Identification of vehicle sensor locations for link-based network traffic applications

Information on link flows in a vehicular traffic network is critical for developing long-term planning and/or short-term operational management strategies. In the literature, most studies to develop such strategies typically assume the availability of measured link traffic information on all network links, either through manual survey or advanced traffic sensor technologies. In practical applications, the assumption of installed sensors on all links is generally unrealistic due to budgetary constraints. It motivates the need to estimate flows on all links of a traffic network based on the measurement of link flows on a subset of links with suitably equipped sensors. This study, addressed from a budgetary planning perspective, seeks to identify the smallest subset of links in a network on which to locate sensors that enables the accurate estimation of traffic flows on all links of the network under steady-state conditions. Here, steady-state implies that the path flows are static. A “basis link” method is proposed to determine the locations of vehicle sensors, by using the link-path incidence matrix to express the network structure and then identifying its “basis” in a matrix algebra context. The theoretical background and mathematical properties of the proposed method are elaborated. The approach is useful for deploying long-term planning and link-based applications in traffic networks.     

A statistical approach to the traveling salesman problem

A statistical approach is shown to be adaptable to the N-city traveling salesman problem by considering route distances to be random variables which are continuous and normally distributed. A solution to the shortest route distance and path can be approximated by utilizing a Monte Carlo simulation to obtain a representative sample of possible journeys. The approach involves recursive statistical inference which is used to select next-city visits leading to the most probable minimum route path. A statistical selection of the minimum route path is computationally efficient and computer run time increases in proportion to the square of the number of cities as opposed to an (N - 1)! increase for a deterministic approach. The accuracy of the statistical approach is directly proportional to the number of Monte Carlo simulations.     

FMOLP approach to the inland water transportation problem

Fuzzy optimization techniques can be applied in determining the optimal schedule for the transport of gravel by inland water transportation. Gravel demand, for example, is difficult to determine precisely since it depends on the industrial development of the regions supplied by gravel and on possible buyers. The duration of the annual navigation period varies depending on the water level, possible icebergs, heavy fog, strong and frequent wind. The transport company is usually satisfied if total transportation costs stay within a reasonable range. The formulation of a linear programme lacks flexibility in dealing with imprecise input data. In this paper this type of problem has been approached with fuzzy optimization techniques.     

Optimal solution to the vehicle routing problem by adopting a meta-heuristic algorithm

The delivery service provided by large-scale retailers continues to grow as online sales occupy an increasingly large share of the market. This study aims to tease out efficient vehicle scheduling times as well as optimal delivery routes by applying meta-heuristic algorithms. Monthly data on existing routes were obtained from a branch of Korea’s leading large-scale online retailer. The first task was to examine the status of existing routes by comparing delivery routes created using Dijkstra’s algorithm with existing delivery routes and their vehicle scheduling. The second task was to identify optimal delivery routes through a comparative analysis of the genetic algorithm and Tabu search algorithm, known for its superior applicability amongst other meta-heuristic algorithms. These findings demonstrate that the optimal vehicle routing problem not only has the potential to reduce distribution costs for operators and expedite delivery for consumers, but also the added social benefit of reduced carbon emissions.     

On the dual approach to the traffic assignment problem

This paper attempts to explore the possibility of solving the traffic assignment problem with elastic demands by way of its dual problem. It is shown that the dual problem can be formulated as a nonsmooth convex optimization problem of which the objective function values and subgradients are conveniently calculated by solving shortest path problems associated with the transportation network. A subgradient algorithm to solve the dual problem is presented and limited computational experience is reported. The computational results are encouraging enough to demonstrate the effectiveness of the proposed approach.     

A complex network approach to understand commercial vehicle movement

We introduce complex network analysis and use a commercial vehicle’s observed trip as a proxy for a business relation between two facilities in its activity chain. We extract facility locations by applying density-based clustering to GPS data of commercial vehicle activities. The network among the facilities is then extracted by analysing the activity chains of more than 25,000 commercial vehicles. Centrality metrics prove useful and novel in identifying and locating key logistics players. Transport planners and decision makers can benefit from such an approach as it allows them to design more targeted initiatives and policy interventions.     

A corridor-centric approach to planning electric vehicle charging infrastructure

The transition to electric vehicles (EV) faces two major barriers. On one hand, EV batteries are still expensive and limited by range, owing to the lack of technology breakthrough. On the other hand, the underdeveloped supporting infrastructure, particularly the lack of fast refueling facilities, makes EVs unsuitable for medium and long distance travel. The primary purpose of this study is to better understand these hurdles and to develop strategies to overcome them. To this end, a conceptual optimization model is proposed to analyze travel by EVs along a long corridor. The objective of the model is to select the battery size and charging capacity (in terms of both the charging power at each station and the number of stations needed along the corridor) to meet a given level of service in such a way that the total social cost is minimized. Two extensions of the base model are also considered. The first relaxes the assumption that the charging power at the stations is a continuous variable. The second variant considers battery swapping as an alternative to charging. Our analysis suggests that (1) the current paradigm of charging facility development that focuses on level 2 charging delivers poor level of service for long distance travel; (2) the level 3 charging method is necessary not only to achieve a reasonable level of service, but also to minimize the social cost; (3) investing on battery technology to reduce battery cost is likely to have larger impacts on reducing the charging cost; and (4) battery swapping promises high level of service, but it may not be socially optimal for a modest level of service, especially when the costs of constructing swapping and charging stations are close.     

Approximate algorithms for the discrete network design problem

The discrete network design problem is one of finding a set of feasible actions (projects) from among a collection of possible actions, that when implemented, optimizes some objective function(s). This is a combinatorial optimization problem that is very expensive to solve exactly. This paper proposes two algorithms for obtaining approximate solutions to the discrete network design problem with much less computational effeort. The computational savings are achieved by approximating the original problem with a new formulation which is easier to solve. The first algorithm proposed solves this approximate problem exactly, while the second is even more efficient, but provides only a near-optimal solution to the approximate problem. Experience with test problems indicates that these approximations can reduce the computational effort by a factor of 3–5, with little loss in solution accuracy.     

运用QC方法解决管片生产质量问题

武汉长江隧道钢筋混凝土管片在开始生产之前,成立了QC质量攻关小组。小组运用QC方法,严格按照PDCA循环步骤,针对在管片生产过程中出现的质量问题,进行了大量的试验、研究及摸索,并采取有效措施对混凝土配合比及生产工艺等方面进行了改进,最终成功解决了质量问题。     

Origin-destination matrices estimation model using automatic vehicle identification data and its application to the Han-Shin expressway network

The Automatic Vehicle Identification (AVI) system was recently installed in expressway networks in Japan. License plate numbers of passing vehicles are monitored through roadside AVI cameras and then recognized. This paper shows the formulation of origin and destination (OD) matrices estimation model using the observed data with the AVI system. The results of license plate matching between a pair of AVI cameras are involved as the input variables. The formulated model is a least squares model and yields to the linear transformation of the partly observed OD matrices. The model is applied to the Kobe corridor line in the Han-Shin expressway network. It is found that the estimated OD matrix is consistent with the one using the previous mail survey. The proposed estimation method is expected to investigate the day-to-day fluctuations of OD patterns in the expressway network.     

A fuzzy measure based solution approach to a multimodal analysis problem

This paper discusses the factors that determine the utility of a mode and attempts to suggest and investigate a novel fuzzy measure based solution approach to the problem of multimodal analysis in a multicriteria context. The paper expands on the notions of fuzzy logic and in particular, fuzzy measures. The approach attempts to estimate the probabilities of the “overall system” from a group of eight experts who are experienced in transport planning. The data is used to ascertain the relative utility of various modes in a competitive environment. It explains the application of fuzzy measures to provide guidance information for a transport planning agency.     

Evaluating the impacts of shared automated mobility on-demand services: an activity-based accessibility approach

Transportation - Autonomous vehicle (AV) technologies are under constant improvement with pilot programs now underway in several urban areas worldwide. Modeling and field-testing efforts are...     

Approximation algorithms for the bid construction problem in combinatorial auctions for the procurement of freight transportation contracts

Trucking companies (carriers) are increasingly facing combinatorial auctions conducted by shippers seeking contracts for their transportation needs. The bid valuation and construction problem for carriers facing these combinatorial auctions is very difficult and involves the computation of a number of NP-hard sub problems. In this paper we examine computationally tractable approximation methods for estimating these values and constructing bids. The benefit of our approximation method is that it provides a way for carriers to discover their true costs and construct optimal or near optimal bids by solving a single NP-hard problem. This represents a significant improvement in computational efficiency. We examine our method both analytically and empirically using a simulation based analysis.     

如何提高设备检修工作效率

工作效率的提高是企业提高竞争能力，提高经济效益的重要手段，文章从计划制定．工具准备．人员安排．提高作业熟练度．增加目的性维修．备品备件管理．技术资料管理及总结分析八个方面阐述了如何提高索道设备检修的工作效率。     

An approximate dynamic programming approach for the empty container allocation problem

The objective of this study is to demonstrate the successful application of an approximate dynamic programming approach in deriving effective operational strategies for the relocation of empty containers in the containerized sea-cargo industry. A dynamic stochastic model for a simple two-ports two-voyages (TPTV) system is proposed first to demonstrate the effectiveness of the approximate optimal solution obtained through a simulation based approach known as the temporal difference (TD) learning for average cost minimization. An exact optimal solution can be obtained for this simple TPTV model. Approximate optimal results from the TPTV model utilizing a linear approximation architecture under the TD framework can then be compared to this exact solution. The results were found comparable and showed promising improvements over an existing commonly used heuristics. The modeling and solution approach can be extended to a realistic multiple-ports multiple-voyages (MPMV) system. Some results for the MPMV case are shown.     

Using connected vehicle technology to improve the efficiency of intersections

Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control.Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.     

Analysis of an O(N2) heuristic for the single vehicle many-to-many Euclidean dial-a-ride problem

We develop an O(N²) heuristic to solve the single vehicle many-to-many Euclidean Dial-A-Ride problem. The heuristic is based on the Minimum Spanning Tree of the modes of the problem. The algorithm's worst case performance is four times the length of the optimal Dial-A-Ride tour. An analysis of the algorithm's average performance reveals that in terms of sizes of single-vehicle problems that are likely to be encountered in the real world (up to 100 nodes) and in terms of computational complexity, the O(N²) heuristic performs equally well, or, in many cases, better than heuristics described earlier by Stein for the same problem. The performance of the heuristic exhibits statistical stability over a broad range of problem sizes.     

Diesel-engined vehicle nitric oxide and soot emissions during the European light-duty driving cycle using a transient mapping approach

An engine mapping-based methodology is developed to gain a first approximation of a vehicle’s performance and emissions during a light-duty cycle. The procedure is based on a steady-state experimental investigation of the engine with an appropriate vehicle drivetrain model applied so that the cycle vehicle speed data can be transformed into engine speed and torque. Correction analysis is then applied based on transient experimentation to account for the transient discrepancies during real driving. The developed algorithm is applied for the case of a diesel-engined vehicle running on the European light-duty cycle. A comparative analysis is performed for each section of the cycle revealing its individual transient characteristics.     

An examination of factors affecting propensities to use bicycle and pedestrian facilities in suburban locations

The US federal Congestion Mitigation and Air Quality program was created to fund transportation projects that have the potential to contribute to the attainment or maintenance of the National Ambient Air Quality Standards. This study evaluates a random sample of eight suburban bicycle and pedestrian facilities funded by the Congestion Mitigation and Air Quality Program in the Chicago metro area. Users of these facilities were randomly sampled using a “time-based” user sampling approach and surveyed in intercept mode to implement a recall-based evaluation design. A random intercept logit model was used to explain variations in the propensity to switch from single occupant vehicle use to bicycling or walking, using attributes of users and sites. The analysis shows relatively low usage levels but that substitution of motorized modes have resulted, potentially leading to improved air quality outcomes.     

把脉商用车之"商情"

中国汽车工业建基于商用车,多年来,商用车一直是中国汽车市场的驱动主力.近年来,商用车每年保持了大于50%的市场贡献度.2003年,全国载货车和客车合计销售241.92万辆,轿车销售197.16万辆;2004年载货车和客车合计销售274.46万辆,轿车销售232.65万辆.然而,商用车与乘用车的市场结构终于由量变引发了质变.2005年1月～9月,全国汽车销售413.62万辆,其中商用车133.30万辆,乘用车280.32万辆,商用车对汽车市场的销售贡献度降为32.23%,商用车引领中国汽车市场的格局被打破了.