scholarly journals PERPENDICULAR TURNING SOLAR TRACKER ANTI-COLLISION CAR

2021 ◽  
Vol 5 (9) ◽  
Author(s):  
Sujash Dhole ◽  
Satyam Mehrotra
Keyword(s):  
Social Networking ◽  
Fuel Economy ◽  
Adaptive Cruise Control ◽  
Azimuth Angle ◽  
Cruise Control ◽  
Hard Part ◽  
Driving Skills ◽  
Collision Mitigation ◽  
Solar Tracker ◽  
Turning Radius

"We could definitely make a flying car - but that's not the hard part. The hard part is, how do you make a flying car that is super safe and quiet?” - ELON MUSK While safety, reliability, fuel economy, and low running costs put them at the top of the list of what people consider to be the 'most important' in a car, more than a third (36%) of those tested online rank with the latest driving skills in the same fields. Driving technology includes steering or parking assist, adaptive cruise control, and wireless entry or ignition. More than a quarter (28%) of people online also account for having the latest passenger technology, which includes audio or video streaming and social networking, as 'most important' to them. Our team has developed a vehicle archetype which is incorporated of Azimuth Angle, trimming off the turning radius and anti-collision mitigation system like concepts with a single touch button. The underlying concept of the smart car is to free the driver from many of the mundane tasks associated with driving, making the act of driving more pleasant.

Mobility and Energy Consumption Impacts of Cooperative Adaptive Cruise Control Vehicle Strings on Freeway Corridors

2020 ◽  
Vol 2674 (9) ◽  
pp. 111-123
Author(s):  
Hao Liu ◽  
Xiao-Yun Lu ◽  
Steven E. Shladover
Keyword(s):  
Energy Consumption ◽  
Fuel Economy ◽  
Adaptive Cruise Control ◽  
Baseline Scenario ◽  
Vehicle Speed ◽  
Market Penetration ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control ◽  
Freeway Corridors ◽  
The Impact

Cooperative adaptive cruise control (CACC) vehicle string operations have the potential to improve significantly the mobility and energy consumption performance of congested freeway corridors. This study examines the impact of CACC string operations on vehicle speed and fuel economy on the 13-mi SR-99 corridor, near Sacramento, CA. It extends the existing body of knowledge by performing a multi-scenario simulation analysis of the freeway corridor. A simulation study evaluated the performance of the corridor under various CACC market penetration scenarios and traffic demand inputs. The CACC string operation was also analyzed when vehicle awareness device (VAD) and CACC managed lane (ML) strategies were implemented. The case study revealed that the average vehicle speed increased by 70% when the CACC market penetration increased from 0% to 100%. The highest average fuel economy, expressed in miles per gallon (mpg), was achieved under the 50% CACC scenario where mpg was 27. This was 10% higher than the baseline scenario. However, when the CACC market penetration was 50% or higher, the vehicle fuel efficiency only had minor increases. When CACC market penetration reached 100%, the corridor allowed 30% more traffic to enter the network without experiencing reduced average speed. Results also indicate that the VAD strategy increased the speed by 8% when the CACC market penetration was 20% or 40%, while there was a minor decrease in mpg. The ML strategy decreased the corridor performance when implemented alone.

Evaluation and Testing of Driver-Assistive Truck Platooning: Phase 2 Final Results

2017 ◽  
Vol 2615 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Richard Bishop ◽  
David Bevly ◽  
Luke Humphreys ◽  
Stephen Boyd ◽  
Daniel Murray
Keyword(s):  
Fuel Economy ◽  
Short Range ◽  
Adaptive Cruise Control ◽  
Phase 1 ◽  
Phase 2 ◽  
Cruise Control ◽  
Dedicated Short Range Communications ◽  
Cooperative Adaptive Cruise Control ◽  
Transportation Research ◽  
The Impact

Phase 2 final results are described for the FHWA Exploratory Advanced Research project titled Heavy Truck Cooperative Adaptive Cruise Control: Evaluation, Testing, and Stakeholder Engagement for Near Term Deployment, which evaluates the commercial feasibility of driver-assistive truck platooning (DATP). The project was led by Auburn University, in partnership with Peloton Technology, Peterbilt Trucks, Meritor WABCO, and the American Transportation Research Institute. DATP is a form of cooperative adaptive cruise control for heavy trucks (two-truck platoons). It takes advantage of the increasing maturity of vehicle-to-vehicle (V2V) communications (and the expected widespread deployment of V2V connectivity based on dedicated short-range communications over the next decade) to improve freight efficiency, fleet efficiency, safety, and highway mobility as well as reduce emissions. Notably, truck fleets can implement DATP regardless of the regulatory timeline for dedicated short-range communications. The Phase 2 analysis built on Phase 1 and included a testing program of a DATP prototype (with detailed SAE Type 2 fuel economy testing), wireless communications optimization, traffic modeling to understand the impact on roadways at various levels of market penetration, and additional analysis of methods to find DATP partners as well as aerodynamic simulations to understand drag on the vehicles. Detailed analysis of the fuel economy testing data is provided.

Influence of Speed Forecasting on the Performance of Ecological Adaptive Cruise Control

2019 ◽  
Author(s):  
Eunjeong Hyeon ◽  
Youngki Kim ◽  
Niket Prakash ◽  
Anna G. Stefanopoulou
Keyword(s):  
Fuel Economy ◽  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Autonomous Vehicle ◽  
Cruise Control ◽  
Prediction Horizon ◽  
The Future ◽  
V2v Communications ◽  
Urban Conditions ◽  
Lead Vehicle

Abstract In congested urban conditions, the fuel economy of a vehicle can be highly affected by traffic flow and particularly, the immediately preceding (lead) vehicle. Thus, estimating the future trajectories of the lead vehicle is essential to optimize the following vehicle’s maneuvers for its fuel economy. This paper investigates the influence of speed forecasting on the performance of an ecological adaptive cruise control (eco-ACC) strategy for connected autonomous vehicles. The real-time speed predictor proposed in [1] is applied to forecast the future speed profiles of the lead vehicle over a short prediction horizon. Under the assumption that vehicle-to-vehicle (V2V) communications are available, V2V information from multiple lead vehicles is utilized in the prediction process. Eco-ACC is formulated in a model predictive control (MPC) framework to control the connected autonomous vehicle. The influence of the state prediction to the performance of eco-ACC in terms of fuel economy and acceleration is evaluated with different number of connected vehicles.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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