Showing papers in "IEEE Transactions on Vehicular Technology in 2012"

Electrical Motor Drivelines in Commercial All-Electric Vehicles: A Review

Abstract: This paper presents a critical review of the drivelines in all-electric vehicles (EVs). The motor topologies that are the best candidates to be used in EVs are presented. The advantages and disadvantages of each electric motor type are discussed from a system perspective. A survey of the electric motors used in commercial EVs is presented. The survey shows that car manufacturers are very conservative when it comes to introducing new technologies. Most of the EVs on the market mount a single induction or permanent-magnet (PM) motor with a traditional mechanic driveline with a differential. This paper illustrates that comparisons between the different motors are difficult by the large number of parameters and the lack of a recommended test scheme. The authors propose that a standardized drive cycle be used to test and compare motors.

Comprehensive Topological Analysis of Conductive and Inductive Charging Solutions for Plug-In Electric Vehicles

Abstract: The impending global energy crisis has opened up new opportunities for the automotive industry to meet the ever-increasing demand for cleaner and fuel-efficient vehicles. This has necessitated the development of drivetrains that are either fully or partially electrified in the form of electric and plug-in hybrid electric vehicles (EVs and HEVs), respectively, which are collectively addressed as plug-in EVs (PEVs). PEVs in general are equipped with larger on-board storage and power electronics for charging or discharging the battery, in comparison with HEVs. The extent to which PEVs are adopted significantly depends on the nature of the charging solution utilized. In this paper, a comprehensive topological survey of the currently available PEV charging solutions is presented. PEV chargers based on the nature of charging (conductive or inductive), stages of conversion (integrated single stage or two stages), power level (level 1, 2, or 3), and type of semiconductor devices utilized (silicon, silicon carbide, or gallium nitride) are thoroughly reviewed in this paper.

Pseudonym Changing at Social Spots: An Effective Strategy for Location Privacy in VANETs

Abstract: As a prime target of the quality of privacy in vehicular ad hoc networks (VANETs), location privacy is imperative for VANETs to fully flourish. Although frequent pseudonym changing provides a promising solution for location privacy in VANETs, if the pseudonyms are changed in an improper time or location, such a solution may become invalid. To cope with the issue, in this paper, we present an effective pseudonym changing at social spots (PCS) strategy to achieve the provable location privacy. In particular, we first introduce the social spots where several vehicles may gather, e.g., a road intersection when the traffic light turns red or a free parking lot near a shopping mall. By taking the anonymity set size as the location privacy metric, we then develop two anonymity set analytic models to quantitatively investigate the location privacy that is achieved by the PCS strategy. In addition, we use game-theoretic techniques to prove the feasibility of the PCS strategy in practice. Extensive performance evaluations are conducted to demonstrate that better location privacy can be achieved when a vehicle changes its pseudonyms at some highly social spots and that the proposed PCS strategy can assist vehicles to intelligently change their pseudonyms at the right moment and place.

Bit Error Probability of SM-MIMO Over Generalized Fading Channels

Abstract: In this paper, we study the performance of spatial modulation (SM) multiple-input-multiple-output (MIMO) wireless systems over generic fading channels. More precisely, a comprehensive analytical framework to compute the average bit error probability (ABEP) is introduced, which can be used for any MIMO setup, for arbitrary correlated fading channels, and for generic modulation schemes. It is shown that, when compared with state-of-the-art literature, our framework 1) has more general applicability over generalized fading channels, 2) is, in general, more accurate as it exploits an improved union-bound method, and, 3) more importantly, clearly highlights interesting fundamental trends about the performance of SM, which are difficult to capture with available frameworks. For example, by focusing on the canonical reference scenario with independent identically distributed Rayleigh fading, we introduce very simple formulas that yield insightful design information on the optimal modulation scheme to be used for the signal constellation diagram, as well as highlight the different roles played by the bit mapping on the signal and spatial constellation diagrams. Numerical results show that, for many MIMO setups, SM with phase-shift-keying (PSK) modulation outperforms SM with quadrature-amplitude modulation (QAM), which is a result never reported in the literature. In addition, by exploiting asymptotic analysis, closed-form formulas of the performance gain of SM over other single-antenna transmission technologies are provided. Numerical results show that SM can outperform many single-antenna systems and that, for any transmission rate, there is an optimal allocation of the information bits onto spatial and signal constellation diagrams. Furthermore, by focusing on the Nakagami-fading scenario with generically correlated fading, we show that fading severity plays a very important role in determining the diversity gain of SM. In particular, the performance gain over single-antenna systems increases for fading channels less severe than Rayleigh fading, whereas it gets smaller for more severe fading channels. In addition, it is shown that the impact of fading correlation at the transmitter is reduced for less severe fading. Finally, analytical frameworks and claims are substantiated through extensive Monte Carlo simulations.

Optimizing for Efficiency or Battery Life in a Battery/Supercapacitor Electric Vehicle

Abstract: A novel energy control strategy for a battery/supercapacitor vehicle, which is designed to be tunable to achieve different goals, is described. Two possible goals for adding a pack of supercapacitors are examined for a test vehicle using lead-acid batteries: 1) improving the vehicle's efficiency and range and 2) reducing the peak currents in the battery pack to increase battery life. The benefits of hybridization are compared with those achievable by increasing the size of the battery pack by a comparable mass to the supercapacitors. The availability of energy from regenerative braking and the characteristics of the supercapacitors are considered as impact factors. Supercapacitors were found to be effective at reducing peak battery currents; however, the benefits to range extension were found to be limited. A battery life extension of at least 50% is necessary to make supercapacitors cost effective for the test vehicle at current prices.

Lateral Stability Control of In-Wheel-Motor-Driven Electric Vehicles Based on Sideslip Angle Estimation Using Lateral Tire Force Sensors

Abstract: This paper presents a method for using lateral tire force sensors to estimate vehicle sideslip angle and to improve vehicle stability of in-wheel-motor-driven electric vehicles (IWM-EVs) Considering that the vehicle motion is governed by tire forces, lateral tire force measurements give practical benefits in estimation and motion control To estimate the vehicle sideslip angle, a state observer derived from the extended-Kalman-filtering (EKF) method is proposed and evaluated through field tests on an experimental IWM-EV Experimental results show the ability of a proposed observer to provide accurate estimation Moreover, using the estimated sideslip angle and tire cornering stiffness, the vehicle stability control system, making best use of the advantages of IMW-EVs with a steer-by-wire system, is proposed Computer simulation using Matlab/Simulink-Carsim and experiments are carried out to demonstrate the effectiveness of the proposed stability control system Practical application of lateral tire force sensors to vehicle control systems is discussed for future personal electric vehicles

Efficiency Analysis of Drive Train Topologies Applied to Electric/Hybrid Vehicles

Abstract: One of the most important research topics in drive train topologies applied to electric/hybrid vehicles is the efficiency analysis of the power train components, including the global drive efficiency. In this paper, two basic traction electric drive systems of electric/hybrid vehicles are presented and evaluated, with a special focus on the efficiency analysis. The first topology comprises a traditional pulsewidth-modulation (PWM) battery-powered inverter, whereas in the second topology, the battery is connected to a bidirectional dc-dc converter, which supplies the inverter. Furthermore, a variable-voltage control technique applied to this second topology is presented, which allows for the improvement of the drive overall performance. Some simulation results are presented, considering both topologies and a permanent-magnet synchronous motor (PMSM). An even more detailed analysis is performed through the experimental validation. Particular attention is given to the evaluation of the main drive components efficiency, including the global drive efficiency, presented in the form of efficiency maps. Other parameters such as motor voltage distortion and power factor are also considered. In addition, the comparison of the two topologies takes into account the drive operation under the motoring and regenerative-braking modes.

Energy-Efficient Resource Allocation for Secure OFDMA Systems

Abstract: In this paper, resource allocation for energy-efficient secure communication in an orthogonal frequency-division multiple-access (OFDMA) downlink network is studied The considered problem is modeled as a nonconvex optimization problem that takes into account the sum-rate-dependent circuit power consumption, multiple-antenna eavesdropper, artificial noise generation, and different quality-of-service (QoS) requirements, including a minimum required secrecy sum rate and a maximum tolerable secrecy outage probability The power, secrecy data rate, and subcarrier allocation policies are optimized for maximization of the energy efficiency of secure data transmission (bit/joule securely delivered to the users) The considered nonconvex optimization problem is transformed into a convex optimization problem by exploiting the properties of fractional programming, which results in an efficient iterative resource allocation algorithm In each iteration, the transformed problem is solved by using dual decomposition Simulation results illustrate that the proposed iterative resource allocation algorithm not only converges in a small number of iterations but maximizes the system energy efficiency and guarantees a nonzero secrecy data rate for the desired users as well In addition, the obtained results unveil a tradeoff between energy efficiency and secure communication

${\cal CPAS}$ : An Efficient Conditional Privacy-Preserving Authentication Scheme for Vehicular Sensor Networks

Abstract: In this paper, we propose a conditional privacy-preserving authentication scheme, called CPAS, using pseudo-identity-based signatures for secure vehicle-to-infrastructure communications in vehicular ad hoc networks. The scheme achieves conditional privacy preservation, in which each message launched by a vehicle is mapped to a distinct pseudo-identity, and a trust authority can always retrieve the real identity of a vehicle from any pseudo-identity. In the scheme, a roadside unit (RSU) can simultaneously verify multiple received signatures, thus considerably reducing the total verification time; an RSU can simultaneously verify 2540 signed-messages/s. The time for simultaneously verifying 800 signatures in our scheme can be reduced by 18%, compared with the previous scheme.

Design and Analysis of a Robust Broadcast Scheme for VANET Safety-Related Services

Abstract: IEEE- and ASTM-adopted dedicated short-range communications (DSRC) standards are key enabling technologies for the next generation of vehicular safety communications. Vehicle-safety-related communication services, which require reliable and fast message delivery, usually demand broadcast communications in vehicular ad hoc networks (VANETs). In this paper, we propose and justify a distributive cross-layer scheme for the design of the control channel in DSRC with three levels of broadcast services that are critical to most potential vehicle-safety-related applications. The new scheme for enhancing broadcast reliability includes preemptive priority in safety services, dynamic receiver-oriented packet repetitions for one-hop emergency warning message dissemination, a multifrequency busy tone and minislot within the distributed interframe space (DIFS) in IEEE 802.11, and robust distance-based relay selection for multihop broadcast of emergency notification messages. Compared with a current draft of IEEE 802.11p and other schemes for DSRC safety-related services, the scheme proposed in this paper is more robust and scalable and easy to implement. Additionally, we investigate the reliability and performance of the proposed broadcast scheme for DSRC VANET safety-related services on the highway analytically and by simulations. The analytic model accounts for the impact of the hidden terminal problem, the fading channel conditions, varied message arrival intervals, and the backoff counter process on reliability and performance.

An Automotive Onboard 3.3-kW Battery Charger for PHEV Application

Abstract: An onboard charger is responsible for charging the battery pack in a plug-in hybrid electric vehicle (PHEV). In this paper, a 3.3-kW two-stage battery charger design is presented for a PHEV application. The objective of the design is to achieve high efficiency, which is critical to minimize the charger size, charging time, and the amount and cost of electricity drawn from the utility. The operation of the charger power converter configuration is provided in addition to a detailed design procedure. The mechanical packaging design and key experimental results are provided to verify the suitability of the proposed charger power architecture.

Physical Layer Security for Two-Way Untrusted Relaying With Friendly Jammers

Abstract: In this paper, we consider a two-way relay system where the two sources can only communicate through an untrusted intermediate relay and investigate the physical layer security issue in this two-way untrusted relay scenario. Specifically, we regard the intermediate relay as an eavesdropper from which the information transmitted by the sources needs to be kept confidential, despite the fact that its cooperation in relaying this information is essential. We first indicate that a nonzero secrecy rate is indeed achievable in this two-way untrusted relay system even without the help of external friendly jammers. As for the system with friendly jammers, after further analysis, we can obtain the secrecy rate of the sources can be effectively improved by utilizing proper jamming power from the friendly jammers. Then, we formulate a Stackelberg game between the sources and the friendly jammers as a power control scheme to achieve the optimized secrecy rate of the sources, in which the sources are treated as the sole buyer and the friendly jammers are the sellers. In addition, the optimal solutions of the jamming power and the asking prices are given, and a distributed updating algorithm to obtain the Stackelberg equilibrium is provided for the proposed game. Finally, the simulation results verify the properties and efficiency of the proposed Stackelberg-game-based scheme.

Battery State-of-Health Perceptive Energy Management for Hybrid Electric Vehicles

Abstract: This paper presents a causal optimal control-based energy management strategy for a parallel hybrid electric vehicle (HEV). This strategy not only seeks to minimize fuel consumption while maintaining the state-of-charge of the battery within reasonable bounds but to minimize wear of the battery by penalizing the instantaneous battery usage with respect to its relative impact on battery life as well. This impact is derived by means of a control-oriented state-of-health model. The results indicate that the proposed causal strategy effectively reduces battery wear with only a relatively small penalty on fuel consumption. Ultimately, in terms of cost of fuel and battery replacements, the total cost of ownership over the entire life of the vehicle is significantly reduced.

Analysis and Evaluation of DC-Link Capacitors for High-Power-Density Electric Vehicle Drive Systems

Abstract: In electric vehicle (EV) inverter systems, direct-current-link capacitors, which are bulky, heavy, and susceptible to degradation from self heating, can become a critical obstacle to high power density. This paper presents a comprehensive method for the analysis and comparative evaluation of dc-link capacitor applications to minimize the volume, mass, and capacitance. Models of equivalent series resistance that are valid over a range of frequency and operating temperature are derived and experimentally validated. The root-mean-square values and frequency spectra of the capacitor current are analyzed with respect to three modulation strategies and various operating conditions over practical ranges of load power factor and modulation index in EV drive systems. The modeling and analysis also consider the self-heating process and resulting core temperature of the dc-link capacitors, which impacts their lifetimes. Based on an 80-kW permanent-magnet (PM) motor drive system, the application of electrolytic capacitors and film capacitors has been evaluated by both simulation and experimental tests. The inverter power density is improved from 2.99 kW/L to 13.3 kW/L, without sacrificing the system performance in terms of power loss, core temperature, and lifetime.

Energy-Efficient Cooperative Spectrum Sensing by Optimal Scheduling in Sensor-Aided Cognitive Radio Networks

Abstract: A promising technology that tackles the conflict between spectrum scarcity and underutilization is cognitive radio (CR), of which spectrum sensing is one of the most important functionalities. The use of dedicated sensors is an emerging service for spectrum sensing, where multiple sensors perform cooperative spectrum sensing. However, due to the energy constraint of battery-powered sensors, energy efficiency arises as a critical issue in sensor-aided CR networks. An optimal scheduling of each sensor active time can effectively extend the network lifetime. In this paper, we divide the sensors into a number of nondisjoint feasible subsets such that only one subset of sensors is turned on at a period of time while guaranteeing that the necessary detection and false alarm thresholds are satisfied. Each subset is activated successively, and nonactivated sensors are put in a low-energy sleep mode to extend the network lifetime. We formulate such problem of energy-efficient cooperative spectrum sensing in sensor-aided CR networks as a scheduling problem, which is proved to be NP-complete. We employ Greedy Degradation to degrade it into a linear integer programming problem and propose three approaches, namely, Implicit Enumeration (IE), General Greedy (GG), and λ-Greedy (λG), to solve the subproblem. Among them, IE can achieve an optimal solution with the highest computational complexity, whereas GG can provide a solution with the lowest complexity but much poorer performance. To achieve a better tradeoff in terms of network lifetime and computational complexity, a brand new λG is proposed to approach IE with the complexity comparable with GG. Simulation results are presented to verify the performance of our approaches, as well as to study the effect of adjustable parameters on the performance.

Autonomous Platoon Control Allowing Range-Limited Sensors

Abstract: This paper investigates control design for the platoon of automated vehicles whose sensors have limited sensing capability. A novel hybrid platoon model is established, in which actuator delay (e.g., the fueling and braking delay) and the effect of sensing range limitation are involved. Based on the new model, a framework of guaranteed-cost controller design is presented, which can robustly stabilize the platoon of vehicles with a given level of disturbance attenuation. The obtained controller is complemented by additional conditions that were established to guarantee string stability and zero steady-state spacing error, yielding a useful string-stable platoon control algorithm. The effectiveness and advantage of the presented methodology is demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

Intelligent OLSR Routing Protocol Optimization for VANETs

Abstract: Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobility of the nodes generate frequent topology changes and network fragmentations. For these reasons, and taking into account that there is no central manager entity, routing packets through the network is a challenging task. Therefore, offering an efficient routing strategy is crucial to the deployment of VANETs. This paper deals with the optimal parameter setting of the optimized link state routing (OLSR), which is a well-known mobile ad hoc network routing protocol, by defining an optimization problem. This way, a series of representative metaheuristic algorithms (particle swarm optimization, differential evolution, genetic algorithm, and simulated annealing) are studied in this paper to find automatically optimal configurations of this routing protocol. In addition, a set of realistic VANET scenarios (based in the city of Malaga) have been defined to accurately evaluate the performance of the network under our automatic OLSR. In the experiments, our tuned OLSR configurations result in better quality of service (QoS) than the standard request for comments (RFC 3626), as well as several human experts, making it amenable for utilization in VANET configurations.

Hybrid Electric Vehicle Model Predictive Control Torque-Split Strategy Incorporating Engine Transient Characteristics

Abstract: This paper presents a model predictive control (MPC) torque-split strategy that incorporates diesel engine transient characteristics for parallel hybrid electric vehicle (HEV) powertrains. To improve HEV fuel efficiency, torque split between the diesel engine and the electric motor and the decision as to whether the engine should be on or off are important. For HEV applications where the engines experience frequent transient operations, including start-stop, the effect of the engine transient characteristics on the overall HEV powertrain fuel economy becomes more pronounced. In this paper, by incorporating an experimentally validated real-time-capable transient diesel-engine model into the MPC torque-split method, the engine transient characteristics can be well reflected on the HEV powertrain supervisory control decisions. Simulation studies based on an HEV model with actual system parameters and an experimentally validated diesel-engine model indicate that the proposed MPC supervisory strategy considering diesel engine transient characteristics possesses superior equivalent fuel efficiency while maintaining HEV driving performance.

Resource Allocation with Interference Avoidance in OFDMA Femtocell Networks

Abstract: Interference control and quality-of-service (QoS) awareness are the major challenges for resource management in orthogonal frequency-division multiple access femtocell networks This paper investigates a self-organization strategy for physical resource block (PRB) allocation with QoS constraints to avoid the co-channel and co-tiered interference Femtocell self-organization including self-configuration and self-optimization is proposed to manage the large femtocell networks We formulate the optimization problem for PRB assignments where multiple QoS classes for different services can be supported, and interference between femtocells can be completely avoided The proposed formulation pursues the maximization of PRB efficiency A greedy algorithm is developed to solve the resource allocation formulation In the simulations, the proposed approach is observed to increase the system throughput by over 13% without femtocell interference Simulations also demonstrate that the rejection ratios of all QoS classes are low and mostly below 10% Moreover, the proposed approach improves the PRB efficiency by over 82% in low-loading scenario and 13% in high-loading scenario

Performance of the 802.11p Physical Layer in Vehicle-to-Vehicle Environments

Abstract: A reliable robust wireless network of connected vehicles is desired to enable a number of future telematics and infotainment applications in the vehicular domain. To achieve this objective, vehicle-to-vehicle (V2V) communication is standardized by the IEEE 802.11p Dedicated Short Range Communications (DSRC) standard. Providing reliable communication performance in a highly dynamic time-varying V2V channel is a challenging task. To tackle this challenge, we propose a dynamic equalization scheme, on top of the existing DSRC technology, that significantly improves the packet error rate (PER) of data transmissions without changing the DSRC standard. We also show a hardware implementation of this scheme based on a field-programmable gate array (FPGA) to demonstrate its implementation feasibility. Furthermore, we extend our improved equalization scheme to various data rate options available in the DSRC standard, showing that the proposed scheme is sufficiently generic to support different types of V2V communication. Finally, we report the results of investigating the dependence of wireless communication performance (in terms of PER and throughput) on various design parameters such as packet length, payload size, and data rate.

Cognitive Amplify-and-Forward Relay Networks Over Nakagami- $m$ Fading

Abstract: In this correspondence, the outage probability (OP) of dual-hop cognitive amplify-and-forward (AF) relay networks subject to independent non-identically distributed (i.n.i.d.) Nakagami-m fading is examined. We assume a spectrum-sharing environment, where two different strategies are proposed to determine the transmit powers of the secondary network. Specifically, the transmit power conditions of the proposed spectrum-sharing network are governed by either the combined power constraint of the interference on the primary network and the maximum transmission power at the secondary network or the single power constraint of the interference on the primary network. Closed-form lower bounds and asymptotic expressions for the OP are derived. Regardless of the transmit power constraint, we reveal that the diversity order is strictly defined by the minimum fading severity between the two hops of the secondary network. This aligns with the well-known result for conventional dual-hop AF relaying without spectrum sharing. Furthermore, the impact of the primary network on the diversity-multiplexing tradeoff is investigated. We confirm that the diversity-multiplexing tradeoff is independent of the primary network.

CellSense: An Accurate Energy-Efficient GSM Positioning System

Abstract: Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this paper, we present CellSense, which is a probabilistic received signal strength indicator (RSSI)-based fingerprinting location determination system for Global System for Mobile Communications (GSM) phones. We discuss the challenges of implementing a probabilistic fingerprinting localization technique in GSM networks and present the details of the CellSense system and how it addresses these challenges. We then extend the proposed system using a hybrid technique that combines probabilistic and deterministic estimations to achieve both high accuracy and low computational overhead. Moreover, the accuracy of the hybrid technique is robust to changes in its parameter values. To evaluate our proposed system, we implemented CellSense on Android-based phones. Results from two different testbeds, representing urban and rural environments, for three different cellular providers show that CellSense provides at least 108.57% enhancement in accuracy in rural areas and at least 89.03% in urban areas compared with current state-of-the-art RSSI-based GSM localization systems. In additional, the proposed hybrid technique provides more than 6 and 5.4 times reduction in computational requirements compared with state-of-the-art RSSI-based GSM localization systems for rural and urban testbeds, respectively. We also evaluate the effect of changing the different system parameters on the accuracy-complexity tradeoff and how the cell tower and fingerprint densities affect system performance.

$\hbox{Prius}^{+}$ and $\hbox{Volt}^{-}$ : Configuration Analysis of Power-Split Hybrid Vehicles With a Single Planetary Gear

Abstract: The majority of hybrid electric vehicles (HEVs) available on the market are power-split hybrid vehicles with a single planetary gear (PG), including the popular Toyota Prius and Chevy Volt. Although both vehicles use a single PG, they have different configurations with different numbers of operating modes. The Prius has no clutch and has a single operating mode, whereas the Chevy Volt uses three clutches and has four modes. The goal of this paper is to present a thorough analysis of all possible configurations of power-split hybrid powertrain using a single PG. The analysis includes the following steps: 1) search for all possible ways to connect powertrain elements to the PG; 2) identify all potential locations for clutch installations around the PG and examine the feasibility of additional operating modes introduced by the clutch installation; and 3) optimize fuel economy for performance comparison. The proposed analysis shows that a single PG can produce 12 different configurations, each of which can have four feasible operating modes by adding three clutches to the PG. In case studies, we focus on the two configurations that are used in the Prius and Volt to find the impact of adding (or removing) clutches and modes on their fuel economy performance. Our results show that adding one clutch to the Prius transmission (which is named “Prius+”) can significantly improve fuel economy in urban driving, whereas removing two clutches from the Volt transmission (“Volt-”) will not significantly affect fuel economy in both urban and highway driving. This multimode configuration analysis can be used to systematically design future power-split HEVs.

A Reputation-Based Announcement Scheme for VANETs

Abstract: Vehicular ad hoc networks (VANETs) allow vehicles to generate and broadcast messages to inform nearby vehicles about road conditions, such as traffic congestion and accidents. Neighboring vehicles can utilize this information, which may improve road safety and traffic efficiency. However, messages generated by vehicles may not be reliable. We propose a novel announcement scheme for VANETs based on a reputation system that allows evaluation of message reliability. We present a secure and efficient scheme that is robust and fault tolerant against temporary unavailability of the central server.

Enhanced Road Boundary and Obstacle Detection Using a Downward-Looking LIDAR Sensor

Abstract: Detection of road boundaries and obstacles is essential for autonomous vehicle navigation. In this paper, we propose a road boundary and obstacle detection method using a downward-looking light detection and ranging sensor. This method extracts line segments from the raw data of the sensor in polar coordinates. After that, the line segments are classified into road and obstacle segments. To enhance the classification performance, the estimated roll and pitch angles of the sensor relative to the scanning road surface in the previous time step are then used. The classified road line segments are applied to track the road boundaries, roll, and pitch angles by using an integrated probabilistic data association filter. The proposed method was evaluated with the autonomous vehicle A1, which was the winner of the 2010 Autonomous Vehicle Competition in Korea organized by the Hyundai-Kia automotive group. The proposed method using the estimated roll and pitch angles can detect road boundaries and roadside, as well as road obstacles under various road conditions, including paved and unpaved roads and intersections.

Transmit Diversity and Relay Selection Algorithms for Multirelay Cooperative MIMO Systems

Abstract: In this paper, we propose a set of joint transmit diversity selection (TDS) and relay selection (RS) algorithms based on discrete iterative stochastic optimization for the uplink of cooperative multiple-input-multiple-output (MIMO) systems. Decode-and-forward (DF) and amplify-and-forward (AF) multirelay systems with linear minimum mean square error (MSE), successive interference cancelation, and adaptive reception are considered. The problems of TDS and RS are expressed as MSE and mutual information (MI) joint discrete optimization problems and solved using iterative discrete stochastic algorithms. Such an approach circumvents the need for exhaustive searching and results in a range of procedures with low complexity and increased speed of convergence that can track the optimal selection over an estimated channel. The proposed schemes are analyzed in terms of their complexity, convergence, and diversity benefits and are shown to be both stable and computationally efficient. Their performance is then evaluated via MSE, MI, and bit error rate comparisons and shown to outperform conventional cooperative transmission and, in the majority of scenarios, match that of the optimal exhaustive solution.

Intelligent Hybrid Vehicle Power Control—Part I: Machine Learning of Optimal Vehicle Power

Abstract: In this series of two papers, we present our research on intelligent energy management for hybrid electric vehicles (HEVs). These two papers cover the modeling of power flow in HEVs, the mathematical background of optimization in energy management in HEVs, a machine learning framework that combines dynamic programming (DP) with machine learning to learn about roadway-type- and traffic-congestion-level-specific energy optimization, machine learning algorithms, and real-time quasi-optimal control of energy flow in an HEV. This first paper presents our research on machine learning for optimal energy management in HEVs. We will present a machine learning framework ML_EMO_HEV developed for the optimization of energy management in an HEV, machine learning algorithms for predicting driving environments, and the generation of an optimal power split for a given driving environment. Experiments are conducted based on a simulated Ford Escape Hybrid vehicle model provided by Argonne National Laboratory's Powertrain Systems Analysis Toolkit (PSAT). Based on the experimental results on the test data, we can conclude that the neural networks trained under the ML_EMO_HEV framework are effective in predicting roadway type and traffic congestion levels, predicting driving trends, and learning optimal engine speed and optimal battery power from DP.

Modeling Prioritized Broadcasting in Multichannel Vehicular Networks

Abstract: Effective data broadcasting is essential in vehicular networks not only for road-safety message dissemination but also to aid routing and cooperative driving applications through periodic beaconing and to spread network initialization advertisements that are mandatory to support infotainment applications. Broadcast data are neither acknowledged nor retransmitted in case of failure, which raises the possibility of frame loss due to channel errors and collisions with multiple simultaneous broadcasts. This paper aims at modeling periodic broadcasting on the control channel of IEEE Std. 802.11p vehicular networks with multichannel architecture. Unlike previous related work, the proposed novel analytical approach accounts for mutual influence among nodes, frequent periodic updates of broadcasted data, standard network advertisement procedures, and 802.11p prioritized channel access with multichannel-related phenomena under various link quality conditions.

Secure Incentives for Commercial Ad Dissemination in Vehicular Networks

Abstract: This paper introduces a promising application over vehicular ad hoc networks (VANETs), where advertisers use VANETs to disseminate their commercial ads via car-to-car communication, targeting a large number of potential customers inside cars. However, due to the noncooperative behavior of selfish or even malicious nodes in real-world scenarios, such a vehicular advertisement system cannot be realized unless proper incentives and security mechanisms are in place. This paper presents signature-seeking drive (SSD), which is a secure incentive framework that stimulates cooperative dissemination of advertising messages among vehicular users in a secure way. Unlike existing incentive systems, SSD does not rely on tamper-proof hardware or game-theoretic approaches but leverages a public key infrastructure to provide secure incentives for cooperative nodes. With a set of ad dissemination designs proposed, we demonstrate that our SSD is robust in both incentive and security perspectives.

Performance Study of Two-Hop Amplify-and-Forward Systems With Untrustworthy Relay Nodes

Abstract: This paper investigates the problem of secure communication for amplify-and-forward (AF) systems with untrustworthy relay nodes. To achieve positive secrecy rate, the destination-based jamming (DBJ) technique is applied. We first focus on the single-relay scenario, for which the closed-form expression for the lower bound of the ergodic secrecy capacity (ESC) is derived. Afterward, we extend the DBJ method to the multi-relay scenario and propose a secure relay selection scheme that can maximize the achievable secrecy rate. Based on the extreme-value theory, the approximate ESC is characterized. Our work reveals an interesting result that, when the relay nodes are untrustworthy, the system performance worsens as the number of relays increases.