A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-vMFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in bi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus–Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in bi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority.     

Generalized Maximum Benefit Multiple Chinese Postman Problem

This research is focused on a generalization on the Max Benefit Chinese Postman Problem and the multiple vehicle variant of the Chinese Postman Problem. We call this generalization, the Generalized Maximum Benefit k-Chinese Postman Problem (GB k-CPP). We present a novel Mixed Integer Programming (MIP) formulation for the GB k-CPP. Four different cases of the model are discussed. The first case, performs arc-routing with profits and assumes that the origin and destination for each vehicle is the same for each cycle and is given by the user. The next case relaxes the assumption that the origin and destination for each vehicle should be the same and allows the users to select possible origins/destinations for vehicles. Case three gets the origin for each vehicle as input and produces a solution based on finding the best destination for each vehicle. The last case, that is very general, allows the optimization model to select possibly different locations for vehicle origin and destination, during each cycle. The different cases are applied to a security patrolling case conducted on the network of University of Maryland at College Park campus and the results are compared.     

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network – Performance evaluation

Connected Vehicle Technology (CVT) requires wireless data transmission between vehicles (V2V), and vehicle-to-infrastructure (V2I). Evaluating the performance of different network options for V2V and V2I communication that ensure optimal utilization of resources is a prerequisite when designing and developing robust wireless networks for CVT applications. Though dedicated short range communication (DSRC) has been considered as the primary communication option for CVT safety applications, the use of other wireless technologies (e.g., Wi-Fi, LTE, WiMAX) allow longer range communications and throughput requirements that could not be supported by DSRC alone. Further, the use of other wireless technology potentially reduces the need for costly DSRC infrastructure. In this research, the authors evaluated the performance of Het-Net consisting of Wi-Fi, DSRC and LTE technologies for V2V and V2I communications. An application layer handoff method was developed to enable Het-Net communication for two CVT applications: traffic data collection, and forward collision warning. The handoff method ensures the optimal utilization of available communication options (i.e., eliminate the need of using multiple communication options at the same time) and corresponding backhaul communication infrastructure depending on the connected vehicle application requirements. Field studies conducted in this research demonstrated that the use of Het-Net broadened the range and coverage of V2V and V2I communications. The use of the application layer handoff technique to maintain seamless connectivity for CVT applications was also successfully demonstrated and can be adopted in future Het-Net supported connected vehicle applications. A long handoff time was observed when the application switches from LTE to Wi-Fi. The delay is largely due to the time required to activate the 802.11 link and the time required for the vehicle to associate with the RSU (i.e., access point). Modifying the application to implement a soft handoff where a new network is seamlessly connected before breaking from the existing network can greatly reduce (or eliminate) the interruption of network service observed by the application. However, the use of a Het-Net did not compromise the performance of the traffic data collection application as this application does not require very low latency, unlike connected vehicle safety applications. Field tests revealed that the handoff between networks in Het-Net required several seconds (i.e., higher than 200 ms required for safety applications). Thus, Het-Net could not be used to support safety applications that require communication latency less than 200 ms. However, Het-Net could provide additional/supplementary connectivity for safety applications to warn vehicles upstream to take proactive actions to avoid problem locations. To validate and establish the findings from field tests that included a limited number of connected vehicles, ns-3 simulation experiments with a larger number of connected vehicles were conducted involving a DSRC and LTE Het-Net scenario. The latency and packet delivery error trend obtained from ns-3 simulation were found to be similar to the field experiment results.     

Sustainability provisions in the bus-scheduling problem

The traditional vehicle scheduling problem attempts to minimize capital and operating costs. However, the carbon footprint and toxic air pollutants have become an increasingly important consideration. This paper studies the bus-scheduling problem and evaluates new types of buses that use alternative energy sources to reduce emissions, including some toxic air pollutants and carbon dioxide. A time-space network based approach is applied to formulate the problem to reduce the numbers of arcs in the underlying network; CPLEX is used to solve the problem. The results show that the bus-scheduling model can significantly reduce the bus emissions – hence reducing the carbon footprint of the transit operation – while only slightly increasing operating costs.     

The design of bus route systems — An interactive location-allocation approach

An interactive modelling approach is developed to solve the practical problem of bus route network design. Possible bus routes are identified with facilities which can be located. Zones or pairs of zones in the urban area are identified with customers who will be allocated to the established facilities. It is shown that the classical Set Covering Problem is useful under the assumption of fixed demand; the Simple Plant Location Problem is effective under the assumption of demand which is sensitive to the level of bus service provided.     

Creating bus timetables with maximal synchronization

This paper addresses the problem of generating a timetable for a given network of buses so as to maximize their synchronization. It attempts to maximize the number of simultaneous bus arrivals at the connection (transfer) nodes of the network. Transit schedulers, taking into account the satisfaction and convenience of the system's users, appreciate the importance of creating a timetable with maximal synchronization, which enables the transfer of passengers from one route to another with minimum waiting time at the transfer nodes. In this paper, the problem is formulated as a mixed integer linear programming problem, and a heuristic algorithm is developed to solve the problem in polynomial time. The efficiency of this algorithm, compared to optimal solutions, is illustrated through a series of examples.     

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

This paper proposes a novel approach to identify the pockets of activity or the community structure in a city network using multi-layer graphs that represent the movement of disparate entities (i.e. private cars, buses and passengers) in the network. First, we process the trip data corresponding to each entity through a Voronoi segmentation procedure which provides a natural null model to compare multiple layers in a real world network. Second, given nodes that represent Voronoi cells and link weights that define the strength of connection between them, we apply a community detection algorithm and partition the network into smaller areas independently at each layer. The partitioning algorithm returns geographically well connected regions in all layers and reveal significant characteristics underlying the spatial structure of our city. Third, we test an algorithm that reveals the unified community structure of multi-layer networks, which are combinations of single-layer networks coupled through links between each node in one network layer to itself in other layers. This approach allows us to directly compare the resulting communities in multiple layers where connection types are categorically different.     

Spatiotemporal intersection control in a connected and automated vehicle environment

Current research on traffic control has focused on the optimization of either traffic signals or vehicle trajectories. With the rapid development of connected and automated vehicle (CAV) technologies, vehicles equipped with dedicated short-range communications (DSRC) can communicate not only with other CAVs but also with infrastructure. Joint control of vehicle trajectories and traffic signals becomes feasible and may achieve greater benefits regarding system efficiency and environmental sustainability. Traffic control framework is expected to be extended from one dimension (either spatial or temporal) to two dimensions (spatiotemporal). This paper investigates a joint control framework for isolated intersections. The control framework is modeled as a two-stage optimization problem with signal optimization at the first stage and vehicle trajectory control at the second stage. The signal optimization is modeled as a dynamic programming (DP) problem with the objective to minimize vehicle delay. Optimal control theory is applied to the vehicle trajectory control problem with the objective to minimize fuel consumption and emissions. A simplified objective function is adopted to get analytical solutions to the optimal control problem so that the two-stage model is solved efficiently. Simulation results show that the proposed joint control framework is able to reduce both vehicle delay and emissions under a variety of demand levels compared to fixed-time and adaptive signal control when vehicle trajectories are not optimized. The reduced vehicle delay and CO₂ emissions can be as much as 24.0% and 13.8%, respectively for a simple two-phase intersection. Sensitivity analysis suggests that maximum acceleration and deceleration rates have a significant impact on the performance regarding both vehicle delay and emission reduction. Further extension to a full eight-phase intersection shows a similar pattern of delay and emission reduction by the joint control framework.     

A warehouse location-routing problem

The interdependence between distribution center location and vehicle routing has been recognized by both academics and practitioners. However, only few attempts have been made to incorporate routing in location analysis. This paper defines the Warehouse Location-Routing Problem (WLRP) as one of simultaneously solving the DC location and vehicle routing problems. We present a mixed integer programming formulation of the WLRP. Based on this formulation, it can be seen that the WLRP is a generalization of well-known and difficult location and routing problems, such as the Location-Allocation Problem and the Multi-depot Vehicle Dispatch Problem. It is therefore a large and complex problem which cannot be solved using existing mixed-integer programming techniques. We present a heuristic solution method for the WLRP, based on decomposing the problem into three subproblems. The proposed method solves the subproblems in a sequential manner while accounting for the dependence between them. We discuss a large-scale application of the proposed method to a national distribution company at a regional level.     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.     

Transit user perceptions of driverless buses

This paper reports the results of a stated preference survey of regular transit users’ willingness to ride and concerns about driverless buses in the Philadelphia region. As automated technologies advance, driverless buses may offer significant efficiency, safety, and operational improvements over traditional bus services. However, unfamiliarity with automated vehicle technology may challenge its acceptance among the general public and slow the adoption of new technologies. Using a mixed logit modeling framework, this research examines which types of transit users are most willing to ride in driverless buses and whether having a transit employee on board to monitor the vehicle operations and/or provide customer service matters. Of the 891 surveyed members of University of Pennsylvania’s transit pass benefit program, two-thirds express a willingness to ride in a driverless bus when a transit employee is on board to monitor vehicle operations and provide customer service. By contrast, only 13% would agree to ride a bus without an employee on board. Males and those in younger age groups (18–34) are more willing to ride in driverless buses than females and those in older age groups. Findings suggest that, so long as a transit employee is onboard, many transit passengers will willingly board early generation automated buses. An abrupt shift to buses without employees on board, by contrast, will likely alienate many transit users.

     

Time-dependent Hyperstar algorithm for robust vehicle navigation

The vehicle navigation problem studied in Bell (2009) is revisited and a time-dependent reverse Hyperstar algorithm is presented. This minimises the expected time of arrival at the destination, and all intermediate nodes, where expectation is based on a pessimistic (or risk-averse) view of unknown link delays. This may also be regarded as a hyperpath version of the Chabini and Lan (2002) algorithm, which itself is a time-dependent A^* algorithm. Links are assigned undelayed travel times and maximum delays, both of which are potentially functions of the time of arrival at the respective link. Probabilities for link use are sought that minimise the driver’s maximum exposure to delay on the approach to each node, leading to the determination of a pessimistic expected time of arrival at the destination and all intermediate nodes. Since the context considered is vehicle navigation, the probability of link use measures link attractiveness, so a link with a zero probability of use is unattractive while a link with a probability of use equal to one will have no attractive alternatives. A solution algorithm is presented and proven to solve the problem provided the node potentials are feasible and a FIFO condition applies to undelayed link travel times. The paper concludes with a numerical example.     

Mitigation of disruptions in public transit by Bee Colony Optimization

Dispatchers in many public transit companies face the daily problem of assigning available buses to bus routes under conditions of bus shortages. In addition to this, weather conditions, crew absenteeism, traffic accidents, traffic congestion and other factors lead to disturbances of the planned schedule. We propose the Bee Colony Optimization (BCO) algorithm for mitigation of bus schedule disturbances. The developed model takes care of interests of the transit operator and passengers. The model reassigns available buses to bus routes and, if it is allowed, the model simultaneously changes the transportation network topology (it shortens some of the planned bus routes) and reassigns available buses to a new set of bus routes. The model is tested on the network of Rivera (Uruguay). Results obtained show that the proposed algorithm can significantly mitigate disruptions.     

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.     

Time-dependent green vehicle routing problem with stochastic vehicle speeds: An approximate dynamic programming algorithm

This paper addresses a Time Dependent Capacitated Vehicle Routing Problem with stochastic vehicle speeds and environmental concerns. The problem has been formulated as a Markovian Decision Process. As distinct from the traditional attempts on the problem, while estimating the amount of fuel consumption and emissions, the model takes time-dependency and stochasticity of the vehicle speeds into account. The Time Dependent Capacitated Vehicle Routing Problem is known to be NP-Hard for even deterministic settings. Incorporating uncertainty to the problem increases complexity, which renders classical optimization methods infeasible. Therefore, we propose an Approximate Dynamic Programming based heuristic as a decision aid tool for the problem. The proposed Markovian Decision Model and Approximate Dynamic Programming based heuristic are flexible in terms that more environmentally friendly solutions can be obtained by changing the objective function from cost minimization to emissions minimization. The added values of the proposed decision support tools have been shown through computational analyses on several instances. The computational analyses show that incorporating vehicle speed stochasticity into decision support models has potential to improve the performance of resulting routes in terms of travel duration, emissions and travel cost. In addition, the proposed heuristic provides promising results within relatively short computation times.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

Developing link-based particle number emission models for diesel transit buses using engine and vehicle parameters

To better assess health impacts from diesel transportation sources, particle number emissions can be modeled on a road network using traffic operating parameters. In this work, real-time particle number emissions rates from two diesel transit buses were aggregated to the roadway link-level and modeled using engine parameters and then vehicle parameters. Modern statistical methods were used to identify appropriate predictor variables in the presence of multicollinearity, and controlled for correlated emission measurements made on the same day and testing route. Factor analysis helped to reduce the number of potential engine parameters to engine load, engine speed, and exhaust temperature. These parameters were incorporated in a linear mixed model that was shown to explain the variation attributable to link-characteristics. Vehicle specific power and speed were identified as two surrogate vehicle travel variables that can be used in the absence of engine parameters, although with a loss in predictive power compared to the engine parameter model. If vehicle speed is the only operating input available, including road grades in the model can significantly improve particle number emission estimates even for links with mild grade. Although the data used are specific to the buses tested, the approach can be applied to modeling emissions from other vehicle models with different engine types, exhaust systems, and engine retrofit technologies.     

Fare deregulation of transit services: Winners and losers in a competitive market

Currently, the Hong Kong government imposes fare control on buses and taxi while the rail services are immune to such a control. This study examined four scenarios of fare deregulation on transit services by considering three related parties of a transit system – service providers, travelers, and society in general, with their respective objectives represented as – revenue, travel utility, and congestion. Analyzing the resultant impacts on these three parties, we found that a different regulatory environment would favor or hurt a different set of parties. There is no clear win‐win situation for all parties. Deciding a socially acceptable regulatory environment is likely to involve difficult tradeoffs among these parties.     

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Merging bus routes in Hong Kong’s central business district: Analysis and models

A significant portion of the 200,000 people working in Hong Kong’s central business district (CBD) relies on buses as their primary means of transport. During peak hours, nearly a thousand double-decker buses pour into a tiny area of 150 ha. This causes traffic congestion and air pollution. Moreover, given that the flow is uni-directional (into the CBD in the morning and out of the CBD in the afternoon), the occupancy of buses in the CBD is actually low.In this paper, we propose to reduce traffic congestion and to increase bus occupancy by merging bus routes. We describe the peculiar situation of the CBD in Hong Kong and explain the necessary conditions for the possible success of merging routes. Our analysis shows that merging will lead to an overall benefit for all parties, including government, bus operators, and passengers. The actual merging decisions, which routes to merge and at what frequencies buses should run, are determined by a mathematical model. The model also shows quantitatively the benefits of merging routes and the impacts of other factors. The procedure that we follow and the model that we adopt can be applied to other CBD.