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Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

India contributed to 11% of the global road accidents and was ranked 1st among road deaths according to the latest World Health Organization (WHO) report 2018. Indian National Highways (NH) is a meagre 5% of the country’s road network but accounts for 55% of the road accidents and 61% of the road deaths. Majority of the freight traffic is ferried by Commercial Vehicles (CV) or trucks along these highways and this in turn increases the probability of them being involved in a road accident. The country’s economy is forecasted to thrive in the coming years and hence the requirement of CVs is aligned to international categorisation in the supply chain and shall play a pivotal role. In the year 2019, 13,532 road deaths were associated with CV occupants. The trucking industry is an unorganized sector wherein the illegal overloading of vehicles and over-the-limit driving hours pose a serious threat to road users.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

India witnessed 151,113 road deaths in the year 2019 and this alarming number is due to increased urbanization, motorization and per capita income. India is home to the 2nd largest road network in the world and accounts for the highest number of road deaths globally. Curbing the menace of road accidents requires tactical road safety policies and their effective implementation. The meagre availability of factual data regarding socio-economic loss due to road accidents is proving to be a hindrance to the ideation and implementation of the policies. The Planning Commission estimated the social costs of road accidents to be 7.9 billion $ in 1999/2000 which was roughly 3% of the country’s GDP and this value was revised to 14.3 billion $ in 2011. Absence of data regarding the loss due to road accidents in the recent times, has been a motivating factor to estimate the socio economic loss due to accidents on Indian roads.

Pedestrian crashes are a major safety concern worldwide, especially in India. About one of every ten traffic-related fatalities in the country is a pedestrian. In 2016 nearly 15,800 pedestrians were killed in India. They were mainly exposed to risk when crossing and walking on the road in urban and rural areas. The aim of the study was to understand the pedestrian behavior on the road and to identify characteristics of pedestrian crashes in India. Many unique behavior was observed like pedestrian crossed half way and stopped in middle of road. Nearly 10% of pedestrians are fatal each year involving in ~5% of overall accidents in India, This study revels every second pedestrian accident occurred while walking and crossing the road straight.

India has one of the highest growth rates of individual mobility in the world, as well as one of the largest numbers of road casualties. Modern active safety systems are slowly becoming established in the Indian passenger car market. The intension of this study is to investigate the effectiveness of the car safety feature Electronic Stability Control (ESC) for India. The Indian accidents has to be analysed to identify the reliable root cause. For this purpose, passenger car Loss of Control accidents were investigated in more detail with the aim of estimating the safety potential of ESC for India. A methodology is developed to extrapolate the in-depth accident database of Road Accident Sampling System for India (RASSI) to the entire accident situation in India. Loss of Control accidents are analysed with regard to their root causes, crash consequences and contributing factors.

The official Indian accident statistics show that the number of road accidents and fatalities are one of the highest worldwide. These official statistics provide important facts about the current accident situation. It is suspected that for various reasons not all accidents are reported to the official statistic. This study estimates the degree of underreporting of traffic accidents with casualties in India. In order to get a national overview of the traffic accident situation it is necessary to improve the knowledge about underreported accidents. Therefore, the in-depth accident database of “Road Accident Sampling System India” (RASSI) was analyzed [1]. This project is organized by a consortium that has collected traffic accidents scientifically in four different regions since 2011 on the spot which have been reported either by police or by local hospitals and own patrol by RASSI engineers.

The Side View Assist is the World’s first rider assistance system for two-wheelers. This is a Blind Spot Warning system, which uses four ultrasonic sensors to monitor the surrounding of the rider. Whenever there is a vehicle (i.e. a car, truck, or another motorbike) in the rider’s blind spot, the technology warns the rider with an optical signal close to the mirror. This will allow the rider to avoid a collision when changing lanes. In the current vehicle application, Side View Assist is active at speeds ranging from 25 to 80 kilometers per hour and supports riders whenever the difference in relative speed to other road users is small. The system helps to improve safety especially in cities, where heavy traffic makes it necessary to change lanes more often. Originally such systems have been developed for cars and different system solutions for cars have been in serial production for several years. The challenge was to adapt these systems so they would work for two-wheelers as well.

In the low-cost segment for 2-Wheelers legislative, economic and ecologic considerations necessitate a reduction of the emissions and further improvement in fuel consumption. To reach these targets, the commonly used carburetors are being replaced by engine management systems (EMS). One option to provide these systems for acceptable and attractive system costs is to save a sensor device and to substitute its measure by an estimation value. In many motorcycles the rotor of the vehicle's alternator is rigidly attached to the crankshaft. Therefore, the voltage and current signals of the alternator contain information about the engine's speed, which can be retrieved by evaluating these electric signals. After further processing of this information inside the electronic control unit (ECU), the absolute crankshaft position can be obtained. A high-resolution speed signal without mechanical distortions like tooth errors is gained, whose signal quality equals the one of a common speed sensor.

On the way to automated driving, the installation rate of surround sensing systems will rapidly increase in the upcoming years. The respective technical progress in the areas of driver assistance and active safety leads to a numerous and valuable information and signals to be used prior to, during and even after an accident. Car makers and suppliers can make use of this new situation and develop integrated safety functions to further reduce the number of injured and even deaths in car accidents. Nevertheless, the base occupant safety remains the core of this integrated safety system in order to ensure at least a state-of-the-art protection even in vehicles including partial, high or full automation. Current networked safety systems comprehend a point-to-point connection between single components of active and safety systems. The optimal integration requires a much deeper and holistic approach.

This paper presents an overview of the evolution & revolution of automotive E/E architectures and how we at Bosch, envision the technology in the future. It provides information on the bottlenecks for current E/E architectures and drivers for their evolution. Functionalities such as automated driving, connectivity and cyber-security have gained increasing importance over the past few years. The importance of these functionalities will continue to grow as these cutting-edge technologies mature and market acceptance increases. Implementation of these functionalities in mainstream vehicles will demand a paradigm shift in E/E architectures with respect to in-vehicle communication networks, power networks, connectivity, safety and security. This paper expounds on these points at a system level.

Motorized two wheelers, also known as powered two wheelers (PTW) are the most common mode of transportation in India. Around one in four deaths that occurred on the roads in India in 2012 involved a motorcyclist, according to Ministry of Road Transport and Highways. This constitutes the highest contributor for fatal accidents in India [1]. The European Transport Safety Council (ETSC) analysis shows the risk of a motorcyclist having a fatal accident is 20 times greater than for a car driver travelling the same route [2]. An investigation conducted by Bosch looked at the accident database of Road Accident Sampling System for India (RASSI). This investigation revealed interesting facts about the Indian motorcycle accident situation, such as root causes of powered two wheeler collisions and riders behaviour including their braking patterns during the pre-crash phase of the accident.

In the year of 2012 in India the total number of accidents with injuries is registered by Ministry of Road Transport and Highway with 490,383 out of which injured people are 509,667 and fatalities are 138,258 [1]. Nearly 17% of the fatalities are occupants of passenger cars which constitute the second highest contributor for fatal accidents in India [1]. In order to understand the root causes for car accidents in India, Bosch accident research carried out a study based on in-depth accidents collected in India. Apart from other accident contributing factors e.g. infrastructure the driver behaviour and his actions few milliseconds just prior to the crash is an extremely important and a key valuable data for the understanding of accident causation. Further on it supports also the development of modern automotive safety functions. Hence this research was undertaken to evaluate the benefit of the state-of-the art vehicle safety systems known as Antilock Braking System (ABS).

Current exhaust gas emission regulations can only be well adhered to through optimal interplay of combustion engine and exhaust gas after-treatment systems. Combining a modern diesel engine with several exhaust gas after-treatment components (DPF, catalytic converters) leads to extremely complex drive systems, with very complex and technically demanding control systems. Current engine ECUs (Electronic Control Unit) have hundreds of functions with thousands of parameters that can be adapted to keep the exhaust gas emissions within the given limits. Each of these functions has to be calibrated and tested in accordance with the rest of the ECU software. To date this task has been performed mostly on engine test benches or in Hardware-in-the-Loop (HiL) setups. In this paper, a Software-in-the-Loop (SiL) approach, consisting of an engine model and an exhaust gas treatment (EGT) model, coupled with software from a real diesel engine ECU, will be described in detail.

The 2011 Report of Ministry of Road Transport and Highways, Government of India states that the total accidents with injuries is estimated about 497, 686 out of which the injuries are 511, 394 and fatalities are 142, 485, an average of one fatality per 3.5 [1]. Social losses on account of these crashes are estimated at over Rupees 100 000 Crores annually or 3% of our Gross Domestic Product (GDP) [2]. The irony is that these causalities are rising at 5.9 % annually. India accounts for 10% of the global road crash fatalities. Therefore traffic safety became very important in India. In order to understand the root causes of accidents data is needed in more detail which could be analyzed and points out the major issues to find solutions to stop this trend. Besides vehicle safety, infrastructure related issues and education skills can be derived out of accident data. Official statistics regarding accidents in India are available in national and state wise reports.

Today, knock control is part of standard automotive engine management systems. The structure-borne noise of the knock sensor signal is evaluated in the electronic control unit (ECU). In case of knocking combustions the ignition angle is first retarded and then subsequently advanced again. The small-sized combustion chamber of small two-wheeler engines, uncritical compression ratios and strong enrichment decrease the knock tendency. Nevertheless, knock control can effectuate higher performance, lower fuel consumption, compliance with lower legally demanded emission limits, and the possibility of using different fuel qualities. The Knock-Intensity-Detector 2 (KID2) and the Bosch knock control tool chain, based on many years of experience gained on automotive engines, provides an efficient calibration method that can also be used for two-wheeler engines. The raw signal of the structure-borne noise is used for signal analysis and simulation of different filter settings.

The increasing number of electronic control units (ECUs) in vehicles leads to more and more complex systems with a steadily growing demand for data exchange. This growth includes the number of bus participants, the amount of data and hence the data transfer rates. In addition, the trend towards car-to-x connectivity reinforces the need for new in-vehicle communication solutions. Since the early 1990s Controller Area Network (CAN) is the most widely used powertrain bus system. Since 2000 FlexRay is used in addition to CAN in the premium segment. For classic powertrain applications, the data transfer rates of these bus systems are sufficient; however the utilization is sometimes difficult and gateways are often required. For new applications like hybrid and electric vehicles and the next generation of external communication applications (e.g. telematics services) new concepts based on the existing bus systems or completely new solutions are needed.

“Safe Driving” is an essential world-wide automotive requirement. The demand for “Safe Driving” is particularly high in industrialized countries, but it is also growing in the fast-developing nations. However, the annual reduction of serious traffic injuries and fatalities is still too low and the target to halve the number of people killed in traffic in the European Union from 2001 to 2010 has not been met. Essential influences to close this gap include legislation, road traffic regulations and monitoring, technical improvement of vehicles including active and passive safety systems, the increase of the equipment rate for safety functions and the re-design of traffic infrastructure for safety reasons. During the last years several countries in Europe started to consider these aspects combined in an integrated and general traffic safety policy, i.e. “Vision Zero” in Sweden.

AUTOSAR (AUTomotive Open System ARchitecture) is a worldwide standard for automotive basic software in line with an architecture that eases exchange and transfer of application software components between platforms or companies. AUTOSAR provides the standardized architecture together with the specifications of the basics software along with the methodology for developing embedded control units for automotive applications. AUTOSAR matured over the last several years through intensive development, implementation and maintenance. Two main releases (R3.2 and R4.0) represent its current degree of maturity. AUTOSAR is driven by so called core partners: leading car manufacturers (BMW, Daimler, Ford, GM, PSA, Toyota, Volkswagen) together with the tier 1 suppliers Continental and Bosch. AUTOSAR in total has more than 150 companies (OEM, Tier X suppliers, SW and tool suppliers, and silicon suppliers) as members from all over the world.

With the development of start stop technology to improve fuel economy and to reduce carbon dioxide (CO2) emissions, the information of State of Charge (SOC) of the battery is highly desirable. Recent days the battery sensors are used in mid-segment and luxury automobiles that monitors the current, voltage and temperature of the battery and calculates the charge model and sends the information via CAN or LIN. These dedicated sensors are intended to perform various functions other than basic start stop. Hence these sensors are proven to be expensive for emerging market, which is intended to perform only basic start stop as the market is looking for a low cost solution. Bosch- India has developed and implemented a novel idea of bringing a low cost and reliable battery charge detection algorithm that can be realized within the Electronic Control Unit (ECU) without a dedicated sensor.