Tag Archives: ai

EV, NEWS

Proton e.MAS Impianku: design an EV with AI, win a 3D-printed model

Proton New Energy Technology (PRO-NET) is inviting Malaysians to take part in the e.MAS Impianku design competition, which will run from 19 October to 30 November 2026.

The initiative gives participants an opportunity to share their ideas on the design, features, and technologies they would like to see in future electric vehicles (EVs).

Two competition categories are available: Open Category and University Student Category.

Open Category

This category is open to Malaysian residents aged 18 and above.

Eligible submissions will be showcased in a digital gallery for public voting from 5 to 13 December 2026.

The top 20 designs with the highest number of votes will be shortlisted for final judging.

A total of eight winners will receive the following prizes:

  • Three Grand Prize Winners: A 10-inch 3D-printed model based on their winning design.
  • Five Consolation Prize Winners: A miniature 3D model based on their respective designs.

Winners of the Open Category will be announced at an official PRO-NET event in January 2027.

University Student Category

This category is open to students aged 18 and above who are enrolled in recognised higher education institutions in Malaysia.

Unlike the Open Category, winners will be selected exclusively by a judging panel, with no public voting involved.

The top three winners will receive cash prizes as follows:

  • First Prize: RM1,000
  • Second Prize: RM600
  • Third Prize: RM400

In addition, 12 consolation prize winners will receive exclusive Proton e.MAS merchandise.

How to Participate

Participants must visit protonemasimpianku.com, select their preferred category, and use the sample AI prompts provided as guidance to create their design using any generative AI platform.

Completed designs must then be uploaded together with a fully completed entry form before 11:59 pm on 30 November 2026.

Participants may submit more than one design, but they may only enter one competition category. All submissions must be original works generated using AI and must comply with the competition’s terms and conditions.

The submitted designs are intended purely as creative concepts and do not represent confirmed Proton e.MAS production models.

NEWS

Pilot testing of AWAS using AI to detect speeding drivers on PLUS and KLK starting this June

Pilot testing of the Automatic Awareness Safety System (AWAS) using point-to-point methods will be implemented by June, reported Berita Harian.

This method will be used to detect drivers who exceed speed limits by measuring the duration and distance traveled, in addition to using artificial intelligence (AI) technology.

Initially, two highway locations will be selected for this pilot project: the route from Genting Sempah Tunnel to Gombak Rest Stop (KL-Karak Highway), and from Senawang Toll Plaza to Simpang Ampat Toll Plaza (North-South Highway).

The system will also be installed at locations where accidents frequently occur, such as the route from Menora Tunnel to Sungai Perak Rest Stop.

In an interview with Berita Harian, the Secretary-General of the Ministry of Transport (MOT), Datuk Jana Santhiran Muniayan, stated that the system can detect drivers who violate speed limits if they arrive at their destination quicker than the estimated time.

“This system, installed at toll plazas, will record travel time based on distance.

“For example, if a driver travels from Jalan Duta, Kuala Lumpur to Tanjung Malim, Perak, and arrives earlier than expected, the vehicle’s license plate will be detected and an automatic summons will be issued,” he said.

With the help of AI, this system can detect how long a driver stops at any location to extend their travel time to avoid detection.

He also mentioned that a company has been appointed to handle the proof-of-concept (POC) process without incurring financial impacts on the government.

Previously, Transport Minister Anthony Loke revealed that the AWAS camera system would be enhanced with the point-to-point method compared to the static method implemented earlier.

This is because the implementation of the AWAS cameras at present is seen as not achieving the goal of reducing vehicle speed and minimizing accident risks.

NEWS

Toyota and Stanford develop self-driving drift cars in the name of safety

Toyota Research Institute (TRI) and Stanford Engineering said they have successfully performed tandem drifts with two self-driving Toyota GR Supras.

For nearly seven years, both teams have collaborated on research to make driving safer. But what does autonomous tandem drifting has to do with safety?

According to TRI, by adding a second car drifting in tandem, the teams have now more closely simulated dynamic conditions where cars must respond quickly to other vehicles, pedestrians, and cyclists.

Both cars were programmed to perform tandem drifting using the latest tools in AI. Algorithms on the lead car were developed at TRI, while Stanford engineers developed those on the chase car.

TRI focused on developing robust and stable control mechanisms for the lead car, allowing it to make repeatable, safe lead runs.

Meanwhile, the AI models and algorithms developed by Stanford enabled the chase car to adapt dynamically to the motion of the lead car so that it can drift alongside without colliding.

Both cars were modified by GReddy and Toyota Racing Development (TRD) and built to the same specifications used in Formula Drift competitions to help the teams collect data with expert drivers in a controlled environment.

Both are equipped with computers and sensors that allow them to control their steering, throttle, and brakes while also sensing their motion. The cars share a dedicated WiFi network that allows them to communicate in real time by exchanging information such as their relative positions and planned trajectories.

To achieve autonomous tandem drifting, the vehicles must continually plan their steering, throttle, and brake commands and the trajectory they intend to follow using a technique called Nonlinear Model Predictive Control (NMPC).