumptions.     

A two-sided market platform analysis for the electric vehicle adoption: Firm strategies and policy design

This study explores how to facilitate the electric vehicle (EV) diffusion from a two-sided market platform competition. We develop a stylized model depicting the platform competition between electric and gasoline vehicles by combining indirect network effects of consumer and energy supplier sides as well as vehicle manufacturers’ profits. The findings of this study provide several meaningful strategic and policy implications for EV manufacturers and policymakers who wish to enhance EV diffusion. First, EV sales are significantly influenced by indirect network effects from the energy supplier side to the consumer side, and vice versa. This implies that EV manufacturers who wish to boost EV diffusion should implement a strategy providing energy suppliers with incentives to willingly join the EV platform. Second, the dynamic nature of the effects of energy costs on platform competition might render counter-intuitive evidence that the drop in oil prices does not always negatively influence EV sales. This requires EV manufacturers to prepare a contingent strategy adjusting to such unexpected conditions. Third, governments should consider the energy supplier side as well as the consumer side in designing EV diffusion policies. When governments have a very challenging EV diffusion target, a balanced policy, which treats both gasoline and electric vehicle technologies fairly, may be more effective than a consumer subsidy policy.     

A comparative analysis of US toll policy

In the US, there is a long tradition of toll roads, beginning with the Lancaster Turnpike that was built at the end of the 18th century connecting Philadelphia and Lancaster. There are currently more than 300 toll facilities in the US, which is probably the largest number of toll facilities in the world. These facilities represent a wide range of conditions, from hypercongested facilities in large metropolitan areas such as New York City to toll highways in rural areas. The toll structures are equally diverse, ranging from multi-tier price structures with frequent user, carpool, and time of day discounts; to simpler structures in which the only differentiation is made on the basis of the number of axles per vehicle. The toll rates are typically set by the agencies that operate or own the toll facilities. The rules or formulas by which these tolls are determined are not generally available to the public, though it is safe to say that toll decisions are made taking into account technical considerations, as well as the all important criterion of political acceptability. However, data on toll rates and how they change by vehicle types and by some other attributes are readily available.The overall objective of this paper is to analyze the toll data from various facilities across the US to gain insight into the overall factors affecting the tolls. A more specific objective is to assess—though in a rather approximate fashion—if the tolls by vehicle type, relative to each other, are appropriate and consistent with economic theory. This is achieved by comparing tolls to approximate indicators of road space consumption and pavement deterioration. The literature review confirmed that this is the first time such research has been conducted which is an important first step toward an analysis of the efficiency of current toll policies.The analyses in this paper are based on a random sample of all toll facilities across the US. The toll dataset, which include toll rates for passenger cars, busses, and three different truck types, is assembled mainly from the available information on the web sites of various toll agencies. After cleaning the data, the authors used econometric modeling to estimate a set of ordinary least squares (OLS) regression models that express tolls as functions of independent variables. Three families of models were estimated: linear models, models based on expansions of Taylor series, and models based on piece-wise linear approximations to non-linear effects. The resulting models were analyzed to identify the salient features of current toll policies towards different vehicle types.     

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21%, 33%, 24% and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than non-commercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity.     

Experimental evaluation of CAM and DENM messaging services in vehicular communications

The Cooperative Awareness Basic Service and Decentralized Environmental Notification Basic Service have been standardized by the European Telecommunications Standards Institute (ETSI) to support vehicular safety and traffic efficiency applications needing continuous status information about surrounding vehicles and asynchronous notification of events, respectively. These standard specifications detail not only the packet formats for both the Cooperative Awareness Message (CAM) and Decentralized Environmental Notification Message (DENM), but also the general message dissemination rules. These basic services, also known as facilities, have been developed as part of a set of standards in which both ISO and ETSI describe the Reference Communication Architecture for future Intelligent Transportation Systems (ITS). By using a communications stack that instantiates this reference architecture, this paper puts in practice the usage of both facilities in a real vehicular scenario. This research work details implementation decisions and evaluates the performance of CAM and DENM facilities through a experimental testbed deployed in a semi-urban environment that uses IEEE 802.11p (ETSI G5-compliant), which is a WiFi-like communication technology conceived for vehicular communications. On the one hand, this validation considers the development of two ITS applications using CAM and DENM functionalities for tracking vehicles and disseminating traffic incidences. In this case, CAM and DENM have demonstrated to be able to offer all the necessary functionality for the study case. On the other hand, both facilities have been also validated in a extensive testing campaign in order to analyze the influence in CAM and DENM performance of aspects such as vehicle speed, signal quality or message dissemination rules. In these tests, the line of sight, equipment installation point and hardware capabilities, have been found as key variables in the network performance, while the vehicle speed has implied a slight impact.     

Exploring public bicycle network structure based on complex network theory and shortest path analysis: the public bicycle system in Yixing,China

A well-functioning public bicycle system relates not only to its mode of operation, vehicle allocation, rental station layout and vehicle leasing configuration, but also the bicycle network structure and its formation. However, the latter aspects have been widely overlooked in China. Here, we help to further attract more researchers to conduct relevant studies and make suggestions for the development of public bicycle transport in many small and medium-sized cities across the world. We demonstrate how to explore the public bicycle network structure of a county-level Chinese city – Yixing – known for its clay ware and tourism. We show that complex network theory and shortest path analysis technology are useful in characterizing the public bicycle network structure, in aspects such as network topology, the spatial distribution of sub-networks and traffic flows. Finally, the paper proposes relevant urban planning strategies.     

Differences in single heavy vehicle crashes at intersections and midblocks

The objective of this research is to identify the factors differentiating between single heavy vehicle collisions at intersections and midblocks by using a binary logit model. Our results show that single vehicle crashes involving heavy vehicle at intersections are more likely to occur on main roads and highways, whereas crashes at midblocks are more likely to occur on divided two‐way roads, roads with special facilities or features (e.g. bridge) and roads with a higher percentage of heavy vehicle traffic. Intersection crashes are also more likely to involve vehicles that are turning left or right, resulting in angle crashes and vehicle overturn, whereas midblock crashes are more likely to involve vehicles on higher posted speed roads. Copyright © 2017 John Wiley & Sons, Ltd.     

Route design for last-in,first-out deliveries with backhauling

The retail route design problem extends the capacitated vehicle routing problem with time windows by introducing several operational constraints, including order loading and delivery restrictions (last-in, first-out), order-dependent vehicle capacity, material handling limits at the warehouse, backhauling, and driving time bounds. In this paper, the problem is modeled on a directed network for an application associated with a major grocery chain. Because the corresponding mixed-integer program proved too difficult to solve with commercial software for real instances, we developed a greedy randomized adaptive search procedure (GRASP) augmented with tabu search to provide solutions. Testing was done using data sets provided Kroger, the largest grocery chain in the US, and benchmarked against a previously developed column generation algorithm. The results showed that cost reductions of $4887 per day or 5.58% per day on average, compared to Kroger’s corresponding solutions.     

Failure rates and data driven policies for vehicle safety inspections in Pennsylvania

Rail, truck, commercial bus, and aircraft have federally mandated safety inspection programs in the United States, while inspections of personal vehicles, which make up the majority of passenger miles, are optionally imposed at the state level. In recent years, some states have chosen to eliminate the vehicle safety inspection program because of budget constraints and concerns about program effectiveness. Currently, 26 states have a schedule for conducting safety inspections, but Pennsylvania is one of thirteen states that currently require all personal light duty vehicles to be inspected every year. The remaining states have completely eliminated safety inspection programs. However, as automobiles become safer, Pennsylvania legislators are now pushing to phase out the inspection program to reduce the costs of owning a vehicle. This study combines Pennsylvania vehicle registration data with two large samples of results from state safety inspections. We find that the state safety inspection fail rate for light-duty vehicles is 12–18%, well above the often-cited rate of 2%. Vehicles that are older than three years old or have more than about 30,000 miles can have much higher rates. When analyzing new vehicles, less than or equal to one year old, it is found that even these vehicles have a failure rate greater than zero. Furthermore, while the vehicle fleet appears to be getting safer over the past few years by improvements in technology or other external circumstances, the inspection failure rate does not appear to be trending toward zero in the near future. We also show that accurate inspection data is limited and often incorrectly analyzed. Lastly, the importance of vehicle maintenance over a vehicle’s lifetime is proven to be evident, since regular usage causes vehicles to deteriorate. We conclude that vehicle safety inspections should continue to be implemented in order to keep driving conditions safe.     

Locating inspection facilities in traffic networks: an artificial intelligence approach

Abstract

In order for traffic authorities to attempt to prevent drink driving, check truck weight limits, driver hours and service regulations, hazardous leaks from trucks, and vehicle equipment safety, we need to find answers to the following questions: (a) What should be the total number of inspection stations in the traffic network? and (b) Where should these facilities be located? This paper develops a model to determine the locations of uncapacitated inspection stations in a traffic network. We analyze two different model formulations: a single-objective optimization problem and a multi-objective optimization problem. The problems are solved by the Bee Colony Optimization (BCO) method. The BCO algorithm belongs to the class of stochastic swarm optimization methods, inspired by the foraging habits of bees in the natural environment. The BCO algorithm is able to obtain the optimal value of objective functions in all test problems. The CPU times required to find the best solutions by the BCO are found to be acceptable.     

上海市城市机动车停车场(库)环保设计优化研究

对上海市7家建筑、环评设计院的15位工程师开展问卷调研,运用Cronbach’sα系数量化了问卷的信度,并根据调研结果,随机实测4座停车场16辆车的洗车污水,进行对标分析与Kruskal-Walli test,最终对城市机动车停车场(库)提出了设计优化建议。结果表明:问卷的Cronbach’sα系数为0.639,信度较好。未经过处理的停车场洗车污水样本存在超标现象,COD的超标区间为[4.23%,108.32%],TP的超标率为10.00%,BOD₅的超标区间为[22.40%,139.40%]。COD、BOD₅、SS的检测结果受车型大小的影响,呈正相关关系。建议从洗车设施、绿荫绿化等方面优化城市停车场(库)的环保设计。     

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

The quest for more fuel-efficient vehicles is being driven by the increasing price of oil. Hybrid electric powertrains have established a presence in the marketplace primarily based on the promise of fuel savings through the use of an electric motor in place of the internal combustion engine during different stages of driving. However, these fuel savings associated with hybrid vehicle operation come at the tradeoff of a significantly increased initial vehicle cost due to the increased complexity of the powertrain. On the other hand, telematics-enabled vehicles may use a relatively cheap sensor network to develop information about the traffic environment in which they are operating, and subsequently adjust their drive cycle to improve fuel economy based on this information – thereby representing ‘intelligent’ use of existing powertrain technology to reduce fuel consumption. In this paper, hybrid and intelligent technologies using different amounts of traffic flow information are compared in terms of fuel economy over common urban drive cycles. In order to develop a fair comparison between the technologies, an optimal (for urban driving) hybrid vehicle that matches the performance characteristics of the baseline intelligent vehicle is used. The fuel economy of the optimal hybrid is found to have an average of 20% improvement relative to the baseline vehicle across three different urban drive cycles. Feedforward information about traffic flow supplied by telematics capability is then used to develop alternative driving cycles firstly under the assumption there are no constraints on the intelligent vehicle’s path, and then taking into account in the presence of ‘un-intelligent’ vehicles on the road. It is observed that with telematic capability, the fuel economy improvements equal that achievable with a hybrid configuration with as little as 7 s traffic look-ahead capability, and can be as great as 33% improvement relative to the un-intelligent baseline drivetrain. As a final investigation, the two technologies are combined and the potential for using feedforward information from a sensor network with a hybrid drivetrain is discussed.     

Integrated modeling of urban hierarchy and transportation network planning

A major problem addressed during the preparation of spatial development plans relates to the accessibility to facilities where services of general interest such as education, health care, public safety, and justice are offered to the population. In this context, planners typically aim at redefining the level of hierarchy to assign to the urban centers of the region under study (with a class of facilities associated with each level of hierarchy) and redesigning the region’s transportation network. Traditionally, these two subjects – urban hierarchy and transportation network planning – have been addressed separately in the scientific literature. This paper presents an optimization model that simultaneously determines which urban centers and which network links should be promoted to a new level of hierarchy so as to maximize accessibility to all classes of facilities. The possible usefulness of the model for solving real-world problems of integrated urban hierarchy and transportation network planning is illustrated through an application to the Centro Region of Portugal.     

Experimental validation of connected automated vehicle design among human-driven vehicles

In this paper, we present results regarding the experimental validation of connected automated vehicle design. In order for a connected automated vehicle to integrate well with human-dominated traffic, we propose a class of connected cruise control algorithms with feedback structure originated from human driving behavior. We test the connected cruise controllers using real vehicles under several driving scenarios while utilizing beyond-line-of-sight motion information obtained from neighboring human-driven vehicles via vehicle-to-everything (V2X) communication. We experimentally show that the design is robust against variations in human behavior as well as changes in the topology of the communication network. We demonstrate that both safety and energy efficiency can be significantly improved for the connected automated vehicle as well as for the neighboring human-driven vehicles and that the connected automated vehicle may bring additional societal benefits by mitigating traffic waves.     

A microscopic simulation model for merging control on a dedicated-lane automated highway system

The automated highway systems (AHS) are not designed as stand-alone transportation facilities. Drivers will by necessity drive from their origins to the AHS entrance, and from the AHS exit to their final destinations. Therefore, the AHS will affect other transportation facilities, and should be integrated with all other facilities in the transportation system. Interfaces create much of the congestion for today’s transportation systems. Likewise, AHS interfaces may cause a similar problem, due to either AHS interactions with conventional systems or internal limitations from AHS merging capabilities. If these problems exist, either the AHS or the conventional road network cannot function properly. Consequently, the system as a whole may break down and the AHS could potentially become a detriment to the overall transportation system.Clearly, not enough is known about the automated merging process to determine what conditions would lead to congestion at interface points. The current macroscopic analysis techniques assume parameters that are not applicable to an AHS, and no detailed AHS merging models have been developed and validated. This paper addresses the interface problem between an AHS, and conventional roadway. Specifically, it presents a microscopic simulation model for one scenario of the automated merging maneuver. The results of the model show that for low flows and conventional highway speeds, an one-lane AHS merging section with a dedicated automated entrance ramp has many similar characteristics as a two-lane conventional freeway with or without fixed-time ramp metering. However, when the conventional freeway starts to “break down” near its capacity, the AHS continues to perform with little delay. The model also validates that the minimum ramp length requirements are a function of the merging vehicle’s speed, the mainline vehicles’ speed, and the acceleration and deceleration rates of the merging vehicle.     

Evaluating unintended outcomes of regional smart-growth strategies: Environmental justice and public health concerns

Many urban areas are perusing infill, transit oriented, and other “smart-growth” strategies to address a range of important regional goals. Denser and more mixed use urban development may increase sustainability and improve public health by reducing vehicle travel and increasing the share of trips made by transit, walking and bicycling. Fewer vehicle trips results in fewer greenhouse gas and toxic vehicle emissions, and more trips made by walking and bicycle increases physical activity. Prior research has largely focused on modeling and estimating the potential size of these and other smart-growth strategy benefits. A largely overlooked area is the potential for unexpected public health costs and environmental justice concerns that may result from increasing density. We evaluate regional land-use and transportation planning scenarios developed for the year 2040 by a metropolitan planning organization with a newly developed regional air quality modeling framework. Our results find that a set of regional plans designed by the MPO to promote smart-growth that are estimated to result in less vehicle use and fewer vehicle emissions than a more typical set of plans results in higher population exposure to toxic vehicle emissions. The smart-growth plans also result in greater income-exposure inequality, raising environmental justice concerns. We conclude that a more spatially detailed regional scale air quality analysis can inform the creation of smarter smart-growth plans.     

Maintenance optimization for transportation systems with demand responsiveness

We present a quadratic programming framework to address the problem of finding optimal maintenance policies for multifacility transportation systems. The proposed model provides a computationally-appealing framework to support decision making, while accounting for functional interdependencies that link the facilities that comprise these systems. In particular, the formulation explicitly captures the bidirectional relationship between demand and deterioration. That is, the state of a facility, i.e., its condition or capacity, impacts the demand/traffic; while simultaneously, demand determines a facility’s deterioration rate. The elements that comprise transportation systems are linked because the state of a facility can impact demand at other facilities. We provide a series of numerical examples to illustrate the advantages of the proposed framework. Specifically, we analyze simple network topologies and traffic patterns where it is optimal to coordinate (synchronize or alternate) interventions for clusters of facilities in transportation systems.