Acquiring high-quality origin–destination (OD) information for traffic in a geographic area is both time consuming and expensive while using conventional methods such as household surveys or roadside monitoring. These methods generally present only a snapshot of traffic situation at a certain point in time, and they are updated in time intervals of up to several years. A technique was developed that makes use of the global system for mobile communications (GSM) mobile phone network. Instead of monitoring the flow of vehicles in a transportation network, the flow of mobile phones in a cell-phone network is measured and correlated to traffic flow. This methodology is based on the fact that a mobile phone moving on a specific route always tends to change the base station nearly at the same position. For a first pilot study, a GSM network simulator has been designed, where network data can be simulated, which is then extracted from the phone network, correlated, processed mathematically and converted into an OD matrix. Primary results show that the method has great potential, and the results inferred are much more cost-effective than those generated with traditional techniques. This is due to the fact that no change has to be made in the GSM network, because the information that is needed can readily be extracted from the base station database, that is the entire infrastructure needed is already in place.

The new capabilities of autonomous cars can be used to mitigate to a large extent safety concerns and nuisance traditionally associated with double parking. In this paper double parking for autonomous cars is proposed as a new approach to temporarily increase parking capacity in locations in clear need for extra provision when best alternatives cannot be found. The basic requirements, operation, and procedures of the proposed solution are outlined. A curbside parking has been simulated implementing the suggested double parking operation and important advantages have been identified for drivers, the environment, and the city. Double parking can increase over 50% the parking capacity of a given area. Autonomous car owners would (at least) double their probabilities of finding parking compared to traditional drivers, saving cruising time and emissions. However, significant work and technological advances are still needed in order to make this feasible in the near future.

In recent times, electric vehicles (EV) are gaining a lot of attention as they run clean and are environment friendly. Recent advances in the applications of integrating control systems in automotive vehicles have made it practicable to accomplish improvement in vehicle's longitudinal and lateral dynamics. This paper deals with a brief overview of current state of art vehicle technologies like direct yaw moment control, traction control and side slip control of EV. There are various controller algorithms available in literature with different torque vectoring strategies. As EV can be precisely controlled because of quick in hub wheel motor response times, therefore various torque vectoring strategies can be comfortably used for enhancing vehicle dynamics. Moreover, by using four independent in-wheel motors, several types of motion controls can be performed. These motion controls are intensively researched by a comprehensive literature review with an aim to obtain desired vehicle handling characteristics.The motivation behind doing this study is to obtain a guideline for systematic development of control strategy. The control law development is discussed in three subsequent stages, namely, Supervisory control, Upper level control and Lower level control. The controller is to be designed and implemented for the torque management of the four independent electric traction motors of a FOX racing electric car.