A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> In this paper, we present a distributed approach to build a dynamic map in the context of VANets (Vehicular Ad hoc Networks). It is based on the principle of cooperative perception where vehicles work as a team in order to extend their field of view. Each vehicle is equipped with sensors allowing it to detect its environment and to build its map, denoted by local map. It receives messages from other vehicles containing mobile objects detected in their surroundings. The algorithm of distributed dynamic map builds a map of the dynamic environment including objects in the sensor's field of view as well as those sent by other vehicles. This algorithm is developed under the belief functions framework. The implementation of such an application is complex and needs many treatments: temporal and spatial alignment, object association, fusion of messages and data dissemination. This approach has been validated by simulation on scenario involving several vehicles in traffic situation. <s> BIB001 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> The Ko-PER (cooperative perception) research project aims at improvements of active traffic safety through cooperative perception systems. Within the project a prototype of a cooperative warning system was realized. This system provides early advisory warnings which are especially useful in critical situations with occluded conflict partners. The development process was accompanied by a series of driving simulator studies to determine both the potential to reduce traffic conflicts and important design characteristics of early advisory warning signals. The most important details of the prototype system's components inter-vehicle information-fusion and situation analysis are described and the achieved warning timings are compared to the results of the driving simulator studies. <s> BIB002 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> In this article, we investigate how cooperative perception gives the impact on decision making and planning of autonomous vehicles on the road. Cooperative perception is the exchange of local sensing information with other vehicles or infrastructures via wireless communications, by which the perception range can be considerably extended up to the boundary of connected vehicles. This augmented perception capability can provide oncoming traffic information beyond line-of-sight and field-of-view, which enables better control of both manned and unmanned vehicles. In this article, we first present an on-road sensing system to provide a see-through/lifted-seat/satellite view to drivers. Then, we investigate how the extended perception capability can contribute to situation awareness on the road. Finally, we provide methods for safer and smoother autonomous driving using the augmented situation awareness and perception capability. All introduced and proposed concepts are implemented and validated on autonomous vehicles. <s> BIB003 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> The advances in Information Technologies have led to more complex road safety applications. These systems provide multiple possibilities for improving road transport. The integrated system that this paper presents deals with two aspects that have been identified as key topics: safety and efficiency. To this end, the development and implementation of an integrated advanced driver assistance system (ADAS) for rural and intercity environments is proposed. The system focuses mainly on single-carriageways roads, given the complexity of these environments compared to motorways and the high number of severe and fatal accidents on them. The proposed system is based on advanced perception techniques, vehicle automation and communications between vehicles (V2V) and with the infrastructure (V2I). Sensor fusion architecture based on computer vision and laser scanner technologies are developed. It allows real time detection and classification of obstacles, and the identification of potential risks. The driver receives this information and some warnings generated by the system. In case, he does not react in a proper way, the vehicle could perform autonomous actions (both on speed control or steering maneuvers) to improve safety and/or efficiency. Furthermore, a multimodal V2V and V2I communication system, based on GeoNetworking, facilitates the flow of information between vehicles and assists in the detection and information broadcasting processes. All this, combined with vehicle positioning, detailed digital maps and advanced map-matching algorithms, establish the decision algorithms of different ADAS systems. The applications developed include: adaptive cruise control with consumption optimization, overtaking assistance system in single-carriageways roads that takes into account appropriate speed evolution and identifies most suitable road stretches for the maneuver; assistance system in intersections with speed control during approximation maneuvers, and collision avoidance system with the possibility of evasive maneuvers. To this end, mathematical vehicle dynamics models have been used to ensure the stability, and propulsion system models are used to establish efficient patterns, Artificial Intelligence and simulation are used for experimentation and evaluation of algorithms to be implemented in the control unit. Finally, the system is designed to warn the driver if a risk is detected and, if necessary, to take control of the vehicle. The system has been implemented on a passenger car and has been tested in specific scenarios on a test track with satisfactory results. Language: en <s> BIB004 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Abstract This paper describes a fully automated driving algorithm on complex urban roads with guaranteed safety. A serial-production sensor setup is modified as follows: Radar, LiDAR, vision, and GPS/map. The proposed algorithm consists of the following three steps: an environment representation, a safety driving envelope decision, and a motion optimization. An environment representation system consists of three main modules: object classification, vehicle/non-vehicle tracking and map/lane based localization. A motion planning modules derives an optimal motion as a function of time, from the environment representation results. A safety envelope decision module determines the complete driving corridor that leads to the destination while assigning all objects to either the left or right corridor bound. In the case of moving objects such as other traffic participants, their behaviors are anticipated in the near future. A motion optimization module uses the safety envelop as a constraint and computes a trajectory that the vehicle stays in its bounds. The vehicle control module feeds back the pose estimate of the localization module to guide the vehicle along the planned trajectory. The effectiveness of the proposed automated driving algorithm is evaluated via vehicle tests. Test results show the robust performance on an inner-city street scenario. <s> BIB005 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> The introduction of Vehicle-to-X (V2X) communication enhances the perception range of a vehicle significantly. The technology, however, is subjected to the network effect: a minimum number of communication partners need to be within range, in order for V2X applications to work. Taking current vehicle replacement rates on the market into account, the time of market introduction is critical, as early adopters are likely not to profit from the technology, whilst having to account for the development costs. This contribution picks up the concept of collective perception, in which vehicles share their information gathered by their local perception sensors about objects in their vicinity. This work extends our earlier research by introducing a new message format, the Environmental Perception Message (EPM) for exchanging sensor information. Additionally, a high-level data fusion framework is presented, which separates the fusion process of local sensor data and V2X information, along with the required coordinate transformations for representing another vehicle's sensor information in the recipient's reference frame. We also realized the introduced framework and message in two automated vehicles and provide a performance analysis in an obstacle avoidance scenario for these vehicles on a race track. Since the vehicles share their sensor data with each other, the resulting available reaction time for avoiding the obstacle on the track increases significantly. <s> BIB006 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> This paper introduces a multi-level cooperative scheme for autonomous vehicles, using the sensors equipped on-board and a communication scheme with the deployed infrastructures. The proposed model focuses on the communication elements, delving into the cooperative aspect between the network components. The first level of the proposed scheme is composed of a multi-sensor data fusion framework using the measurements obtained from the vehicle on-board sensors, in order to detect obstacles in front of the vehicle. The obstacle detection is based on a liner regression fusion rule, which combines the obtained features from several sensors. Once the decision is taken, the vehicle responds consequently using implicit coordination and bringing the network to an uncertain status. Hence, the second level consists on achieving a stable network by applying explicit coordination between the vehicles and the deployed infrastructures. The third level controls the entire network from a centralized perspective using long-range communication links. Using the knowledge obtained from the centralized network, optimization can be achieved using a coordination scheme based on communication. To finalize, the theoretical framework is simulated under realistic conditions obtaining promising results, in terms of obstacle avoidance and network coordination. <s> BIB007 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Abstract Driving environment perception technology is a key issue for driving assistance systems and autonomous vehicles. Driving environment information collection and information fusion and representation are two important contents of this technology. On-board sensors such as camera, radar, lidar, etc., are popularly used to collect relevant information. However, when using these on-board sensors, uncertainty arises from ignorance and errors, where ignorance is usually caused by vehicle occlusion, and errors is caused by imprecise pose estimation and noisy measurements. Increasing sensor number would decrease such uncertainty, but complexity and cost is also increased in this way. In this paper, we present a V2I (vehicle-infrastructure) based urban driving environment collection method achieved only by two sensors, i.e., a Road Side Unit camera (RSU camera) and vehicle GPS. RSU camera is used to extract lane marking information, including position and type, and vehicle position information. Vehicle GPS provide position information of vehicle. A credibility map is proposed as the compact representation of urban environment, and accept those information from RSU camera and vehicle GPS. In order to hand uncertainty caused by sensors, Dempster-Shafer theory is employed to estimate the credibility of each cell, fuse the credibility root in the information provided by RSU camera and vehicle GPS, and map onto the credibility map. The performance of this method has been validated with real-world urban traffic data. <s> BIB008 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> With cooperative intelligent transportation systems, vulnerable road users (VRU) safety can be enhanced by multiple means. On the one hand, perception systems are based on embedded sensors to protect VRUs. However, such systems may fail due to the sensors’ visibility conditions and imprecision. On the other hand, vehicle-to-pedestrian (V2P) communication can contribute to the VRU safety by allowing vehicles and pedestrians to exchange information. This solution is, however, largely affected by the reliability of the exchanged information, which most generally is the GPS data. Since perception and communication have complementary features, we can expect that a fusion between these two approaches can be a solution to the VRU safety. In this paper, we propose a cooperative system that combines the outputs of communication and perception. After introducing theoretical models of both individual approaches, we develop a probabilistic association between perception and V2P communication information by means of multi-hypothesis tracking. Experimental studies are conducted to demonstrate the applicability of this approach in real-world environments. Our results show that the cooperative VRU protection system can benefit of the redundancy coming from the perception and communication technologies both in line-of-sight (LOS) and non-LOS conditions. We establish that the performances of this system are influenced by the classification performances of the perception system and by the accuracy of the GPS positioning transmitted by the communication system. <s> BIB009 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Pedestrian detection has become one of the hottest topics in intelligent traffic system because of its potential applications in driver assistance and automatic driving. In this study, a fast pedestrian detection and dynamic tracking method within vehicle-to-vehicle (V2V) cooperative environment is proposed. A dynamic tracking-by-detection framework for real-time pedestrian detection is developed. First, a cascade classifiers, based on selected Haar-like features, is trained to detect pedestrian. Then, CamShift algorithm combined with extended Kalman filtering is used to pedestrian dynamic tracking. Finally, with the crowdsourcing detected information, a smartphone-based V2V cooperative warning system is developed to share useful detection results within blind spots. The experiment results show that the proposed method has a real-time and accurate performance, which can provide a reference for road traffic safety monitoring technology. <s> BIB010 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Abstract The automotive industry is changing from conventional driving into connected and later on autonomous driving. The fundamental principle of this alteration is communication and exchange of data between vehicles and other kind of traffic objects, for example traffic lights. The knowing about basic conditions from all traffic objects within a close proximity can ensure a more precise reaction of Advanced Driver Assistant Systems (ADAS). Thereby Vehicle-to-Vehicle (V2V) technology contributes to increase traffic safety. This paper describes an investigation of V2V communication based on commercial On-Board-Units (OBU). These units, integrated in two test-vehicles, transmit and receive data based on the IEEE 802.11p standard (ETSI ITS-G5). The messages include basic conditions like position, motion vector and vehicle configuration parameters. Those information ensure a relative positioning which is also implemented in the paper on hand. The calculations provide the prerequisites for additional autonomous vehicle system applications like autonomous braking or steering maneuver. To improve precision and reliability of ADAS, statements about integrity are inevitable. These can be achieved by a fusion of different sensor information. Therefore the paper also presents possibilities to ensure an accurate localization and object detection, regarding a Light Detection and Ranging (LiDAR) System (Velodyne VLP-16) and an Differential Global Positioning System (DGPS) approach. The interaction of communication, sensor fusion algorithms and integrity considerations form the basis for autonomous driving. <s> BIB011 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Multiple means have been proposed to enhance safety for vulnerable road users (VRUs), especially pedestrians. V2X communication, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P), and roadside sensor perception are two such approaches. V2X communication requires communication devices and is not applicable to VRUs not carrying such a device. On the other hand, for specific areas such as an intersection roadside sensors are getting installed and operable for surveillance purpose. So we investigate the cooperation of the two approaches at an intersection. A 79GHz millimeter radar is used as the roadside sensor to detect vehicles and pedestrians including those without V2X communication ability, while V2I/P2I (pedestrian-to-infrastructure) communication is utilized to assist the radar to recognize hidden vehicles and pedestrians blocked by buildings. In the paper, we first introduce our developed V2P communication and 79GHz radar systems, and then consider object identification and selection based on fusing perception data and communication data. As a new function we also investigate action prediction and collision prediction for pedestrians. Our system is experimented with field tests and the cooperation performance is verified. <s> BIB012 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> In the field of autonomous navigation, perception of the driving scene is one of the essential elements. Existing solutions combine on-board exteroceptive sensors, and are capable of understanding some of the near vehicle’s dynamic surrounding environment. Furthermore, the perception capability of each vehicle can be enhanced by wireless information sharing if vehicles in the neighborhood transmit pertinent information. The primary benefit of such approach is to enable and improve the performance-safety of cooperative autonomous driving. The introduction of such a vehicle-to-vehicle communication leads to think of the global architecture as a system of systems. In this work, we address the task of evidential occupancy grid fusion so that a given vehicle can refine and complete its occupancy grid with the help of grids received from other near vehicles. The communication channel is supposed to be ideal, noiseless with infinite capacity. We focus on the fusion framework itself, using the theory of belief functions for reasoning with uncertainties on the relative poses of the vehicles and on the exchanged sensor measurement data. We evaluate the fusion system with real data acquired on public roads, with two connected vehicles. <s> BIB013 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> The complete perception of the environment is an important prerequisite for realizing autonomous driving. However, due to the existence of obstructions and the limits of sensing range, perception ability of a single vehicle cannot meet the requirements of perception. In this paper, we attempt to expand the range of vehicle perception and eliminate blind areas by fusing multimedia based on vehicle network. Using a deep leaning method, we get a more in-depth understanding and extract critical information from vision system. We integrate multi-vehicle’s information into the ego-vehicle’s coordinate by merging unified bird-view maps, taking both graphic and semantic alignment as association. Furthermore, a transport protocol is designed to limit the information transmission amount. The experimental results on open data sets show that our approach can effectively fuse multimedia information in the multi-vehicle system, and improve the vehicle’s perception ability. <s> BIB014 </s> A Review of Research on Traffic Conflicts Based on Intelligent Vehicles <s> IV. RESEARCH ON TRAFFIC CONFLICT BASED ON INTELLIGENT VEHICLES PERCEPTION-COMMUNICATION TECHNOLOGY FUSION <s> Abstract In conjunction with automated vehicles, Inter-Vehicle Communication represents the next ‘big thing’ towards the vision of cooperative driving, where road participants share information about their planned behaviour and where hazardous situations are solved or avoided jointly. One prerequisite to fulfill this long-term goal is a common information base, where all road participants are fully aware of each other. The idea of collective perception contributes to this information base by sharing local sensor data with other road users. Whereas most related work focuses on the aspects of sensor data fusion, we focus on the implications of an ETSI ITS G5 based network for collective perception. We present and analyse different message formats and dissemination variants for sharing sensor data. Their usability is validated in two extensive microscopic simulation studies with different traffic densities and up to several hundred concurrent vehicles. In particular, implications caused by standardised Decentralized Congestion Control are assessed in a controlled environment. <s> BIB015
In the development stages of intelligent vehicles, it is inevitable that intelligent vehicles will mix with traditional cars and share the road with other participants. Research on traffic conflicts based on perception technology and communication technology has its own advantages and disadvantages. Therefore, the integration of these two technologies is a more reliable solution. Through advanced vehicle and road sensing equipment such as radar and video, real-time and high-precision perception of road traffic environment is realized. According to the communication protocol and data interaction standard, the communication between vehicle and vehicle, vehicle and road, vehicle and human, vehicle and road facilities are realized  . As shown in Fig. 10 , an example of conflict assessment model based on the intelligent vehicle perception-communication fusion is given. Some scholars include Calvo BIB007 proposed a cooperative scheme of vehicle sensor and vehicle communication. The vehicle sensor was used to detect the obstacles in front of the vehicle. The measured data was shared by workshop communication to enhance the perception ability, so as to avoid the obstacle or pedestrian. Further, Jiménez et al. BIB004 proposed a comprehensive collision avoidance system, which includes real-time detection and obstacle classification. Computer vision and three-dimensional laser scanner are utilized to identify, potential conflicts. The V2V and V2I communication is used to promote information flow between vehicles, assisting detection and information broadcasting. The two systems complement each other and improve road safety and driving efficiency. Zhao et al. BIB008 proposed a method of urban driving environment acquisition based on V2I, which integrates the information of RSU camera and vehicle-borne GPS. Vehicles send the location data provided by GPS to RSU through V2I communication. At the same time, RSU camera is used to extract and collect the information of moving vehicles, lane information and vehicle location information, which effectively solves the problem of vehicle congestion. Liu et al. BIB012 proposed a radar collaborative perception communication system based on V2I/P2I for intersection. Communication technology was used to expand the radar's action area and deal with obstacles. Vehicles and pedestrians were detected by radar, and their location information was sent to other vehicles or pedestrians. It is effective in target recognition, selection and collision prediction. Sensors can identify and track targets, but the reality will be blocked by other vehicles and infrastructure, resulting in perception information reduction. Camarda et al. BIB013 used the fusion framework of lidar and wireless communication technology to realize the urban scene representation. The uncertainties of vehicle attitude and the measured data of switched sensors are used to improve the vehicle perception. Merdrignac et al. BIB009 use the complementary features of perception and communication to solve the safety problems of vulnerable road users via the method of perception and communication fusion. Li et al. BIB010 applied vision and communication technology for pedestrian detection training. A cooperative early warning system based on smartphones is developed to achieve blind spot detection sharing. Kim et al. BIB005 generate real-time environment representation using information from on-board sensors and V2X communication, in order to achieve lane-level positioning, adjacent vehicle detection, static obstacles and safe driving area detection. Eckelmann et al. BIB011 uses high-resolution three-dimensional point cloud data provided by Velodyne VLP-16 lidar, and then locates traffic objects through V2X communication for target recognition and tracking. Xiao et al. BIB014 proposed a vehicle perception fusion framework based on V2V, vision and GPS. By fusing multimedia information of vision, GPS and digital map, the method of in-depth learning is used to deeply understand and extract the key information in the vision system, which significantly improves the vehicle perception ability and perception range, and eliminates most of the perception blind areas. Collaborative perception is to exchange local perception information with other vehicles or infrastructure through wireless communication. The local perception of vehicles is thus enhanced by using the received information about current traffic conditions. Through these methods, it is possible to fully perceive the driving environment in real-time. This enables the drivers to comprehensively and broadly recognize potential conflict situations, and also improves the situational awareness performance of intelligent vehicles, so as to better resolve conflicts and improve active traffic safety  , BIB003 . Using collaborative perception as a conflict solution, drivers can predict the traffic situation ahead and take measures, such as blind spot avoidance, safe lane change/overtaking, and smooth braking/acceleration. Compared with traditional remote sensors, it is also a more economical method. Zoghby et al. BIB001 built a dynamic environment map based on cooperative perception, including the targets in the sensor vision and the targets sent by other vehicles. Vehicle-borne sensors can detect and map the surrounding environment. At the same time, it receives the target information from other vehicles to expand the vision and reduce false alarms. Günther et al. BIB015 , BIB006 put forward the concept of collective perception, which means sharing local sensor data with other vehicles within the communication range. The feasibility of realizing group perception in V2X communication under different traffic densities is analyzed. The potential of collective perception for avoiding collision in complex situations is proved. Because vehicles share their sensor data with each other, the response time for drivers to avoid obstacles increases significantly. Seeliger et al. BIB002 constructed an advisory warning system. By providing early warning to drivers before conflicts occur, researches show that these warnings have great potential to reduce traffic conflicts, especially when traffic conflicts are difficult to predict and other road users are unaware of conflicts. As shown in Fig. 11 , some examples of collaborative perception in potential typical conflict scenarios are given. These examples are representative and versatile. Traffic conflict research based on perceptioncommunication fusion technology is mainly used in active vehicle safety. Intelligent vehicles use communication technology to obtain sensor data from other vehicles or road infrastructures. Through the time and space dimension, the vehicle's perception of traffic and environment is expanded. The surrounding environment information such as vehicle operation information, traffic control information, congestion prediction information, visual blind area and so on can be obtained in advance. It improves the system responds and is not easily affected by environmental factors. Moreover, more information can be used in vehicle control to reduce various threats in the driving processes.