Different from the conventional operation mode in existing taxi dispatch systems, in this paper, we envision a new cyber-technology enabled taxi dispatch system which can efficiently provide vacant taxis with cruising route suggestions, not to respond to any specific pick-up request but instead, hoping to find prospective customers (such system is also complementary to the conventional operation mode). We address the Taxi Cruising Guidance (TCG) problem with the objective being to minimize the Global Vacant Rate (GVR), which is defined as the ratio of traveling miles with no passenger onboard, to the total traveling miles in a given time period. We propose a number of heuristic solutions and conduct comprehensive performance evaluations based on large-scale simulations. A case study is also presented by utilizing real traces collected from taxis in the city of Shanghai. As part of our research, we leverage a well-known microscopic traffic simulator (called TRANSIMS) to demonstrate that the application of TCG is also beneficial to traffic management.

We consider a promising application in Vehicular Cyber-Physical Systems (VCPS) called On-road Ad Delivery (OAD), where targeted advertisements are delivered via roadside APs to attract commuters to nearby shops. Different from most existing works on VANETs which only focused on a single technical area, this work on OAD involves technical elements from human factors, cyber systems and transportation systems since a commuter's shopping decision depends on e.g. the attractiveness of the ads, the induced detour, and traffic conditions on different routes. In this paper, we address a new optimization problem in OAD whose goal is to schedule ad messages and allocate a limited amount of AP bandwidth so as to maximize the system-wide performance in terms of total realized utilities (TRU) of the delivered ads. A number of efficient heuristics are proposed to deal with ad message scheduling and AP bandwidth allocation. Besides largescale simulations, we also present a case study in a more realistic scenario utilizing real traces collected from taxis in the city of Shanghai. In addition, we use a commercial traffic simulator (PARAMICS) to show that our proposed solutions are also useful for traffic management in terms of balancing vehicular traffic and alleviating congestion.

Vehicular Cyber-Physical Systems (VCPS) provide human drivers with various services related to road safety, and on-road infotainments. Since a service (message) delivery includes service transmission, service display and driver processing, many challenges arise due to limited network resources, possible pre-emption and contention between services for the display and non-negligible driver processing delay. In this paper, we address a new Driver-centric Service Delivery Problem (DSDP) from a cross-disciplinary resource allocation standpoint. Our goal is to deliver a number of services to a set of intended drivers in a given time period so as to maximize the system-wide performance in terms of total utility income (TUI) to drivers. We show that DSDP differs from all existing problems and is NP-Complete. A number of efficient heuristics are proposed to address several issues, including wireless transmission failure as well as distributed implementation of the multi-sender systems. Utilizing real traces collected from taxis in the city of Shanghai, we also present a case study in a more realistic scenario and conduct comprehensive simulations providing numerical results.

It is essential to consider drivers' perceptions and reactions when building Vehicular Cyber-Physical Systems (VCPS) since the effectiveness and efficiency of VCPS will largely depend on how drivers could benefit from such a system. This paper considers, for the first time, novel service scheduling problems from a Human Factors (HF) standpoint by taking into consideration the following fact: a driver may not be able to receive more than one service in a short period of time, even if multiple services can be transmitted to the driver from the conventional communications and networking standpoint. We study a family of the HF-aware Service Scheduling (HFSS) Problems, where the goal is to deliver up to n services, each having a time-dependent (and possibly decreasing) utility to a subset of intended drivers so as to minimize the system-wide total utility loss due to unsuccessful delivery of some services. We show that such problems are different from all existing problems. We formulate the basic HFSS problem (BHFSSP) using Integer Linear Programming (ILP) and prove its NP-Completeness. We then propose efficient heuristics for BHFSSP and its more general versions, and present numerical results from large-scale test cases. We also address several practical issues related to wireless transmission failures, distributed implementation in the multisender scenario, and other HF related considerations.

It is essential to consider drivers' perceptions and reactions when building Vehicular Cyber-Physical Systems (VCPS) since the effectiveness and efficiency of VCPS will largely depend on how drivers could benefit from such a system. This paper considers, for the first time, novel service scheduling problems from Human Factors (HF) standpoint by taking into consideration the following fact: a driver may not be able to receive more than one service in a short period of time, even if the VCPS can somehow transmit multiple services to the driver from the conventional communications and networking standpoint. We study a family of the HF-aware Service Scheduling (HFSS) Problems, where the goal is to deliver up to n services, each having a time-dependent (and non-increasing) utility to a subset of intended drivers so as to minimize the system-wide total utility loss due to unsuccessful delivery of some services. We show that such problems are different from all existing problems. We formulate the basic HFSS problem (BHFSSP) using Integer Linear Programming (ILP) and prove it and other more general problems to be NP-Complete. We also propose efficient heuristics and present numerical results from large-scale test cases.

Sink mobility has attracted much research interests in Wireless Sensor Networks (WSNs), because it could provide energy saving and reduce latency during data collection. However, the mobile sink node is still a single point of failure in many WSNs applications, thus needs to be particularly protected against adversaries. We propose in this paper a moving strategy for the mobile sink which prevents tracking or detecting on it by adversaries during its data collection phase around the sensor field. Our moving strategy aims to selecting a trajectory for mobile sink node, which minimizes the total number of message communication from all static sensor nodes to the mobile sink node (including multi-hop relaying) and thereby reducing the possibility of being detected by the adversaries. We also employed a routing protocol on sensor nodes to forward the data to mobile sink node with shortest-path. Four strategies are evaluated in our simulation and the performance results show that our moving strategy we proposed achieves best goal and adapts well to the different deployment patterns.

In this article, we focus on a typical application of Cyber Physical System (CPS), i.e., vehicle route navigation. Two fundamental problems have been examined: 1) How different are various vehicle routing algorithms? 2) How valuable is real-time traffic information or historical traffic information in helping vehicle routing? Different from most previous works based on simulations, we presented performance comparisons of four routing algorithms using real GPS sensory data from 4000 taxis. It has been shown that using real-time traffic information could substantially improve the quality of vehicle path routing. This can benefit an individual driver, because through our evaluation results on realistic vehicle traces we found that the paths selected by taxi drivers are not as good as expected. More importantly, utilizing real-time information could improve global transportation efficiency in terms of dispersing/managing traffic, which plays a key role in constructing an effective vehicular CPS.

Delay Tolerant Network (DTN) is a kind of networks that have no fixed path between nodes due to lack of continuous network connectivity. To achieve successful communication and to improve performance in DTN is always a challenge work. Most existing works are based on designing high efficient routing protocols and have not emphasized the MAC layer as well as new technologies available in the Physical layer which may influence the performance for whole networks. In this paper, we consider utilization of Multi-packet Reception (MPR) capability in DTN in order to provide better performance. We introduce our own MPR scheduling scheme, Group Based Scheme (GBS), and compare the performance of DTN with different MPR capabilities. Our works have been evaluated by the simulation using a real vehicular network trace composed of the GPS data of more than 4,000 taxis in Shanghai urban area. The results have demonstrated various impacts of using Multi-Packet Reception (MPR) on performance in DTN. By using MPR in DTN, it outperforms the network without MPR especially when the wireless transmission range increases.

We consider distributed top-k processing problem in a mobile scenario. Specially, we focus on a real application of a bus network (N nodes), where buses are equipped with cameras for real-time security surveillance. Due to the limited number of screens (k, k<;<;N) at the traffic management center, how to select k bus nodes with most passengers to upload image data by DSRC needs to be solved. We present a novel distributed scheme BSS to handle this so-called "top-k node selection" issue in bus network, in which challenges of low time cost and high accuracy is not trivial. BSS utilizes various strategies to speed up top-k node selection facing poor network condition and application requirements. Performance evaluation is carried out on a real-trace driven simulator, which utilizes about 700 buses in Shanghai. The testing results show that BSS has an excellent performance in terms of time cost and average degree of accuracy, which shows the effectiveness of BSS scheme for real-time security surveillance.

In this paper, we present our study of extracting a mobility model for vehicular ad hoc networks (VANETs) from a large amount of real taxi GPS trace data. In order to capture characteristics of the urban vehicle network from microscopic to macroscopic aspects, we design three parameters and extract their values from the GPS trace data. Using this mobility model, we can generate the synthetic trace to simulate the movement of taxis in the urban area of a metropolis. The validation is carried through extensive comparisons between the synthetic trace and the real trace. Validation results show that our mobility model has a good approximation to the real scenario.

Bus lane enforcement system aims to monitor illegal utilization of bus lane by non-permitted vehicles (violator). However, Road-side system leads to considerable infrastructure cost while bus mounted system has limited surveillance coverage. In this paper, we consider an interesting problem in bus mounted system: how to improve the surveillance coverage of bus mounted system without additional infrastructure cost? In other words, we attempt to identify not only the violator immediately in front of the bus, bus also the violators not close to the bus, whose number plates cannot be read directly because of sight blocking of bus mounted cameras. With utilization of communication between bus and existing cameras around intersections, we propose a novel cooperative violator identification scheme, DoubleChecking, with which violators can be sorted out from traffic flow with high accuracy. From theoretical analysis, DoubleChecking shows a good performance for violator identification, which demonstrates the effectiveness of the proposed scheme.

We consider a practical application of intelligent vehicles for intersection traffic control. Specially, we study the intersection traffic control problem using reservation-based intersection traffic control system, which utilizes the information exchange between intelligent vehicles and management agents around the intersections to direct traffic, instead of traffic lights. We focus on how to design an effective passing permission (PP) allocation strategy for this system. In this work, with an observation that will cause this system to be inefficient, we propose a novel look-ahead passing permission allocation strategy (LICP) for intersection traffic control. The large-scale testing results show that LICP can make nearly 25% performance improvement on average intersection delay than the previous first come, first serve method (FCFS).

Currently, vehicles are equipped with forward facing cameras to assist the forensic investigations of events by proactive image capturing from streets and roads. With content redundancy and storage imbalance in this in-network distributed storage system, how to maximize its storage capacity is a challenge. In other words, how to maximize the average lifetime of sensory data (i.e. images generated by cameras) in network is a fundamental problem need to be solved. This paper presents, VStore, a cooperative storage solution for mobile surveillance in vehicular sensor networks (VSN). The mechanisms in VStore are designed for redundancy elimination by exchanging information between vehicles and storage balancing. Compared with previous work, we deal with new challenges in mobile scenario. Field testing was carried out on a real-trace driven simulator, which utilizes about 500 taxies in Shanghai city. The testing results show that VStore can largely prolong the average lifetime of sensory data by cooperative storage.

Currently, vehicular sensor network (VSN) has been paid much attention for monitoring the physical world of urban areas. We have studied VSNs by utilizing about 4000 taxies and 1000 buses equipped with GPS-based mobile sensors in Shanghai to constitute a virtual vehicular sensor network. The communication-connection intermittence makes the routing issue nontrivial when delay-tolerant applications are deployed in VSNs. The existing DTN routing protocols can be categorized as "neighbor-oriented" and how to select a neighbor candidate was always neglected. In this paper, we present a new DTN routing protocol for Delay-Tolerant Vehicular Sensor Networks, Packet-Oriented Routing protocol (POR), which is designed to emphasize neighbor selection based on awareness of packets to be sent and in consideration of probability to complete transferring of these packets. Our results show that POR performs much better than the ordinary Epidemic routing, as well as other popular routing protocols applied in a similar setting.

The existing vehicular sensors of taxi companies in most of cities can be used for traffic monitoring, however sensors are always set with a long sampling interval because of communication cost saving and network congestion avoidance. In this paper, we focus on the traffic data processing in vehicular sensor networks providing sparse and incomplete information. A performance evaluation study has been carried out in Shanghai by utilizing the sensors installed on 4000 taxis. Two types of traffic status estimation algorithms, the link-based and the vehicle-based, are introduced based on such data basis. The results from large-scale testing cases show that the traffic status can be fairly well estimated based on these imperfect data and we demonstrate the feasibility of such application in most of cities.

We present a mobile sensor system for traffic monitoring (GSSTM), which is a typically Grid application in ShanghaiGrid to provide accurate realtime traffic status information. Several issues and challenges in GSSTM are discussed, such as Grid architecture design, data processing for traffic status estimation, storage strategy of massive data, etc. We implemented a prototype system of GSSTM and carried out a field testing in Shanghai city by using GPS-based sensors on 4000 taxis. The testing results show that by utilizing the Grid technology, the expected performance can be obtained, such as stability, scalability, etc. Meantime, traffic status can be fairly well estimated in GSSTM.

A disruption-tolerant network (DTN) attempts to route packets between nodes that are temporarily connected. Difficulty in such networks is that nodes have no information about the network status and contact opportunities. The situation is different in public bus networks because the movement of buses exhibits some regularity so that routing in a deterministic way is possible. Many algorithms use a contacts oracle that provides the exact meeting times and durations between all nodes. However, in a real vehicular environment, an oracle is not always accurate, and deterministic routing gives poor results. In this paper, we present BLER, a routing algorithm that achieves effective routing in a buses environment. BLER, compared to other algorithms, performs routing at bus line level instead of bus level; it uses specific bus lines information to achieve good performances. We evaluate BLER on real traces of the bus network of Shanghai, and compare it to other routing algorithms. Performances provide good results for this kind of DTNs.