Safety Messages Research Articles

A VANET Collision Warning System with Cloud Aided Pliable Q-Learning and Safety Message Dissemination

Ease of self-driving technological developments revives Vehicular Adhoc Networks (VANETs) and motivates the Intelligent Transportation System (ITS) to develop novel intelligent solutions to amplify the VANET safety and efficiency. Collision warning system plays a significant role in VANET due to the avoidance of fatalities in vehicle crashes. Different kinds of collision warning systems have been designed for diverse VANET scenarios. Among them, reinforcement-based machine learning algorithms receive much attention due to the dispensable of explicit modeling about the environment. However, it is a censorious task to retrieve the Q-learning parameters from the dynamic VANET environment effectively. To handle such issue and safer the VANET driving environment, this paper proposes a cloud aided pliable Q-Learning based Collision Warning Prediction and Safety message Dissemination (QCP-SD). The proposed QCP-SD integrates two mechanisms that are pliable Q-learning based collision prediction and Safety alert Message Dissemination. Firstly, the designing of pliable Q-learning parameters based on dynamic VANET factors with Q-learning enhances collision prediction accuracy. Further, it estimates the novel metric named as Collision Risk Factor (CRF) and minimizes the driving risks due to vehicle crashes. The execution of pliable Q-learning only at RSUs minimizes the vehicle burden and reduces the design complexity. Secondly, the QCP-SD sends alerts to the vehicles in the risky region through highly efficient next-hop disseminators selected based on a multi-attribute cost value. Moreover, the performance of QCP-SD is evaluated through Network Simulator (NS-2). The efficiency is analyzed using the performance metrics that are duplicate packet, latency, packet loss, packet delivery ratio, secondary collision, throughput, and overhead.

Performance Evaluation of CAM Broadcast Message and Vehicle Safe Distance Under Nakagami-m Radio Channel Conditions

Many potentials exist in the 5G era for effectively managing vehicle safety on the road. The European Telecommunications Standards Institute (ETSI) 5G C-V2X standards for Cooperative Aware Messages for Intelligent Transport Systems (ITS) provide necessary upper-layer requirements for safety message distribution between vehicles using Cooperative Aware Messages (CAM). In addition, the Long Term Evolution (LTE) mobile radio technology in Release-14 has two modes of communication, mode 3 and mode 4, to facilitate vehicle-to-vehicle communications. The focus of this study is on vehicle communications in a mode 3 environment, in which the cellular network chooses and manages the radio services utilised by vehicles for direct vehicle-to-vehicle communication. The performance modelling of Safety Avoidance Time (AT) and safety CAM message broadcast for vehicle-to-vehicle communication in LTE C-V2X under the Nakagami-m radio channel, which has two components, LOS and NLOS, is studied in this thesis. Under the Nakagami-m radio channel, the LOS and NLOS components will affect the CAM message disseminating to other vehicles within safe time gaps. Therefore, the aim of this study is to look into the various radio channel characteristics in a vehicle-to-vehicle communication environment that are related to CAM message dissemination and vehicle safe distance, as well as to evaluate the performance of the relationship between PDR, throughput, and transmit power proportional to safe time gaps under the Nakagami-m radio channel with various setting shape factors.

Architecture of Emergency Communication Systems in Disasters through UAVs in 5G and Beyond

Unmanned aerial vehicles (UAVs) are valued in 5G and 6G networks due to their communication capabilities, low cost, and flexible deployment. Recently, UAV-aided emergency networks in disasters have been designed where one single large UAV is used. Compared with a single large UAV, Flying Ad Hoc Networks (FANETs) with small UAVs have many benefits. Therefore, instead of a single large UAV, a FANET is proposed in this paper. To take full advantage of their services, UAVs must be able to communicate efficiently with each other and with existing networking infrastructures. However, high node mobility is one of the main characteristics of FANETs, which can result in rapid topology changes with frequent link breakage and unstable communications that cause collision and packet loss. As an alternative, networks can be broken up into smaller groups or clusters to control their topology efficiently and reduce channel contention. In this study, a novel cluster-based mechanism is proposed for FANETs. The process of cluster management is described. The IEEE 802.11 backoff method is specifically intended for direct communications and is not appropriate for cluster-based communications. Therefore, a new backoff mechanism is proposed based on cluster size to optimize performance. An analytical study using the Markov chain model is presented to explore the performance of the proposed mechanism. The study takes into account Nakagami-m fading channels. Performance-influencing parameters are taken into consideration and the relationships among these parameters as well as performance metrics such as throughput, packet dropping rate, outage probability, and delay are obtained. Furthermore, simulation results are provided which verify the analytical studies. A quantitative comparison with current cluster-based methods is also presented. The simulation results show that the suggested technique enhances system performance and complies with the safety message delay constraint of 100 ms.

Partnering with High-Risk Communities to Successfully Reduce Pediatric Injury Over Time

Injury is the leading cause of childhood morbidity and mortality. Injury prevention (IP) initiatives are often created in isolation from the communities most affected. We hypothesized that the use of a comprehensive approach to injury prevention through community partnerships will result in a measurable reduction in pediatric injuries. The IP program at our free-standing level 1 pediatric trauma center developed partnerships within eight targeted high-risk communities. IP coordinators and community partners implemented programs driven by community-specific injury data and community input. Programs focused on home, bike, playground, pedestrian, and child passenger safety. Program components included in-home education with free safety equipment and installation; free bike helmet fittings and distribution; community playground builds; and car seat classes with education, free car seat distribution and installation. Using trauma registry data, we compared injuries rates in targeted communities with non-intervention communities county-wide over an eight-year period. Between 2012 and 2019, nearly 4000 families received home safety equipment and education through community partnerships. Approximately 2000 bike helmets, 900 car/booster seats, in addition to safety messages and education were provided across the intervention communities. Over this 8-year time period, the injury rates significantly decreased by 28.4%, across the eight targeted high-risk communities, compared to a 10.9% reduction in non-intervention communities across the county. Effective injury prevention can be achieved through partnerships, working in solidarity with community members to address actual areas of concern to them. Sharing data, seeking ongoing community input, continuously reviewing learnings, and implementing identified changes are crucial to the success of such partnerships. Level III.

A Novel V2V-Based Temporary Warning Network for Safety Message Dissemination in Urban Environments

Vehicular communication networks (VCNs) have been widely recognized as promising solutions to support safety-related applications in urban transportation systems. However, constructing and maintaining such networks is quite challenging due to the complex traffic and communication environment. Substantial studies have focused on the design of the networking schemes and message dissemination protocols. Nonetheless, most existing designs only consider the connectivity and rapid end-to-end transmission, regardless of the network coverage and duration. In this article, we propose a novel temporary warning network (TWN) for safety message dissemination in the urban traffic environment, in which both the spatial distribution and temporal duration of the networking scheme are taken into account. Specifically, TWN is constructed by the selection of relay vehicles based on the spatiotemporal correlation of vehicle trajectory so that the safety message can be quickly disseminated within the Regions of Interest (RoIs). To maintain TWN during an accident, a reselection mechanism is also proposed, which enables newly come vehicles in the RoI to receive the messages in time. Finally, we conduct extensive numerical experiments to validate the effectiveness of our method in various traffic scenarios.

CluRMA: A cluster-based RSU-enabled message aggregation scheme for vehicular ad hoc networks

The fundamental goal of Vehicular Ad hoc NETworks (VANETs) is to facilitate safe driving by sending safety/warning messages to vehicles as well as to exchange non-safety/infotainment messages among vehicles. Flooding is a common broadcasting technique and it is mainly used for disseminating safety/non-safety messages. However, flooding causes broadcast storm problem which is the most challenging issue in VANETs. In a dense vehicular network, high message generation rate demanding more transmissions could further increases the effects of the broadcast storm problem. In this context, message aggregation schemes could offer a great relief. In this paper, we propose a cluster based RSU enabled message aggregation protocol (CluRMA) which applies two levels of message aggregation — local aggregation at the cluster heads and global aggregation at the Road Side Unit (RSU). Before message aggregation process is performed, we make use of cosine distance for similarity checking between the messages for eliminating the duplicates. Then the syntactic aggregation is accomplished by employing message compression techniques — Adaptive Huffman Compression technique for safety messages, and Arithmetic Coding Technique for non-safety messages. The competence of the proposed scheme has been rigorously analyzed and compared with the existing ones regarding several metrics including delay, packet delivery ratio, collision rate, redundancy rate and overload.

Impact of Victorian COVID-19 restrictions on emergency department presentations and hospital admissions for ophthalmic conditions

ABSTRACT Clinical Relevance Assessing the extent to which COVID-19 impacted hospitals can provide important learnings for future pandemics. Background This study aims to determine the impact of the 7-month duration COVID-19 pandemic-related lockdown orders on ophthalmology-related hospital admissions and emergency department (ED) presentations, during 2020 in Victoria, Australia. Methods Analysis was performed on Victorian statewide data from the Victorian Emergency Minimum Dataset (VEMD) and Victorian Admitted Episodes Dataset (VAED), between 1 January 2018 and 31 October 2020. Numbers of presentations and admissions for key ophthalmic conditions were stratified by age, socioeconomic status, location (metropolitan versus rural), and triage category. From the observations occurring in the pre-pandemic period (January 2018 to March 2020), a linear regression prediction model was built for each diagnosis which predicted what the presentation number in the COVID-19 period would have been if the pandemic had not occurred. Results Based on pre-COVID-19 trends, the largest decreases in expected admissions were for glaucoma (32.9%) and retinal breaks and detachments (21.2%). For the ED data, the most apparent changes were: an increase in presentations for foreign bodies (22.6%); a decrease in retinal detachments (35.5%); and a decrease in keratitis (18.4%) relative to predictions. Conclusions Hospital admissions decreased and patterns of ED attendances changed during lockdown. The findings suggest the need for the following: increased safety messaging to avoid eye injuries around the home; improved pathways for safe and rapid triaging of eye conditions in the community to ensure effective use of ED resources; and messaging to ensure that people do not delay care when they notice signs of sight-threatening conditions such as retinal detachment.

Food safety knowledge, needed and trusted information of pork consumers in different retail types in Northern Vietnam

IntroductionFood safety is an important public health concern globally. Risk communication is one of crucial element to manage food safety. While current food safety studies have focused on contamination of hazards or risk factors, limited research exists on consumer concerns, knowledge and perception about the actual risk food poses to their health. This study aimed to assess and compare the knowledge and perceptions regarding food safety, and the information needed and trusted by pork consumers in Northern Vietnam.MethodsA total of 225 consumers recruited from three different market types: modern urban, traditional urban and traditional rural, were interviewed using a questionnaire between November to December 2019.ResultsThe majority of participants (81.8%) were female and consumers interviewed at modern urban retail were younger than those interviewed at traditional retail settings (p < 0.01). Sixty-five percent of participants across the three retail types agreed that microbes were the most common hazards which can make them sick, but the adverse health effect due to chemical hazards was ranked higher than that of biological hazards. Most participants often received food safety information that was about animal diseases (such as African swine fever most recently), chemical contamination and the unknown origin of food rather than about food poisoning and measures to prevent it. Food safety messages from television and professional experts were the most trusted sources and consumer preference was for information about the origin of food (traceability) and how to choose safe food. Participants were willing to receive food safety information daily to weekly. A lack of perception and awareness about animal welfare related to pig farming or slaughtering was reported by most respondents (84.3%).DiscussionThese findings provide insight on Vietnamese consumer knowledge gaps, information demand and communication channels for food safety, so that risk communicators and managers can implement better food safety awareness campaigns and communication to consumers.

Blockchain-based decentralized data dissemination scheme in smart transportation

Data dissemination of safety messages in smart transportation allows vehicles to broadcast safety-related information about their surroundings to other vehicles within their proximity for early warnings of endangering events. Safety can only be achieved if the data transmitted are reliable. However, this may violate the privacy of a vehicle. At the same time, malicious or defective vehicles should be held accountable when misbehavior occurs. Utilizing blockchain technology, we propose a secure data dissemination scheme for smart transportation that solves the conflicting security requirements of reliability, privacy and accountability simultaneously, which provides a desirable level of security through its decentralized system. The analysis evaluation and simulation experiments signify our proposed scheme achieves security and performance efficiency, robust against adversarial attacks and practical for real world deployment.

Liver Transplant Recipients Speak Out on Public Awareness and Education Surrounding Alcohol-Related Health Effects: A Survey Study.

Compared to other recreational substances in Canada, alcohol consumption incurs the highest healthcare costs. Liver transplant recipients are unique stakeholders as members of the general public with lived experiences of liver disease. We sought to explore their perspectives on the current state of public education on alcohol-related health effects. The most recent 400 liver transplant recipients at Vancouver General Hospital, Canada, were invited to participate in an anonymous online survey on alcohol-related health effects by mail, email, and phone. Of 372 contacted patients, 212 (57%) completed the survey. Most patients were between 60-79 years, 63% were male, and 69% were Caucasian. The most common liver conditions leading to transplant were viral hepatitis (33%), alcohol-related liver disease (16%), autoimmune liver disease (14%), and non-alcoholic fatty liver disease (15%). Most patients knew that alcohol leads to liver failure (85%), but fewer knew about alcohol leading to cancer (54%), heart disease (50%), and damage to other organs (58%). Most common sources of information included public media (61%), family and friends (52%), and physicians (49%), with narrative comments about learning of alcohol-related health effects after liver diagnosis. Most patients believed that public health education at a middle/high school level would have long-term efficacy (72%) compared to health warning labels (33%) and safety messaging in commercials (39%). Current public education was felt to be adequate by only 20% of patients and 73% of patients supported health warning labels. Liver transplant patients reported a high, but not universal, awareness of alcohol-related health effects. A majority thought that current public health efforts were inadequate; it is critical to implement public health interventions to ensure consumers are able to make an informed decision on alcohol consumption.

SDN-enabled vehicular networks: Theory and practice within platooning applications

With the recent developments of communication technologies surrounding vehicles, we witness the simultaneous availability of multiple onboard communication interfaces on vehicles. While most of the current interfaces already include Bluetooth, WiFi, and LTE, they are augmented further by IEEE 802.11p and the 5G interfaces, which will serve for safety, maintenance, and infotainment applications. However, dynamic management of interfaces depending on application becomes a significant issue that can be best addressed by Software Defined Networking (SDN) capabilities. While SDN-based vehicular networks have been promoted previously, none of these works deal with practical challenges. In this paper, we propose and develop a practical framework that realizes SDN-based vehicular networks for a wide range of applications. Through this framework, we demonstrate a truck platooning application as a use case in which the two truck platoons strive to merge and establish connectivity. The route from source vehicle (i.e., Platoon Leader A) to destination (i.e., Platoon Leader B) is computed with the help of the SDN Controller to transmit the Beacon Safety Messages through Road Side Units (RSUs) at the MAC layer without relying on IP for proper platooning operations. The results show the efficiency of the SDN-based approach compared to the traditional routing approaches.

Efficient Cryptographic Hardware for Safety Message Verification in Internet of Connected Vehicles

An important security requirement in automotive networks is to authenticate, sign, and verify thousands of short messages per second by each vehicle. This requirement mandates the use of a high speed Elliptic Curve Cryptography (ECC) hardware. The Residue Number Systems (RNS) provide a natural parallelism and carry-free operations that could speed-up long integer arithmetics of cryptographic algorithms. In this article, we propose a high-speed RNS Montgomery modular reduction units with parallel computing to reduce the latency of the field modular operations. We propose a fully RNS-based ECC scalar multiplication co-processor for NIST-P256r1 and Brainpool256r1 standard curves and improved the scalar multiplication speed using NAF and DBC numbering systems. Compared to the literature, our scheme provides faster computation without compromising the security level. The performance of our fully RNS-ECC point multiplication meets the requirements of the automotive industry.

Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest

Accurate crash frequency prediction is critical for proactive safety management. The emerging connected vehicles technology provides us with a wealth of vehicular motion data, which enables a better connection between crash frequency and driving behaviors. However, appropriately dealing with the spatial dependence of crash frequency and multitudinous driving features has been a difficult but critical challenge in the prediction process. To this end, this study aims to investigate a new Artificial Intelligence technique called Geographical Random Forest (GRF) that can address spatial heterogeneity and retain all potential predictors. By harnessing more than 2.2 billion high-resolution connected vehicle Basic Safety Message (BSM) observations from the Safety Pilot Model Deployment in Ann Arbor, MI, 30 indicators of driving volatility are extracted, including speed, longitudinal and lateral acceleration, and yaw rate. The developed GRF was implemented to predict rear-end crash frequency at intersections. The results show that: 1) rear-end crashes are more likely to happen at intersections connecting minor roads compared to major roads; 2) a higher number of hard acceleration and deceleration events beyond two standard deviations in the longitudinal direction is a leading indicator of rear-end crashes; 3) the optimal GRF significantly outperforms Global Random Forest, with a 9% lower test error and a substantially better fit; and 4) geographical visualization of variable importance highlights the presence of spatial non-stationarity. The proposed framework can proactively identify at-risk intersections and alert drivers when leading indicators of driving volatility tend to worsen.

Field testing anti-speeding messages

PurposeDetermine whether anti-speeding messages displayed on roadside variable message signage (VMS) influence drivers’ speed choice selections. MethodSpeed detection tubes were installed across a single carriageway 60 km/h limit road section at positions prior to, immediately after, and at a longer distance from VMS display of anti-speeding messages during study Week2. Bi-directional vehicle speed data were collected continuously during the week prior to VMS installation (Week1), throughout the week that the anti-speeding messages were displayed (Week2), and a post-display week (Week3). ResultsOf six separately measured locations, Week2 southbound mean speeds (facing signage) and percent of drivers/riders exceeding the signed speed limit were consistently below those recorded during Week1 for all time periods. Aggregated Week3 (post-VMS) southbound data for all time periods, showed consistent patterns for mean speed and percent of drivers exceeding the signed speed limit, being higher than in Week2 (VMS displayed) but lower than during Week1 (pre-VMS). DiscussionCompared with Week1, messages influenced aggregate driver speed selection during Week2, with a residual positive effect (slower speeds) in Week3. While all three messages had positive effects, differences occurred in relative effectiveness between daytime (school and non-school hours) and night-time periods. Separately disaggregated data revealed differential effects for the three messages. ConclusionsFindings demonstrated the value of implementing theoretically informed message content and provided evidence for the impact that roadside road safety messaging can have on driver speed selection.

Crash characteristics for classic/historic vehicles and comparisons to newer vehicles

Introduction: Older vehicles, commonly referred to as “classic,” “vintage,” or “historic” vehicles (CVH), share the roadways with newer vehicles. Older vehicles lacking safety systems likely come with an increased risk of fatality, however there is no study examining the typical conditions for crashes involving CVH. Method: This study utilized information from crashes occurring in 2012 to 2019 to estimate fatal crash rates for vehicles grouped by model year deciles. Data from crashes documented in the National Highway Traffic Safety Administration’s (NHTSA) FARS and GES/CRSS data sets were utilized to examine roadway, temporal, and crash types for passenger vehicles produced in 1970 or earlier (CVH). Results: These data show CVH crashes are rare (<1% of crashes), but carry a relative risk of fatality from 6.70 (95th CI: 5.44–8.26) for impacts with other vehicles, which was the most common crash, to 9.53 (7.28–12.47) for rollovers. Most crashes occurred in dry weather, typically during summer, in rural areas, most frequently on two lane roads, and in areas with speed limits between 30 and 55 mph. Factors associated with fatality for occupants in CVH included alcohol use, lack of seat belt use, and older age. Conclusions and Practical Applications: Crashes involving a CVH are a rare event but have catastrophic consequences when they do occur. Regulations that limit driving to daylight hours may lower the risk of crash involvement, and safety messaging to promote belt use and sober driving may also help. Additionally, as new “smart” vehicles are developed, engineers should keep in mind that older vehicles remain on the roadway. New driving technologies will need to safely interact with these older, less safe vehicles.

Incorporating driving volatility measures in safety performance functions: Improving safety at signalized intersections

About 40 percent of motor vehicle crashes in the US are related to intersections. To deal with such crashes, Safety Performance Functions (SPFs) are vital elements of the predictive methods used in the Highway Safety Manual. The predictions of crash frequencies and potential reductions due to countermeasures are based on exposure and geometric variables. However, the role of driving behavior factors, e.g., hard accelerations and declarations at intersections, which can lead to crashes, are not explicitly treated in SPFs. One way to capture driving behavior is to harness connected vehicle data and quantify performance at intersections in terms of driving volatility measures, i.e., rapid changes in speed and acceleration. According to recent studies, driving volatility is typically associated with higher risk and safety-critical events and can serve as a surrogate for driving behavior. This study incorporates driving volatility measures in the development of SPFs for four-leg signalized intersections. The Safety Pilot Model Deployment (SPMD) data containing over 125 million Basic Safety Messages generated by over 2,800 connected vehicles are harnessed and linked with the crash, traffic, and geometric data belonging to 102 signalized intersections in Ann Arbor, Michigan. The results show that including driving volatility measures in SPFs can reduce model bias and significantly enhances the models' goodness-of-fit and predictive performance. Technically, the best results were obtained by applying Bayesian hierarchical Negative Binomial Models, which account for spatial correlation between signalized intersections. The results of this study have implications for practitioners and transportation agencies about incorporating driving behavior factors in the development of SPFs for greater accuracy and measures that can potentially reduce volatile driving.

Multi-BSM: An Anomaly Detection and Position Falsification Attack Mitigation Approach in Connected Vehicles

With the dawn of the emerging technologies in the field of vehicular environment, connected vehicles are advancing at a rapid speed. The advancement of such technologies helps people daily, whether it is to reach from one place to another, avoid traffic, or prevent any hazardous incident from occurring. Safety is one of the main concerns regarding the vehicular environment when it comes to developing applications for connected vehicles. Connected vehicles depend on messages known as basic safety messages (BSMs) that are repeatedly broadcast in their communication range in order to obtain information regarding their surroundings. Different kinds of attacks can be initiated by a vehicle in the network with malicious intent by inserting false information in these messages, e.g., speed, direction, and position. This paper focuses on the position falsification attacks that can be carried out in the vehicular environment and be avoided using the multi-BSM approach. Multi-BSM uses consecutive multiple BSMs with different parameters to detect and warn other vehicles about position falsification attacks. Multi-BSM is compared to other anomaly detection algorithms and evaluated with rigorous simulations. Multi-BSM shows a high level of anomaly detection, even in high vehicle density, with up to 97% accuracy rate compared to the respective algorithms.

A New Transit Safety Narrative

Public transportation is, overall, a relatively safe (low crash risk) and secure (low crime risk) transport mode. Transit travel has about one-tenth the traffic casualty (injury or death) rate as automobile travel, and residents of transit-oriented communities have about one-fifth the per capita crash casualty rate as in automobile-oriented communities. Transit also tends to have lower overall crime rates than automobile travel, and transit improvements can help reduce overall crime risk by improving surveillance and economic opportunities for at-risk populations. Despite its relative safety and security, many people consider transit travel dangerous and are reluctant to use it or support service expansions in their communities. Various factors contribute to this excessive fear, including the nature of transit travel, heavy media coverage of transit-related crashes and crimes, and conventional traffic safety messages that emphasize danger rather than safety. Transit agencies can help create a new transit safety narrative by better communicating transit’s overall safety and security impacts and providing better guidance concerning how users and communities can enhance transit safety and security.

An adaptive and cooperative MAC protocol for safety applications in cognitive radio enabled vehicular Ad-hoc networks

Rapid broadcast of safety message (sm) is critical for real-time applications in cognitive radio vehicular ad hoc networks (CR-VANETs). The arrival of primary users (PU) and the relative unpredictability of traffic emerge as network bottleneck constraints, resulting in unreliable broadcast services. The requirement is for a Medium Access Control (MAC) protocol that allows for fair contention, is adaptive, and includes a makeup strategy for rebroadcasting failed transmissions. There are intricate tradeoff optimisation relationships in which a value for the contention window that is inadequate will not result in optimal network performance. In this paper, we develop a dynamic contention window backoff mechanism using Karush–Kuhn–Tucker (KKT) conditions that enhances network performance by modifying the backoff time according to traffic density. Then we amalgamate this algorithm with a cooperative makeup strategy to design a novel adaptive and cooperative MAC protocol that is operable in a dynamic CR-VANET paradigm (ACCRV-MAC). A Markov chain decision model characterises the protocol, and Network Simulator -2 analyses various performance parameters. The study reveals that ACCRV-MAC improves throughput by 38.3% and reduces network latency by 49% compared to existing MAC protocols.

Hybrid and Hierarchical Aggregation-Verification Scheme for VANET

To deal with the security and privacy issues in vehicular ad hoc network (VANET), digital signature based on public key infrastructure (PKI) is recognized as being the most mature and popular approach. However, existing secure and privacy-preserving schemes for vehicular communications face some challenges, e.g., fast verification of signatures and certificates, reducing the storage/transmission overheads, avoiding the dependence on ideal tamper-proof devices. In this paper, we propose a hybrid and hierarchical aggregation-verification scheme for efficient verification of certificates and signatures on safety messages in VANET. In our scheme, short-term anonymous certificates and aggregate signatures are employed to guarantee the security and privacy of the VANET system. A novel hybrid aggregation-verification technique is proposed to firstly aggregate the signatures in different certificates and signatures on safety messages into fixed length aggregate signature and then verify the aggregate signature with very short delay. To the best of our knowledge, this paper achieves signature aggregation and verification of such kind for the first time. Further, our scheme also enables hierarchical aggregation-verification of certificates and signatures in VANET.