Posted 2 months ago

Junior Software Engineer, Driving Planning

TokyoHybrid

AI Summary

A Junior Software Engineer in Driving Planning develops and optimizes vehicle velocity and path planning algorithms for advanced driver assistance and autonomous driving systems.

About this role

About Woven by Toyota

Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.

Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.

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TEAM

Dynamics and Control is a team that aims to develop safer and more secure vehicle maneuver applications for mass production vehicles. In advanced driving assistance systems such as autonomous driving, the ego-velocity and path planning technology is highly required so that the driving trajectory on public roads should be calculated efficiently and smoothly. Our driving planning engineers have been developing optimized velocity and path planning algorithms so as to emulate a skilled driver based on the surrounding environment and obstacles information acquired from the autonomous sensors and lane information from a high-precision map.

WHO ARE WE LOOKING FOR?

An expert in developing the optimized ego-velocity, driving planning and decision-making technology for the autonomous driving system or advanced driving assistance system. The specific areas are as follows.

Longitudinal and lateral vehicle dynamics control such as acceleration, de-acceleration and velocity

Velocity management based on the acquired data by autonomous sensors and lane information from a high-precision map.

Virtual development and validation with closed-simulation models.

Optimal velocity and driving planning algorithms subject to environmental, perceptual capabilities, high-precision map and actuation constraints.

Cross-functional discussions about vehicle controller and actuator performance, and contribute to motion control design reviews

RESPONSIBILITIES

Developing driving planning algorithms to control vehicles in complex and sensitive surrounding environments

Realizing safer and more secure autonomous driving systems and driver assistance systems through collaboration across different functions

Developing efficient real-time ADAS applications for embedded systems

Becoming familiar with cutting-edge vehicle dynamics control and driving planning technologies, and incorporating them into feasible application software for real-time platforms

Evaluating application functionality and performance using data acquired by test vehicles or vehicle simulators

To understand and align with the customer’s requirements, and define the software requirements